Copyright 1993 by the American Psychological Association, Inc.
OO33-295X/93/S3.OO

Psychological Review
1993, Vol. 100. No. 3, 363-406

The Role of Deliberate Practice in the Acquisition of Expert Performance
K. Anders Ericsson, Ralf Th. Krampe, and Clemens Tesch-Romer
The theoretical framework presented in this article explains expert performance as the end result ofindividuals' prolonged efforts to improve performance while negotiating motivational and external
constraints. In most domains of expertise, individuals begin in their childhood a regimen ofeffortful activities (deliberate practice) designed to optimize improvement. Individual differences,even among elite performers, are closely related to assessed amounts of deliberate practice. Many
characteristics once believed to reflect innate talent are actually the result of intense practiceextended for a minimum of 10 years. Analysis of expert performance provides unique evidence on
the potential and limits of extreme environmental adaptation and learning.

Our civilization has always recognized exceptional individuals, whose performance in sports, the arts, and science isvastly superior to that of the rest of the population. Speculations on the causes of these individuals' extraordinary abilities
and performance are as old as the first records of their achievements. Early accounts commonly attribute these individuals'
outstanding performance to divine intervention, such as theinfluence of the stars or organs in their bodies, or to special
gifts (Murray, 1989). As science progressed, these explanations
became less acceptable. Contemporary accounts assert that thecharacteristics responsible for exceptional performance are innate and are genetically transmitted.
The simplicity of these accounts is attractive, but more isneeded. A truly scientific account of exceptional performancemust completely describe both the development leading to exceptional performance and the genetic and acquired characteristics that mediate it. This account must specify the criticaldifferences between exceptional and ordinary performers. It
must also show that any postulated genetic differences can behereditary and are plausible from an evolutionary perspective.
Theoreticians in behavioral genetics (Plomin, DeFries, &McClearn, 1990) now argue that this is a very challenging task
K. Anders Ericsson, Institute of Cognitive Science, University ofColorado at Boulder; Ralf Th. Krampe and Clemens Tesch-Romer,
Max Planck Institute for Human Development and Education, Berlin,
Federal Republic of Germany.
The empirical research for this article was conducted at the Max
Planck Institute for Human Development in Berlin. Research support
by the Max Planck Society and support and encouragement from Paul
Baltes are gratefully acknowledged.
We thank Peter Usinger and Stefanie Heizmann for their help in thedata collection and Catherine Ashworth, Gregory Carey, Robert
Crutcher, Janet Grassia, Reid Hastie, Stefanie Heizmann, Charles
Judd, Ronald Kellogg, Robert Levin, Clayton Lewis, William Oliver,Peter Poison, Robert Rehder, Kurt Schlesinger, Vivian Schneider, andJames Wilson for their valuable comments on earlier drafts of thisarticle. Helpful suggestions and valuable criticism by Richard Shiffrin
on previously submitted versions of this article are gratefully acknowledged.
Correspondence concerning this article should be sent to K. Anders
Ericsson, who is now at the Department of Psychology R-54, Florida
State University, Tallahassee, Florida 32306-1051.

because observed behavior is the result of interactions between
environmental factors and genes during the extended period ofdevelopment. Therefore, to better understand expert and exceptional performance, we must require that the account specify the different environmental factors that could selectively
promote and facilitate the achievement of such performance. In
addition, recent research on expert performance and expertise(Chi, Glaser, & Farr, 1988; Ericsson & Smith, 1991a) has shownthat important characteristics of experts' superior performance
are acquired through experience and that the effect of practiceon performance is larger than earlier believed possible. For thisreason, an account of exceptional performance must specify
the environmental circumstances, such as the duration andstructure of activities, and necessary minimal biological attributes that lead to the acquisition of such characteristics and acorresponding level of performance.
An account that explains how a majority of individuals canattain a given level of expert performance might seem inherently unable to explain the exceptional performance of only asmall number of individuals. However, if such an empiricalaccount could be empirically supported, then the extreme
characteristics of experts could be viewed as having been acquired through learning and adaptation, and studies of expert
performance could provide unique insights into the possibilities and limits of change in cognitive capacities and bodilyfunctions. In this article we propose a theoretical frameworkthat explains expert performance in terms of acquired characteristics resulting from extended deliberate practice and that
limits the role of innate (inherited) characteristics to generallevels of activity and emotionality. We provide empirical support from two new studies and from already published evidence on expert performance in many different domains.
Brief Historical Background
Sir Francis Galton was the first scientist to investigate thepossibility that excellence in diverse fields and domains has acommon set of causes. He found that eminent individuals in
the British Isles were more likely to have close relatives who
were also eminent—although not necessarily in the same domain—than to have distant relatives who were eminent. He
concluded that eminence, that is, exceptional performance in a

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field, must be transmitted from parents to their offspring. Galton (1869/1979) argued that eminence was a virtually inevitable consequence of inherited "natural ability," which was the
conjunction of three types of elements:
By natural ability, I mean those qualities of intellect and disposition, which urge and qualify a man to perform acts that lead to
reputation. I do not mean capacity without zeal, nor zeal without
capacity, nor even a combination of both of them, without anadequate power of doing a great deal of very laborious work. (p.
37)
If a man is gifted with vast intellectual ability, eagerness towork, and power of working, I cannot comprehend how such aman should be repressed, (p. 39)

Galton readily acknowledged the importance of physiological
exercises for improvement in motor performance and drew a
direct analogy to improvement of mental powers through studying and education. In his view, hereditary factors determine thelimit of the attainable performance for a given individual:
So long as he is a novice, he perhaps flatters himself there is hardly
an assignable limit to the education of his muscles; but the daily
gain is soon discovered to diminish, and at last it vanishes altogether. His maximum performance becomes a rigidly determinate quantity. (Galton, 1869/1979, p. 15)
Even a hundred years later, Galton's conceptualization of eminent performance as reflecting a higher level of ultimate performance determined primarily by innate capacities (talent) is still
the modal view among people outside genetics and behavioral
genetics. Genetic influences are still incorrectly viewed as deterministic factors that lead to unmodifiable consequences determining the structure of the human body and its nervous
system (Plomin, 1991). Galton's recognition of the interaction
between environmental and genetic factors is clearly shown in
his tri-part definition of natural ability as innate capacity, zeal,
and power to do very laborious work. The last two factors arealso likely to have a genetic component as we argue later in thisarticle. Nonetheless, the study of eminent performance subsequent to Galton has given far less emphasis to zeal and power todo very laborious work and has focused primarily on genetic
influences on structure and capacities. Everyone agrees thatthe shared characteristics of the human body and its nervous
system are due to shared genes. Similarly, the successful identification of genetic factors influencing individual differences inheight and other physical characteristics has inspired researchers to search for genetic mechanisms regulating individual differences in mental capacities. Hence the focus of research on talent has been on finding similar basic structuraldifferences in the nervous system that might mediate stabledifferences in expert performance.

Natural Abilities and Other Stable Characteristics
If genetic factors rigidly determine maximal performance, it
is reasonable to assume that these genetic factors cannot be
influenced by practice and training and hence remain stable
across time. Early genetic research showed that many physicaland anatomical attributes, such as height and facial features, arelargely determined by hereditary factors. In many sports theheight of elite athletes is systematically different from that of

the normal population. Greater height is an obvious advantage
in basketball, high jumping, and most sports emphasizing
strength. Shorter height is an advantage in gymnastics. Differences in height were found to discriminate well among maleathletes of different events at the Olympic games in Montreal,
although the average height of all athletes did not differ fromthat of a control group of students (Carter, Ross, Aubrey, Hebbelinck, & Borms, 1982). Elite athletes also differ in the size of
their muscles, such as arm girth, and in the amount of fat measured by skin folds. Endurance athletes have a much higher
aerobic ability, larger hearts, more capillaries supplying blood
to muscles, and a higher percentage of slow-twitch muscle
fibers (Ericsson, 1990). Until quite recently researchers commonly believed that percentages of muscle fiber types and aerobic power "are more than 90% determined by heredity formales and females" (Brown & Mahoney, 1984, p. 609). Some
researchers have therefore reasoned by analogy that basic general characteristics of the nervous system, such as speed ofneural transmission and memory capacities, have a genetic origin and cannot be changed through training and practice.
Early efforts to find stable individual differences in neuraltransmission speed with simple response time (RT) and otherbasic capacities were remarkably unsuccessful (Guilford, 1967).
Binet (Varon, 1935) started out using tests of basic perceptualand cognitive capacities to measure IQ, but found large practiceeffects, which were later documented by Gibson (1969). Binet
eventually developed successful IQ tests derived from tests
measuring comprehension, knowledge, and acquired skills. Because IQ reflects both environmental and genetic factors, recent research has challenged its interpretation and relation to
successful performance outside the school environment (Ceci,
1990; Howe, 1990). The relation of IQ to exceptional performance is rather weak in many domains, including music(Shuter-Dyson, 1982) and chess (Doll & Mayr, 1987). For scientists, engineers, and medical doctors that complete the required
education and training, the correlations between ability measures and occupational success are only around 0.2, accounting
for only 4% of the variance (Baird, 1985). More generally, prediction of occupational success from psychometric tests has notbeen very successful (Tyler, 1965). In a review of more than one
hundred studies, Ghiselli (1966) found the average correlation
between success-on-the-job measuring and aptitude-test scores
to be 0.19. Aptitude tests can predict performance immediately
after training with an average correlation of 0.3, but the correlation between performance after training and final performanceon the job is only about 0.2 (Ghiselli, 1966). Reviews of subsequent research (Baird, 1985; Linn, 1982) have reported very
similar correlation estimates. When corrections were made forthe restriction of range of these samples and for unreliability of
performance measures, Hunter and Hunter (1984) found that
only cognitive ability emerged as a useful predictor with anaverage adjusted correlation of 0.5 with early job performance.
However, a recent review (Hulin, Henry, & Noon, 1990) has
shown that with increased experience on the job the predictive
validities of ability tests for performance decrease over time byan average correlation of 0.6 (after corrections for restrictions ofrange and unreliability of performance measures). This implies
that ability tests can predict early performance on a job,
whereas final performance is poorly predicted. Even for a well-THE ROLE OF DELIBERATE PRACTICE
defined skill, such as typing, with relatively unselect groups ofsubjects, numerous efforts to predict the attained performancefrom pretraining aptitude tests have failed (Clem, 1955). Striking differences between eminent individuals (experts) and lessaccomplished individuals are found, not surprisingly, when
their current performance in the field of expertise is compared(Ericsson & Smith, 1991 b); experts are faster and more accurate
than less accomplished individuals. However, experts' superior
speed in their domain of expertise does not transfer to generaltests of speed, such as simple RT, or to general tests of perception (Starkes, 1987; Starkes & Deakin, 1984). Similarly, experts'
memory for representative stimuli from their domain is vastly
superior to that of lesser experts, especially for briefly presented stimuli. But when tested on randomly rearranged versions of representative stimuli from their domain presented
with short exposures or on materials outside their domain, thememory of experts is no better than that of ordinary individuals.
The domain-specific nature of experts' superior performance implies that acquired knowledge and skill are important
to attainment of expert performance. We can cite only two abilities that investigators have argued directly reflect genetic factors. Some successful musicians can recognize a musical note inisolation by its pitch (perfect pitch). Championship-level typists can tap their fingers faster than normal (Book, 1924;
Keele & Hawkins, 1982). Although we claim that genetic factors have little direct impact on ultimate adult performance, aplausible role for hereditary factors is in the developmental history of an individual. Superior performance by very young
children without prior instruction may suggest exceptional
promise, leading to the early onset of training. This in turnleads to a consistently greater accumulation of practice (andhence, by our framework, performance) relative to later-starting individuals. In the General Discussion section we consider
this potential indirect role of innate talent at length, concluding
instead that unique environmental conditions and parental
support, rather than talent, may be the important factors determining the initial onset of training and ultimate performance.
In summary, the search for stable heritable characteristics
that could predict or at least account for the superior performance of eminent individuals has been surprisingly unsuccessful. The best evidence for the effect of heritable characteristics
comes from several types of sports, for which anatomical characteristics such as height systematically differ for elite performers compared with the average population. The belief thatthe striking differences between expert performers and lessaccomplished performers reflect innate abilities (talent) is sostrong that the failure to identify the specific talents necessaryfor expert performance in a given domain is viewed, at most, asa temporary problem until the relevant talents are discovered.
The conviction in the importance of talent appears to be basedon the insufficiency of alternative hypotheses to explain the
exceptional nature of expert performance. If one agrees with
Galton's plausible claim that the improvements resulting fromexperience and practice occur during limited time until a stablemaximal level of performance is attained, the factors limiting
further improvement must be fixed and unmodifiable by environmental factors. The most likely source of such unmodifi-

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able factors is genetic. However, this argument is only valid if
the associated assumptions can be verified empirically.
In the following two sections we examine the assumptionthat with extensive experience in a domain a maximal level of
performance is automatically reached and that the period of
improvement has a relatively limited duration, especially fortalented individuals.
Does Practice and Experience Inevitably Lead to
Maximal Performance?
The view that merely engaging in a sufficient amount ofpractice, regardless of the structure of that practice, leads tomaximal performance has a long and contested history. In theirclassic studies of Morse Code operators, Bryan and Harter(1897, 1899) identified plateaus in skill acquisition, when forlong periods subjects seemed unable to attain further improvements. However, with extended efforts, subjects could restructure their skill to overcome plateaus. Keller (1958) later showedthat these plateaus in Morse Code reception were not an inevitable characteristic of skill acquisition, but could be avoided bydifferent and better training methods. Nonetheless, Bryan andHarter (1897, 1899) had clearly shown that with mere repetition, improvement of performance was often arrested at lessthan maximal levels, and further improvement required effortful reorganization of the skill. Even very experienced Morse
Code operators could be encouraged to dramatically increase
their performance through deliberate efforts when further improvements were required for promotions and external rewards(Bryan & Harter, 1897).
More generally, Thorndike (1921) observed that adults perform at a level far from their maximal level even for tasks theyfrequently carry out. For instance, adults tend to write more
slowly and illegibly than they are capable of doing. Likewise,
adults (including clerks with many years of frequent daily experience) add numbers far more slowly than they can when they
are doing their best. Thorndike (1921, p. 178) accounts for thesecurious observations with the following comment: "It is that wehave too many other improvements to make, or do not know
how to direct our practice, or do not really care enough about
improving, or some mixture of these three conditions." In support of this claim, he reported several laboratory studies and astudy of experienced typesetters by Aschaffenburg (1896),
which showed gradual improvements of up to 25% as a result ofcontinued testing. Kitson (as described in Book & Norvell,1922) found that during a 20-week period, typesetters witharound 10 years of experience gradually improved their job
performance between 58% and 97% in response to a bonus
system rewarding higher performance. Dvorak, Merrick, Dealey, and Ford (1936) reported substantial improvements in experienced typists as a result of deliberate efforts.
Because performance in sports, especially, has been measured under standardized conditions, and the best performance has been recorded at world, national, district, and clublevels, it can be clearly demonstrated that performance has continually improved during this entire century. Schulz and Curnow (1988) found that throughout the history of the Olympic
Games, the best performance for all events has improved—insome cases by more than 50%. It is generally recognized that

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some of these improvements are due to equipment and rulechanges, but improvements are great even in events with minorchanges, such as running and swimming. Increases in duration,
intensity, and structure of training appear to play a major role.
The fastest time for the marathon in the 1896 Olympic Gameswas just a minute faster than the required entry time in large
marathon races such as the Boston Marathon (Ericsson, 1990).
The fastest rate of typing in the World Championship in typing
increased from 82 words per minute in 1904 to 147 words per
minute in 1923—an improvement of 80% (Book, 1925a). Evenin music there is evidence for improved skill. When Tchaikovsky asked two of the greatest violinists of his day to play his
violin concerto, they refused, deeming the score unplayable(Platt, 1966). Today, elite violinists consider this concerto partof the standard repertory. The improvement in music training
is so great that according to Roth (1982) the violin virtuoso
Paganini "would indeed cut a sorry figure if placed upon themodern concert stage" (p. 23).
In virtually all domains, insights and knowledge are steadily
accumulating and the criteria for eminent as well as expert
performance undergo continuous change. To reach the status ofan expert in a domain it is sufficient to master the existingknowledge and techniques. To make an eminent achievement
one must first achieve the level of an expert and then in addition surpass the achievements of already recognized eminent
people and make innovative contributions to the domain. In
sum, the belief that a sufficient amount of experience or practice leads to maximal performance appears incorrect.
Preparation Time Required for Attainment of
Exceptional Performance
There is a relatively widespread conception that if individuals
are innately talented, they can easily and rapidly achieve an
exceptional level of performance once they have acquired basic
skills and knowledge. Biographical material disproves this notion. In their classic study of expertise in chess, Simon andChase (1973) observed that nobody had attained the level of aninternational chess master (grandmaster) "with less than about
a decade's intense preparation with the game" (p. 402). Simon
and Chase estimated that the amount of knowledge a chessmaster has acquired is comparable in size to the vocabulary ofan adult native speaker of English. It takes normal individuals
approximately a decade to acquire this vocabulary. Similarly,
Krogius (1976) showed that the time between chess players'
first learning the rules of chess and attaining international
chess master status was 11.7 years for those who learned chessrules late (after age 11) and even longer for those who started
early, that is, 16.5 years. If only well-established domains with alarge number of active individuals are considered we know of
only a small number of exceptions to the general rule that individuals require 10 or more years of preparation to attain international-level performance. The exceptions in this century, suchas the famous chess players, Bobby Fischer and Salo Flohr, were
only a year shy of the prerequisite 10 years of preparation (Krogius, 1976).
J. R. Hayes (1981) confirmed that 10 years' experience isnecessary in another domain, musical composition. He calculated an average of about 20 years from the time individuals

started to study music until they first composed an outstanding
piece of music. According to Hayes, this long preparation period is necessary because "the composer must know the
timbres of the various instruments and the sound, look, andfeel of chords and key structures" (p. 209). Most important,
Hayes showed that the 10 or more years of necessary experience
was not an artifact. Because musicians start very early, insufficient development may restrict their ability to compose before
attaining adulthood. Those who started at ages younger than 6
years did not write their first eminent composition until 16.5
years later; those who started between ages 6 and 9 and older
than 10 years of age required 22 and 21.5 years, respectively, tocompose their first distinguished work. Simon and Chase's(1973) "10-year rule" is supported by data from a wide range ofdomains: music (Sosniak, 1985), mathematics (Gustin, 1985),
tennis (Monsaas, 1985), swimming (Kalinowski, 1985), andlong-distance running (Wallingford, 1975).
Long periods of necessary preparation can also be inferred
for writers and scientists, although the starting point of theircareers is more difficult to determine. Scientists have reported
that they made a career decision during their middle or lateteens, whereas they most often published a truly major contribution one or two decades later (Lehmann, 1953). Raskin(1936), who analyzed the 120 most important scientists and 123
most famous poets and authors in the 19th century, found thatthe average age at which scientists published their first work
was 25.2; poets and authors published their first work at the
average age of 24.2. Moreover, many years of preparation preceded first publication. The average ages at which the same
individuals produced their greatest work were 35.4 for scientists and 34.3 for poets and authors. That is, on average, morethan 10 years elapsed between these scientists' and authors'
first work and their best work. In many other domains, thehighest level of expert performance is displayed by individuals
with more than 10 years of experience: evaluation of livestock(Phelps&Shanteau, 1978), diagnosis of X-rays (Lesgold, 1984),
and medical diagnosis (Patel & Groen, 1991). This evidence isconsistent with Galton's (1869/1979) claim that motivation andperseverance are necessary for attainment of eminent performance.
Our review has also shown that the maximal level of performance for individuals in a given domain is not attained automatically as function of extended experience, but the level of
performance can be increased even by highly experienced individuals as a result of deliberate efforts to improve. Hence, stablelevels of performance after extended experience are not rigidly
limited by unmodifiable, possibly innate, factors, but can befurther increased by deliberate efforts. We have shown that expert performance is acquired slowly over a very long time as aresult of practice and that the highest levels of performance andachievement appear to require at least around 10 years of intense prior preparation. However the relation between acquired performance and the amount of practice and experience
was found to be weak to moderate in the earlier review. We
propose that the reason for this comparatively weak relation isthat the current definition of practice is vague. If we are to
improve our understanding of the environmental influences
mediated through participation in different activities, we must
analyze the types of activities commonly called practice.

THE ROLE OF DELIBERATE PRACTICEThe Role of Deliberate PracticeIn this section we characterize deliberate practice—those activities that have been found most effective in improving performance. We then contrast deliberate practice with activities that
tend to occur more frequently in various domains. Finally, we
propose a theoretical framework that explains how expert performance can be attained through deliberate practice.
Characteristics of Deliberate Practice
The basic skills required for living in a culture are acquiredby virtually all children as part of normal social interaction
with a minimum of instruction. In contrast, the skills of reading, writing, and arithmetic have been explicitly taught inschools by teachers with assigned activities of, for example,
copying of presented material, for more than 3 thousand years(Eby & Arrowood, 1940). We want to distinguish activities invented with the primary purpose of attaining and improving
skills from other types of everyday activities, in which learning
may be an indirect result. On the basis of several thousand
years of education, along with more recent laboratory researchon learning and skill acquisition, a number of conditions for
optimal learning and improvement of performance have been
uncovered (Bower & Hilgard, 1981; Gagne, 1970). The mostcited condition concerns the subjects' motivation to attend to
the task and exert effort to improve their performance. In addition, the design of the task should take into account the preexisting knowledge of the learners so that the task can be correctly
understood after a brief period of instruction. The subjects
should receive immediate informative feedback and knowledgeof results of their performance. The subjects should repeatedly
perform the same or similar tasks.
When these conditions are met, practice improves accuracy
and speed of performance on cognitive, perceptual, and motor
tasks (Fitts & Posner, 1967; Gibson, 1969; Welford, 1968). Tasks
used in laboratory studies of learning that are designed to focus
on the accuracy of performance clearly display the relevant cuesand the relevant feedback. Studies focusing on speed of performance tend to use easy tasks, where highly accurate performance is rapidly attained, and subjects are instructed to increase the speed of performance while maintaining the highlevel of accuracy. Under these conditions subjects' performance
improves monotonically as a function of the amount of practiceaccording to the power law (J. R. Anderson, 1982; Newell &Rosenbloom, 1981). In the absence of adequate feedback, efficient learning is impossible and improvement only minimal
even for highly motivated subjects. Hence mere repetition of anactivity will not automatically lead to improvement in, especially, accuracy of performance (Trowbridge & Cason, 1932).
When laboratory training is extended over longer time periods, studies show that providing a motivated individual withrepeated exposure to a task does not ensure that the highest
levels of performance will be attained. Assessment of subjects'
methods shows that inadequate strategies often account for thelack of improvement. For example, in their study on the effects
of practice on digit span, Chase and Ericsson (1981) found a
subject who kept rehearsing the digits whose performance
showed only minimal improvement. In contrast, all subjects

367

who used preexisting knowledge to encode the presented digits
improved dramatically. One subject who discovered how to use
efficient retrieval structures increased his performance by over
1000%. Recent reviews of exceptional memory performance(Ericsson, 1985,1988) show that a small set of general methods
underlie such performance. After being instructed to use adequate strategies, subjects have attained exceptional levels of
memory performance after extended practice (Baltes & Kliegl,
1992; Kliegl, Smith, & Baltes, 1989; 1990).
Early investigators of extended skill acquisition in typing(Book, 1925b; Dvorak et al., 1936) and other perceptual-motor
skills (Kao, 1937) carefully monitored improvements in performance and collected verbal reports on subjects' cognitive processes. These studies revealed subjects' active search for methods to improve performance and found that changes in methods could often be related to clear improvements. Other studies(Chase & Ericsson, 1981; VanLehn, 1991) have also shown that
subjects actively try out different methods and refine methods
in response to errors and violated expectations. The criticalimportance of a correct method or strategy has also been demonstrated in date calculation (Addis & O. A. Parsons, as described in Ericsson & Faivre, 1988), mental multiplication(Chase & Ericsson, 1982; Staszewski, 1988), absolute judgmentof colors and pitches (for a review see Ericsson & Faivre, 1988),
motor skills (Norman, 1976), and methods of work (R. H. Seashore, 1939).
The inability of some subjects to discover new methods has
sometimes been interpreted as evidence for basic cognitive or
perceptual deficits, especially for performance of seemingly
simple tasks. However, specific instruction or the generation of
new methods can eventually enhance improvement temporarily arrested at suboptimal levels. As the complexity of a desired skill increases beyond the simple structure of most laboratory tasks, the logically possible methods to correctly and incorrectly perform the task by subjects increase as well. To assure
effective learning, subjects ideally should be given explicit instructions about the best method and be supervised by ateacher to allow individualized diagnosis of errors, informative
feedback, and remedial part training. The instructor has toorganize the sequence of appropriate training tasks and monitor improvement to decide when transitions to more complex
and challenging tasks are appropriate. Although it is possible togenerate curricula and use group instruction, it is generally
recognized that individualized supervision by a teacher is superior. Research in education reviewed by Bloom (1984) showsthat when students are randomly assigned to instruction by atutor or to conventional teaching, tutoring yields better performance by two standard deviations—the average tutored student performed at the 98th percentile of students taught withthe conventional method. Interestingly, the correlation between
prior achievement and achievement on the current course was
reduced and corresponded to only about 6% of the variance forthe tutored subjects as compared with around 36% for studentstaught with conventional methods. More generally, improved
instruction appears to benefit subjects with lower cognitive ability
more than high-ability subjects thus lowering the earlier
discussed correlation between cognitive ability and early performance seen under standard training conditions.
Most contemporary domains of expertise have evolved over

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centuries from activities originally centered around playful interaction with learning through active participation. As the levels of performance in the domain increased in skill and complexity, methods to explicitly instruct and train individuals
were developed. In all major domains there has been a steady
accumulation of knowledge about the best methods to attain ahigh level of performance and the associated practice activities
leading to this performance. Full-time teachers and coaches areavailable for hire and supervise the personalized training ofindividuals at different levels of performance starting with beginners. Throughout development toward expert performance,
the teachers and coaches instruct the individuals to engage inpractice activities that maximize improvement. Given the costof individualized instruction, the teacher designs practice activities that the individual can engage in between meetings withthe teacher. We call these practice activities deliberate practiceand distinguish them from other activities, such as playful interaction, paid work, and observation of others, that individuals can pursue in the domain.
Comparison of Deliberate Practice to Other Types ofDomain-Related Activities
Consider three general types of activities, namely, work, play,and deliberate practice. Work includes public performance,competitions, services rendered for pay, and other activities directly motivated by external rewards. Play includes activities
that have no explicit goal and that are inherently enjoyable.
Deliberate practice includes activities that have been speciallydesigned to improve the current level of performance. The
goals, costs, and rewards of these three types of activities differ,as does the frequency with which individuals pursue them.
Public performance and competitions are constrained intime; these activities as well as rendering a service for pay require that individuals give their best performance at a given
time. The distinction between work and training (deliberate
practice) is generally recognized. Individuals given a new job
are often given some period of apprenticeship or supervised
activity during which they are supposed to acquire an acceptable level of reliable performance. Thereafter individuals are
expected to give their best performance in work activities andhence individuals rely on previously well-entrenched methods
rather than exploring alternative methods with unknown reliability. The costs of mistakes or failures to meet deadlines are
generally great, which discourages learning and acquisition of
new and possibly better methods during the time of work. For
example, highly experienced users of computer software applications are found to use a small set of commands, thus avoiding
the learning of a larger set of more efficient commands (seeAshworth, 1992, for a review). Although work activities offersome opportunities for learning, they are far from optimal. In
contrast, deliberate practice would allow for repeated experiences in which the individual can attend to the critical aspectsof the situation and incrementally improve her or his performance in response to knowledge of results, feedback, or bothfrom a teacher. Let us briefly illustrate the differences between
work and deliberate practice. During a 3-hr baseball game, abatter may get only 5-15 pitches (perhaps one or two relevant toa particular weakness), whereas during optimal practice of thesame duration, a batter working with a dedicated pitcher has
several hundred batting opportunities, where this weakness canbe systematically explored (T. Williams, 1988).
The external rewards of work activities include social recognition and, most important, money in the form of prizes and pay,
which enables performers to sustain a living. In play and deliberate practice, external rewards are almost completely lacking.
The goal of play is the activity itself, and the inherent enjoymentof it is evident in children who spontaneously play for extended
periods of time. Recent analyses of inherent enjoyment in
adults reveal an enjoyable state of "flow," in which individuals
are completely immersed in an activity (Csikszentmihalyi,1990). Similarly, analyses of reported "peak experiences" insports reveal an enjoyable state of effortless mastery and execution of an activity (Ravizza, 1984). This state of diffused attention is almost antithetical to focused attention required by deliberate practice to maximize feedback and information about
corrective action.
In contrast to play, deliberate practice is a highly structured
activity, the explicit goal of which is to improve performance.
Specific tasks are invented to overcome weaknesses, and performance is carefully monitored to provide cues for ways to improve it further. We claim that deliberate practice requires effort and is not inherently enjoyable. Individuals are motivatedto practice because practice improves performance. In addition, engaging in deliberate practice generates no immediate
monetary rewards and generates costs associated with access toteachers and training environments. Thus, an understanding of
the long-term consequences of deliberate practice is important.

Theoretical Framework for the Acquisition of Expert
Performance
We now outline a framework within which we can explain
how differential levels of performance are attained as a function of deliberate practice. Our basic assumption—the "monotonic benefits assumption"—is that the amount of time an individual is engaged in deliberate practice activities is monotonically related to that individual's acquired performance. This
assumption can be tested empirically. It follows from this assumption that individuals should attempt to maximize theamount of time they spend on deliberate practice to reach expert performance.
However, maximization of deliberate practice is neither
short-lived nor simple. It extends over a period of at least 10
years and involves optimization within several constraints.
First, deliberate practice requires available time and energy forthe individual as well as access to teachers, training material,
and training facilities (the resource constraint). If the individual
is a child or adolescent, someone in the individual's environment must be willing to pay for training material and the timeof professional teachers, as well as for transportation to andfrom training facilities and competitions.
Second, engagement in deliberate practice is not inherently
motivating. Performers consider it instrumental in achieving
further improvements in performance (the motivational constraint). The lack of inherent reward or enjoyment in practice as
distinct from the enjoyment of the result (improvement) is con-THE ROLE OF DELIBERATE PRACTICE

sistent with the fact that individuals in a domain rarely initiate
practice spontaneously.
Finally, deliberate practice is an effortful activity that can besustained only for a limited time each day during extended
periods without leading to exhaustion (effort constraint). To
maximize gains from long-term practice, individuals must
avoid exhaustion and must limit practice to an amount fromwhich they can completely recover on a daily or weekly basis.
Attaining Expert Performance
Considering the cost of pursuing expert-level performanceand the small number of individuals who, out of millions ofchildren exposed to such domains as sports and music, canmake a living as professionals, it seems remarkable that individuals get started and are encouraged to continue. From many
interviews with international-level performers in several domains, Bloom (1985b) found that these individuals start out aschildren by engaging in playful activities in the domain. Aftersome period of playful and enjoyable experience they reveal"talent" or promise. At this point parents typically suggest thestart of instruction by a teacher and limited amounts of deliberate practice. The parents support their children in acquiring
regular habits of practice and teach their children about the
instrumental value of deliberate practice by noticing improvements in performance. With increased experience and deliberate practice, individuals' performance in the domain reflects
an inseparable combination of practice and innate talent. We
rely on Bloom's (1985b) characterization of the period of preparation in three phases, which are illustrated in Figure 1.
The first phase begins with an individual's introduction toactivities in the domain and ends with the start of instruction
and deliberate practice. The second phase consists of an extended period of preparation and ends with the individual'scommitment to pursue activities in the domain on a full-timebasis. The third phase consists of full-time commitment to improving performance and ends when the individual either canmake a living as a professional performer in the domain or369

terminates full-time engagement in the activity. During all
three phases the individual requires support from externalsources, such as parents, teachers, and educational institutions.
This framework needs to be extended with a fourth phase toaccommodate eminent performance. During this fourth phase
the individuals go beyond the knowledge of their teachers tomake a unique innovative contribution to their domain.
To be complete, our theoretical framework must show how
individuals negotiate the various constraints on deliberate
practice during that first decade of preparation necessary for
attaining international-level performance. There are several
methodological problems involved in demonstrating the relevant processes. During the decade or two leading to adult expert performance, many aspects of training and evaluation
change. In the beginning, a child's performance is comparedwith that of other children of the same age in the local neighborhood. At the start of participation in competitions, the reference group consists of other trained individuals of similar ages
from a larger area. Success at these earlier stages may eventuallylead to participation in competitions at a national and international level. At increased levels of performance, the practiceactivities obviously change and so do the criteria of evaluation.
In the performance of music, children and adolescents are
judged principally on their technical proficiency. Expert adultperformers, however, are judged on their interpretation andability to express emotions through music (Sloboda, 1991). The
inability of many child prodigies in music to succeed as adultmusicians (Bamberger, 1986; Barlow, 1952) is often attributed
to difficulties making this transition—possibly resulting frominappropriate training and instruction during the early andmiddle phases of music training. To become outstanding musicians at the international level, individuals have to contribute
unique interpretations of music (Roth, 1982). Similar considerations may explain why mathematical prodigies can fail as
adult mathematicians. The lack of overlap in the performanceof precocious children and adult scientists in mathematics iseven clearer than in music: Superior ability in mental addition

370

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

and multiplication demonstrate efficiency in the mechanics ofmathematics, whereas major adult contributions in mathematics reflect insights into the structure of mathematical problems
and domains. The criteria for eminent performance goesbeyond expert mastery of available knowledge and skills andrequires an important and innovative contribution to the domain. An eminent musician can contribute new techniques anddistinct interpretations of existing music, and eminent chessplayers discover new variants of chess openings and advancethe knowledge of chess. In the arts and sciences, eminentachievements involve contributions of new ideas, theories, andmethods.
In most domains it is impossible to assess retrospectively the
cognitive aspects of the development of precocious exceptional
performers. Precocious painters may be an exception (see J.
Radford's, 1990, review). Pariser (1987) analyzed drawings
completed by Klee, Toulouse-Lautrec, and Picasso until age 20,
and concluded that these three "gifted" individuals encountered and mastered problems in graphic development in ways
similar to those of the "less-gifted" (p. 53). Their juvenile drawings include "a fair number of awkward, flawed and unexceptional drawings" (Pariser, 1987, p. 65), suggesting that instruction and practice strongly affected even these three exceptional
artists. The age at which eminent individuals attain their best
performance is much later in their 20s and 30s (Lehmann,
1953). In fact any significant achievements in literature, music
composition, visual arts, and most other domains before age 16
are exceedingly rare (Barlow, 1952). (Judit Polgar and Bobbie
Fischer attained the level of international grandmasters inchess at age 15; we discuss their developmental history later.)
The methodology we applied in our studies takes these considerations into account as we demonstrate later. At this point wemust further specify the constraints inherent in the attainmentof exceptional performance.
Resource Constraint
International-level performers often receive their first exposure to their domain between the ages of 3 and 8. Obviously,
their parents are responsible for providing this early access.
Parents and guardians, in encouraging the childrens' activity
and monitoring performance, make possible the discovery of
early signs of "talent" and promise. The parents' interest is also
critical in aiding children's transition to deliberate practice andproviding facilities for practice, such as musical instruments formusicians, tennis courts for tennis players, and ice arenas forskaters. Bloom (1985a) and his colleagues show that transportation for young individuals to and from practice, meetings withthe teachers, and competitions can almost completely occupy
parents' free time, and the direct economic costs of sustaining
these activities are substantial. The parents' costs for a nationallevel swimmer is estimated by Chambliss (1988) to exceed 5
thousand dollars per year. In many cases, the family is evenwilling to move to a location close to the best training facilities
offering year-round opportunities for practice. These extraordinary commitments by parents are probably based on the belief
that their children are somehow special and particularly likely
to succeed. Bloom (1985b) found that there seems to be at least
one central person in a promising child's near environment who

firmly believes, as the child develops, that the child is special,that is, talented in the domain. This person's belief prevails
even though Bloom (1985b) found no evidence that, during theearly phases, the individual exhibited any clear evidence of prowess. However, Bloom (1985b) found that only one child perfamily was considered special. This is perhaps the best empirical evidence that each family's available resources are limited.
Effort Constraint
The central claim of our framework is that the level of performance an individual attains is directly related to the amount ofdeliberate practice. Hence, individuals seeking to maximize
their performance within some time period should maximize
the amount of deliberate practice they engage in during that
period. When this time period extends over months and years,
it is clear that maximization of an effortful activity is not simple
and that the traditional research on learning, which is limited
to a few sessions, provides little guidance. In this section, we
review evidence showing that the duration of effective daily
practice that can be sustained for long periods is limited, andthat according to teachers and training instructions, it is necessary to maintain full attention during the entire period of deliberate practice. We then discuss some consequences of increasing practice activity beyond its optimal duration and finallyconsider evidence that through training the daily duration ofdeliberate practice can be slowly increased over extended periods of time.
The limited duration of practice is the best evidence of theeffort it requires. When individuals, especially children, startpracticing in a given domain, the amount of practice is an houror less per day (Bloom, 1985b). Similarly, laboratory studies ofextended practice limit practice to about 1 hr for 3-5 days aweek (e.g., Chase & Ericsson, 1982; Schneider & Shiffrin, 1977;
Seibel, 1963). A number of training studies in real life havecompared the efficiency of practice durations ranging from 1 -8
hr per day. These studies show essentially no benefit from durations exceeding 4 hr per day and reduced benefits from practice
exceeding 2 hr (Welford, 1968; Woodworth & Schlosberg,1954). Many studies of the acquisition of typing skill (Baddeley& Longman, 1978; Dvorak et al.. 1936) and other perceptualmotor skills (Henshaw & Holman, 1930) indicate that the effective duration of deliberate practice may be closer to 1 hr per day.
Pirolli and J. R. Anderson (1985) found no increased learningfrom doubling the number of training trials per session in theirextended training study. The findings of these studies can begeneralized to situations in which training is extended over long
periods of time such as weeks, months, and years.
The goal of deliberate practice is improved performance, anddetailed analyses of the musicians' activities during practicesessions in music (Gruson, 1988; Miklaszewski, 1989) reveal
careful monitoring and problem solving by the musicians toattain the desired improvements. C. E. Seashore (1938/1967),
the pioneering researcher in music psychology, claimed, "Manya student becomes disgusted with music because he cannot
learn by dull drudgery. The command to rest is fully as important as to work in effective learning" (pp. 154-155). Both Auer
(1921), the famous violin teacher, and C. E. Seashore (1938/1967) recommended that practice periods be limited to less

371

THE ROLE OF DELIBERATE PRACTICE
than 1 hr with ample rest in between. A necessary precondition
for practice, according to Auer (1921), is that the individual be
fully attentive to his playing so that he or she will notice areas ofpotential improvement and avoid errors. Auer (1921) believes
that practice without such concentration is even detrimental to
improvement of performance. On the basis of an extended
study of Olympic swimmers, Chambliss (1988, 1989) argued
that the secret of attaining excellence is to always maintainclose attention to every detail of performance "each one done
correctly, time and again, until excellence in every detail becomes a firmly ingrained habit" (1989, p. 85).
Deliberate practice aimed at improving strength and endurance in sports clearly shows the importance of near maximal
effort during practice and the resulting fatigue. Physical activity
and exercise produce no benefit unless they are sufficiently
intense. Untrained adults must attain a minimum heart rate ofaround 140 beats per minute or 70% of their maximal heart rate
for an extended time at least three times a week to see improvements (Lamb, 1984). However, elite athletes train at muchhigher intensities to improve their performance. Athletes train
to maximize their performance in a specific event. In endurance events, such as marathon running, most of the training
consists of running at the highest speed an athlete can maintainfor extended periods. Improvements resulting from training appear to be more a function of intensity (as close to maximum as
possible) than of the total distance covered (Maughan, 1990). In
sprint events, where runners expend maximal effort for a shorttime, strength training is essential (P. F. Radford, 1990). Near
maximal efforts with a 3-s duration produce the most efficientresults for strength training (Klausen, 1990). Obviously suchnear-maximal training can be sustained only for limited periods even if these periods are interspersed with periods of rest.
Other objective indicators of the intensity of athletic training
include measurements of metabolic rate during the activity(MacLaren, 1990). Athletes need to consume many more calories than do normal adults simply to sustain their regular training program (Maughan, 1990). Costill et al. (1988) found thatsome swimmers experienced chronic muscular fatigue because
their intake of calories was insufficient to accommodate a recent increase in training activity. The exhausting effects of regular training are also evidenced by the standard practice of reducing the training level several days before a competition(Maughan, 1990; P. E Radford, 1990).
Under the assumption that practice draws on limited physical and mental resources, one would expect that the level ofpractice an individual can sustain for long periods of time islimited by the individual's ability to recover and thereby maintain a steady state from day to day. After the individual has
slowly adapted to a constant level of practice, increases ought tobe possible. In contrast, if an individual cannot recover each
day from a given level of practice, sustaining that level will leadto exhaustion and mental fatigue. The risk of physical injury
and chronic maladaptation will increase "runner's knee," shin
splints, and Achilles tendonitis for athletes (Subotnick, 1977)
and sores, tendonitis, and muscle spasms for musicians (Caldron et al., 1986). Inability to recover from the stress of training,which is viewed as necessary for improvement in sports, canlead to "staleness," "overtraining," and eventually "burnout."
These states are characterized not only by physical fatigue andsoreness but also by motivational problems such as lack of enthusiasm and even unwillingness to continue with a sport(Silva, 1990). The only known effective treatment for these conditions "consists of rest, and in some cases, complete abstention
from training and sporting activities may be necessary" (Hackney, Pearman, & Novack, 1990, p. 30).
Early in this century, considerable research was directed toward the subjective experience of mental fatigue and its consequences for performance. On the one hand, efforts to demonstrate decline in performance, even after consecutive days ofmental multiplication for 12 hr per day, have been remarkably
unsuccessful (Arai, 1912; Huxtable, White, & McCartor, 1946).
On the other hand, the subjective feelings of discomfort andaversion often become so strong that continuing these experiments beyond 4 days would seem very difficult, if not impossible. The best data on sustained intellectual activity comes fromfinancially independent authors. While completing a novel famous authors tend to write only for 4 hr during the morning,leaving the rest of the day for rest and recuperation (Cowley,
1959; Plimpton, 1977). Hence successful authors, who can control their work habits and are motivated to optimize their productivity, limit their most important intellectual activity to a
fixed daily amount when working on projects requiring long
periods of time to complete.
When individuals start with deliberate practice in a domain,
the initial duration of weekly practice is limited (Bloom,
1985b). Given that most future international-level performers
start at early ages, these brief durations are consistent with theshort duration (10-20 min per session) of long-term training
programs with children (see Howe, 1990, for a review). Consistent with the idea of slow adaptation to the demands of extended practice, individuals beginning to practice are encouraged to adopt a regular weekly schedule with practice periods ofrelatively fixed duration (Bloom, 1985b). After extended timewith an acceptable practice level, individuals adapt their bodies
and lives and can slowly and gradually increase the level ofpractice. Too rapid increases in the intensity of practice lead to"overuse and overtraining," which occur frequently in sports(Hackney et al, 1990; Silva, 1990) and even in music (Fry, 1986;
Newmark & Lederman, 1987). Bailey and Martin (1988) reportmany instances of successful 9- to 11-year-old children increasing their training to very high levels, only to experience motivational burnout and quit the domain altogether.
In summary, disregard of the effort constraint on deliberate
practice leads to injury and even failure. In the short term,
optimal deliberate practice maintains equilibrium between effort and recovery. In the long term, it negotiates the effort constraint by slow, regular increases in amounts of practice thatallow for adaptation to increased demands.
Motivational Constraint
A premise of our theoretical framework is that deliberate
practice is not inherently enjoyable and that individuals are
motivated to engage in it by its instrumental value in improving
performance. Hence, interested individuals need to be engaging in the activity and motivated to improve performance before they begin deliberate practice. Bloom (1985b) found evidence supporting this implication. His interviews with interna-

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K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

tional-level performers showed that parents typically initiateddeliberate practice after allowing their children several monthsof playful engagement in the domain and after noticing that
their children expressed interest and showed signs of promise.
The social reactions of parents and other individuals in theimmediate environment must be very important in establishing this original motivation.
At the start of deliberate practice, parents help their childkeep a regular daily practice schedule and point out the instrumental value of practice for improved performance (Bloom,
1985b). With increased experience and the aid of teachers andcoaches, the developing individual is able to internalize methods for assessing improvement and can thus concurrently monitor the effects of practice. As individuals get more involved in
the activities of a domain, competitions and public performances provide short-term goals for specific improvements. At
this point the motivation to practice becomes so closely connected to the goal of becoming an expert performer and so
integrated with the individual's daily life that motivation topractice, per se, cannot be easily assessed.
Certain naturally occurring events and changes illuminate
the relation between practice and performance. Activities inmany domains, especially sports, are seasonal because mostscheduled competitions occur during a single season of theyear. If individuals enjoyed deliberate practice, they ought topractice at a uniformly high level all year. Instead, athletes train
much harder during the preseason period and during the season itself; during the off season they often reduce the level oftraining dramatically (Reilly, 1990a; Reilly & Secher, 1990).
Many individuals who have practiced for a long period of time
give up their aspirations to compete and excel in an activity.
Without the goal of improving performance, the motivation to
engage in practice vanishes. Kaminski, Mayer, and Ruoff(1984) found that many elite adolescents who decided to stopcompeting remained active in the domain but virtually stopped
engaging in practice.
Some individuals have had to terminate their professional
careers for reasons unrelated to their ability to perform. In alongitudinal study of visual artists, Getzels and Csikszentmihalyi (1976) found that most artists were drawn to painting because it allowed social isolation. However, aspiring painters
have to promote social relations with art dealers, art critics, andbuyers to gain notoriety, increase the demand for their art, andgenerate sufficient sales for full-time artistic activity. Failure to
do so forced many of the best artists to take another job unrelated to painting. Once these artists could no longer commit
sufficient time and energy to maintain and improve their performance they stopped painting completely because they could
not accept performing at a lower level. This finding shows thatthe activity of painting as such is not inherently motivating but
rather the act of producing art that satisfies the artists' subjective criteria for quality.

Implications for Empirical Studies
Applied to an individual, our theoretical framework madethree types of predictions: (a) predictions about the developmental history; (b) predictions about current levels and habitsof practice; and (c) predictions about experts' evaluations re-garding the nature and role of deliberate practice activities thatare relevant throughout development.
Our framework made two important predictions about anindividual's development history. First, the past amount of deliberate practice is directly related to the individual's current
performance. More specifically, expert performance is notreached with less than 10 years of deliberate practice. Second,deliberate practice starts at low levels and increases slowly overtime. These predictions can be best tested in domains of expertise that are relatively independent of the traditional school
system and where deliberate practice can be easily identified
and measured. It is important that the domain has qualified
teachers who guide individuals in learning basic skills correctly
and direct them toward optimal practice activities. Music is one
such domain, and in the current studies we chose to study
individuals who perform at very high levels on a particular
instrument. To study individuals who had completed the 10year period of preparation and had made a commitment tomusic as a profession, we contacted the Music Academy in West
Berlin. This academy has an international reputation for its
training program for violinists. Violinists in this program wereasked to provide retrospective reports on their levels of deliberate practice over the years before they entered the academy sothat we might test our predictions.
Next, our framework made several predictions regarding thecurrent level and related habits in elite performers. First, thehighest improvement of performance, and indirectly the highest attained performance, is associated with the largest weekly
amounts of deliberate practice. We predicted that elite performers practice at a constant level from day to day to maximize improvement over extended periods of time. Furthermore, the daily periods of deliberate practice should be of limited duration with rest periods in between. In domains withweekly competitions, stability and equilibrium should occur
over longer time periods such as a week. The extremely effortfulnature of competition, normally on the weekend, would lead toa reduced load and duration after and just before the competitions.
To obtain information about music performers' current practice patterns, we asked them to keep diaries. By collecting detailed diaries by these individuals, we could assess the duration
and regularity of different types of activities, in particular those
activities judged to constitute deliberate practice. Drawing on
earlier research on time budgeting (Juster & Stafford, 1985;
Szalai, 1972), we had individuals record at the end of the day all
extended activities with their start and end times. By recalling
already completed activities, individuals who maintain thisdiary report should minimize any biasing influence on the frequency and duration of any activity during the day. Furthermore, the instruction to recall the complete sequence of extended activities during the entire day avoids the bias of focusing on a single activity. This type of diary report is consistent
with Ericsson and Simon's (1984) criteria for valid and unbiased
verbal reports of cognitive processes. This technique is preferable to an alternative in which subjects are instructed to keep aselective diary for occurrences of specific problem behaviors,such as drinking and smoking; the keeping of such a diary
appears to reduce the frequency of these behaviors and thus
yields biased estimates (Hodgson & Miller, 1982).

THE ROLE OF DELIBERATE PRACTICE

Large-scale studies have evaluated the accuracy and convergent validity of diary reports by comparing subjects' diary estimates with estimates derived from random time sampling (Robinson, 1985). The diaries were found to underreport activities
of very short duration, such as brief social interactions andphone calls, a result that is to be expected with diaries focusing
on extended activities. More important for our purposes, thediary estimates for extended activities were found to be quiteconsistent with the results derived from more labor-intensive
methods.
Most of the research using diaries with reported temporalsequences of activities has been conducted primarily in sociological and economic studies to estimate and project the use oftime in representative national populations (Juster & Stafford,
1985; Szalai, 1972). The goal of this research has been to derive
general categories of activities that allow investigators to reliably classify any one of the reported activities into one of alimited number of categories. At the highest level, the activities
can be grouped into categories, such as sleep, work, and leisure.
In studying the daily lives of expert performers, we can draw on
this previously developed classification for general activities,
but we must supplement it with an analysis of the activities
relevant to the particular domain of expertise under investigation.
As to the third point, our framework made predictions about
the qualities of various domain-related activities, such as deliberate practice. We predicted that deliberate practice would be
rated very high on relevance for performance, high on effort,
and comparatively low on inherent enjoyment. We could evaluate ratings by expert individuals to determine the extent towhich deliberate practice is perceived to have these attributes.
The central prediction from our framework was that theadult elite performance, even among individuals with morethan 10 years of practice, is related to the amount of deliberate
practice. This prediction contradicts Galton's (1869/1979) modal view outlined earlier that eminent performance reflects primarily innate talent after sufficient practice and that, by implication, practice and elite performance are not related. However,often talent is contrasted with practice, where the best individuals are assumed to practice less than individuals with inferior
performance. Finally, plausible alternative hypotheses also suggest that the most talented individuals would practice more.
These hypotheses imply a high correlation between innate talent and practice. Because our studies were not designed to address the last possibility, we do not consider it except in the
General Discussion section.
Study 1 compared the current and past levels of practice inthree groups, elite violinists judged to have promise for careers
as international soloists and two groups of less accomplishedexpert violinists. Study 2 replicated the results of the first bycomparing expert and amateur pianists. In addition, it related
estimates of the amount of prior practice to current performance on a wide range of musical and nonmusical tasks for all
pianists.
Study 1
We assessed current and past levels of deliberate practice inthree groups of elite, adult violinists whose current perfor-

373

mance differed. First we identified the activities constituting
deliberate practice. We then determined the duration and organization of deliberate practice and contrasted them for thethree groups.

MethodSubjects
The music professors at the Music Academy of West Berlin (Hochschule der Kuenste) nominated violin students who had the potential for
careers as international soloists. Out of 14 students nominated, 3 were
not fluent in German and 1 was pregnant. The remaining 10 students
agreed to participate in the study and are called "the best violinists."
The music professors also nominated a large number of good violinists
in the same department. From these subjects, we selected 10 violinists,"the good violinists," by matching their sex and age to those of the best
violinists. Similarly, we recruited 10 students specializing in the violinfrom a different department (music education) in the academy, which
has lower admissions standards. Again, we matched these students' sex
and age to those of the violinists in the best group. We call the students
from the department of music education the "music teachers" because
teaching is the most likely future profession for this group. To obtain
additional data on the developmental history of outstanding violinists, we interviewed 10 middle-aged violinists who belong to two symphony orchestras in West Berlin with international reputations, theBerlin Philharmonic Orchestra and the Radio Symphony Orchestra(RSO). According to the professors at the music academy, the most
likely professional career for the best young violinists is to perform asa member of one of the best symphony orchestras in Germany.

Procedure
The data-collection procedures for the best and good violinists andthe music teachers were identical. The first part of the procedure forthe middle-aged violinists, from which data are reported, was the same
as for the three groups of young violinists.
Each young violinist was interviewed during three sessions. During
the first session biographical information was obtained including thestart of practice, sequence of music teachers, and participation in competitions. The subjects were then asked to estimate how many hours
per week they had practiced alone with the violin for each year since
they had started to practice.
Each subject was then given instructions about a taxonomy of activities. Ten categories of everyday activities were presented, each with ageneral label and description and a listing of frequent examples. From
extensive pilot work, 12 categories of musical activities were identified
and similarly presented. Musical and everyday activities are listed inTable 1. For those subjects playing other instruments besides the violin, the eight musical categories for playing an instrument were split
into activities involving the violin and activities involving all other
instruments. After presentation of the taxonomy, subjects were asked
to estimate how much time they spent on each type of activity during
the most recent typical week. Subjects were also asked to rate each of
the activities on three dimensions using a scale from 0-10. First they
were asked to rate the relevance of the activity to improving performance on the violin. Next they were asked to rate the effort required toperform the activity. Finally, they were asked to rate how enjoyable theactivity was without considering their evaluation of the result of theactivity. (For example, it is possible to enjoy the result of having cleaned
one's house without enjoying the activity of cleaning.)
During the second session, subjects answered questions about practice and concentration. They also recalled all activities they had engaged in during the previous day. For this recall they used a specially

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

374

Table 1
Mean Relevance, Effort, and Pleasure Ratings for 12
Music-Related and 10 Everyday Activities Collapsed
Over Three Groups of Young Expert Violinists
Activities

Relevance

EffortPleasure

9.82 H8.73 H

8.00 H
6.97 H

7.23
7.57

5.67

3.27 L

8.33 H

6.67
9.63 H
7.03
9.03 H7.67 H8.33 H7.63 H
6.50

3.93
8.60 H7.51 Ha
9.80 H8.14 Ha
4.38a
6.37 H
4.33

8.60 H
7.67
6.79a
7.28a
8.07 H8.38 H
6.07
6.40

2.90 L

4.70

1.53 L1.80 L
2.64 Lb
0.77 L1.79 Lb
4.90
8.17 H
4.52a
1.93 La
6.30
6.07

2.23 L
6.14b
2.80 L
5.56C
1.43 L0.47 L
5.45a
5.55a
3.00 L
2.67 L

3.63 L
6.43b
3.97 L
3.74 Lc
5.23
7.70
7.17a
5.07a
8.93 H
7.07

5.89

5.03

6.52

Music related
Practice (alone)
Practice (with others)
Playing for fun(alone)Playing for fun(with others)
Taking lessons
Giving lessons
Solo performanceGroup performance
Listening to music
Music theory
Professional conversation
Organization andpreparation
EverydayHousehold choresChild care
Shopping
Work (not music related)
Body care and health
Sleep
Education (not music)
Committee work
LeisureSportsGrand meanNote. N = 30, unless shown with a superscript. (Some subjects could
not make their ratings because of a lack of familiarity with the activity
in question.) The grand means over all activities and information about
the significant deviation from the grand mean is given based on post
hoc analyses using Bonferroni's method. The statistical test is conservative as the grand mean includes the ratings for the particular activity
in the respective comparison. H = significantly higher than grandbmean; L = significantly lower than grand mean. a N=29.
N=28.
C
N=27.
designed diary sheet that divided the 24-hr day into ninety-six 15-minute intervals. Use of the sheet ensured that the start and end of recalled
activities covered the entire 24-hr day. After completing the recall,subjects were asked to encode the activities using the 30 categories inthe taxonomy. Following the second session, subjects kept a diary using the provided sheets for a full 7-day week. Subjects were given envelopes addressed to the investigators and sent in their diaries after eachday. Before returning for the third and final interview session, thesubjects, working from copies of their diaries, encoded each activity
according to the taxonomy. Subjects were encouraged to identify the
primary category for each activity but they were allowed to use morethan one category to encode mixtures of activities, such as a professional discussion during lunch. At the beginning of the third interview
session, subjects were allowed to ask any questions they had about
their encoding. During the remaining part of the session the interviewer asked questions about the subjects' developmental life goals
and engaged in general debriefing.

Results
Our analyses focus on young violinists' allocation of time forrelevant preparatory activities as revealed by their diaries andretrospective estimates of practice during their development. In
preparation for this analysis, we briefly describe the biographic
data and other data relevant to systematic differences in theviolin performance of the three groups of young violinists andanalyze each group's ratings of everyday and musical activities
regarding relevance, effort, and enjoyment.
The three groups of subjects were selected such that the performance of the best violinists should be better than that of thegood violinists, whose performance in turn should be better
than that of the music teachers. In the following statistical analyses, the hypothesized differences between the three groups ofviolinists are represented by two orthogonal contrasts. The firstcontrast refers to the average difference between the best andthe good violinists. The second orthogonal contrast compares
the average of the best and good violinists (referred to as thesoloist students) to that of the music teachers. In statistical analyses that include the developmental history of middle-aged professional violinists, the data from this group are contrasted
with those of the group of the best young violinists.

Biographic Information
All three groups of young violinists consisted of 7 womenand 3 men. The middle-aged professional violinists were allmen. The ages of the young subjects were successfully matched,and no reliable differences in age were found. The mean age ofyoung violinists was 23.1 years old. The mean age of the professional violinists was 50.5 years old.
The biographic histories of the four groups of subjects withrespect to violin playing are remarkably similar and show nosystematic differences between groups. The age when they began practice was 7.9 years old and essentially coincided withthe age of starting systematic lessons, which was 8.0-years-old.
The age at which they first decided to become musicians was
14.9 years old. The average number of music teachers who hadtaught them was 4.1, and the average number of musical instruments that they had studied beyond the violin was 1.8.
The best indicator of violin performance, besides the evaluation of the music professors, is success at open competitions. A
statistical analysis of the number of successful entries in violincompetitions confirmed systematic differences in performance
among the three groups of young violinists. The frequencies forthe best and good violinists were reliably different, 2.9 vs. 0.6;
F(\, 27) = 19.35, p < .01. The average frequency of the best andgood violinists differed from that for the music teachers, 1.8 vs.
0.2; F(i, 27) = 11.78, p < .01. The same pattern of results
emerged when the proportion of successful entries from allparticipations was analyzed. The young violinists were also
asked to estimate in minutes of playing time how much music
they could perform from memory without preparation. The
best violinists reported an average of 128.9 min, which is longer
than the 79.1 min reported by the good violinists, F(l, 27) =4.07, p < .05. The average playing times for the best and good
violinists were longer than that of the music teachers, 104.0 vs.
42.27; F(l, 27) = 8.23, p < .015.
In sum, all four groups had a similar musical background,and by the age of 23 (the mean age of the young violinists), all
40 subjects had spent at least 10 years practicing the violin.

THE ROLE OF DELIBERATE PRACTICE

Ratings of Everyday and Musical Activities
In analyzing the ratings of relevance to improving violin performance, effort, and enjoyment of the everyday and musicalactivities, our primary goal was to identify a smaller set of activities rated critical to improvement of violin performance by all
young violinists. Analyses of each set of ratings for the 22 activities for the three groups of young violinists revealed no profile
differences, that is, interactions between group and ratings ofactivities, which could account for differences in their actual
allocation of time to different types of activities. We therefore
collapsed the further analyses of differences in ratings between
various activities across the three groups of young violinists.
For each type of rating (relevance, effort, and enjoyment) wecompared the mean rating across all activities with the mean
rating of that activity. The significance of differences was determined from adjusted alpha levels (a* = a/22 = 0.0023). The
mean ratings and information about significant differences are
given in Table 1.
As shown in Table 1, subjects reliably rated 7 of the 12 musicalactivities as more relevant than the overall mean. Consistent
with our theoretical assumption, 27 of the 30 violinists gave
"practice alone" the highest relevance rating. In contrast, playing alone for fun, which an observer would have difficulty discriminating from practice alone, received a much lower relevance rating. Out of the 10 everyday activities, only sleep was
rated as reliably more relevant to improving one's violin performance than the grand mean, and 5 activities were rated reliably
less relevant. Many of the activities with the highest relevance
ratings are constrained by external factors and resources. For
example, the duration of taking lessons and public performance alone and in a group cannot easily be increased at thewill of the subject. Similarly, practice in groups is to a lesser
degree constrained. After these additional criteria are applied,there remain four relevant activities of which the violinists caneasily control the duration: practice alone, music theory, listening to music, and sleep.
The ratings of effort associated with different activities showthat six of the eight activities judged to be highly relevant toperformance improvement are also judged to require reliably
more effort than the average activity. The two exceptions arelistening to music and, not surprisingly, sleep, which is judged
reliably less effortful than the average activity. The ratings ofinherent pleasure show that only two of the eight highly relevant
activities—listening to music and group performance—are
also judged to be reliably more pleasurable than the average
activity.
In sum, all three groups seem to have the same conception of
the relevance of different activities for improvement of violin
performance, and all three similarly evaluate the inherent enjoyment and effort associated with different activities. We now
turn to the analysis of the time each group allocated to different
activities and, in particular, to activities judged to be highly
relevant for improving violin performance.
Diaries
From the detailed diaries with encoded activities, the total
time a violinist spent during the week on any one of the activity

375

categories can be calculated by simple addition. Most of theencoded activities were described by a single category, such as
exclusive categories like sleep and practice; but some activities,
such as a professional discussion over dinner, were given multiple encodings. When activities were given multiple encodings,
the time of the activity was split equally among the associatedcategories.
When the duration of all music-related activities was
summed across the diary week, the average number of hours
per week was 50.6, and no reliable differences between thegroups were found. Of the eight activities judged to be highly
relevant to improvement of violin performance, only two had
an average duration across all three groups exceeding 5 hr per
week. These two activities were practice alone (19.3 hr perweek) and sleep (58.2 hr per week).
Practice alone. In agreement with our theoretical framework, violinists rated practice alone as the most important activity related to improvement of violin performance. Practicealone is a particularly interesting activity because the violinists
themselves control its duration and distribution during theweek. In contrast, most other activities judged to improve violin performance, such as public solo performance and taking
lessons, are highly constrained by external factors. We analyzed
the total duration of practice alone for the three groups andthen examined the distribution of practice alone during theweek.
During the diary week, the average duration of the violinists'
practice alone with the violin did not differ for the two bestgroups and averaged 24.3 hr of practice. This average was reliably greater than that for the music teachers who practiced 9.3
hr per week, F(l, 27) = 44.05, p < .001. As the first step inanalyzing the distribution of practice, we analyzed the daily
amount of practice as a function of the day of the week for thethree groups. No main effect or interaction of the day of theweek was observed, and only the contrast found earlier between
the two best groups and the music teachers was reliable. The
two best groups practiced alone for 3.5 hr per day and the musicteachers for 1.3 hr per day for each day of the week including theweekend. As the second step, we assessed the frequency ofpractice as a function of time of day. The frequency distributions across all weekdays shown in Figure 2 suggest a preference by the two best groups for practicing alone before lunch,whereas no corresponding pattern is observed for the musicteachers.
For statistical analyses, the percentage of time each violinist
spent practicing alone was calculated for the five 2-hr intervals
from 10:00 am to 8:00 pm for each day of the week. An analysis
of variance (ANOVA) revealed no main effects or interactions
involving the day of the week and no systematic differences
between the two best groups. The two best groups spent agreater proportion of time on practice alone than the musicteachers did, F(l, 27) = 59.11, p < .001, and this difference
interacted with the time of day, F(4,108) = 2.94, p < .05. A post
hoc analysis showed that the time music teachers practiced
alone was distributed uniformly across the day, whereas the twobest groups had elevated levels of practice between 10:00 am
and 2:00 pm. This interaction and the main effect of time ofday, F(4,108) = 6.09, p < .001, are shown in Figure 3.
Consistent with the rated effortfulness of practice alone, the376

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

time requirement for the music teachers was for the most partbalanced out by the longer duration of activities relating to
public performance by the two best groups.
Sleep. The high relevance of sleep for improving violin performance must be indirect and related to the need to recoverfrom effortful activities such as practice. Consistent with theratings, sleep is the least effortful of the activities and thus constitutes the purest form of rest. The weekly amount of sleep
during the diary week did not differ for the two best groups andaveraged 60.0 hr. This average was reliably longer than that forthe music teachers, which was 54.6 hr, F(1, 27) = 5.02, p < .05.
Hence the two best groups, who practice more, also sleep reliably longer.
An ANOVA of the amount of sleep as a function of day of theweek for the three groups showed no main effect or interaction
with day of the week. The average amount of sleep per day was
8.6 hr for the two best groups and was reliably longer than 7.8
hr of sleep for the music teachers. Large-scale diary studies
from several different countries show that adults sleep on average 8 hr per day (Converse, 1972) and that adults sleep about 1 toV- hr more on the weekend than they do during the work week
(Robinson, Converse, & Szalai, 1972). Laboratory studies showthat the amount of sleep differs as a function of age (Roffwarg,
Muzio, & Dement, 1966). A recent study by Robinson,
Andreyenkov, and Patrushev (1988) shows that adults between
18 and 29 years of age sleep around 7.7-7.9 hr per day, a findingthat is remarkably consistent with our estimate for the musicteachers. The distribution of the frequency of sleeping as afunction of the time of the day is shown in Figure 4 for the threegroups.
The two best groups appear to sleep more during the afternoon. The duration of sleep episodes separated from nighttime
sleep by at least 1 hr from 9:00 am to 9:00 pm was not reliably
different for the two best groups and averaged 2.8 hr per week.
This average differed reliably from that of the music teachers,
F(l, 27) = 5.92, p < .05, who napped only 0.9 hr per week. The
two best groups did not take longer naps to compensate for
deficits in nighttime sleep because, when napping was subtracted from the total sleep time, the mean for the two best
duration of sustained practice is limited. Most interestingly, theduration of practice sessions is very similar to other estimates of
optimal practice duration reviewed in this article. The mean
duration of practice sessions during the diary week did not
differ during that week and averaged 80 min with no reliable
differences among groups. Hence, the differences in amount ofpractice reflected differences in the number of practice sessions. The two best groups did not differ reliably and had an
average of 19.5 sessions per week, a number that was reliably
more than the average of 7.1 sessions per week for the musicteachers, F(l, 27) = 22.40, p < .001.
The differences in practice alone between the two bestgroups and the music teachers might be due to very different
curricula in the two departments at the Academy. However, acareful comparison revealed only minor differences between
the two departments' training requirements in music. The music teachers had additional requirements consisting of pedagogical aspects of music education, but these requirements corresponded to less than 5 hr during the diary week. This increased

THE ROLE OF DELIBERATE PRACTICE

377

groups was higher than that of the music teachers, although thedifference was no longer reliable.
An analysis of napping as a function of day of the week forthe three groups showed no main effect of weekday, but did
show a significant interaction between day of the week and thecontrast between the two best groups and the music teachers,
F(6,162) = 2.22, p < .05, which is illustrated in Figure 5.
The overall pattern in Figure 5 suggests that the amount ofnapping is uniformly low for the music teachers, whereas theamount of napping for the best and good violinists is elevated at
the beginning of the work week and reaches its lowest levels
during the weekend. Further analysis revealed that the primarysource of the interaction reflects differences between the weekend and the five weekdays. An ANOVA of the amount of napping for the three groups revealed a reliable difference between
the weekend and the work week, F(l,27)=4.29,p< .05, and aninteraction with the difference between the best and good violinists and the music teachers, F(l, 27) = 12.06, p < .005. Given
our general argument for recovery from practice through rest
and the result that levels of napping decreased over weekends
whereas the amount of practice did not, we looked for alternative sources of rest that could moderate the amount of napping
required over the weekend. Of the other activities rated high on
restfulness, that is, rated low on effortfulness, leisure has thelongest weekly duration during the diary week, with 28.2 hr per
week. Thus, we now consider the role of leisure activity in providing recovery from practice.
Leisure. We performed an ANOVA of the daily amount ofleisure activities as a function of the day of the week for thethree groups. The best violinists spent 3.5 hr per day on leisure,which is reliably less than the 4.7 hr for the good violinists, F(\,27) = 4.27, p < .05. The average for the best and good violinists
was 4.1 hr of leisure per day, which is not reliably different fromthe mean for the music teachers (4.0 hr). In comparison, other
adults aged 18-29 are estimated to spend around 5.2 hr a day on
leisure activities—defined as Robinson et al.'s (1988) estimateof free time with sports and education excluded. An ANOYA of
the leisure time as a function of the day of the week for the threegroups of violinists revealed no reliable interactions, but a reliable main effect of weekday was observed, F(6,162) = 5.59, p <.001, and is shown in Figure 6.
A post hoc analysis using Bonferroni's t tests showed that outof the 21 possible paired comparisons, only 9 reached significance. All 9 involved comparing a weekday to either Saturdayor Sunday, a finding that implies that leisure time is reliably
elevated during the weekend. This pattern is consistent withthe hypothesis that activities other than sleep can provide necessary rest. The finding that the best violinists spend less time forleisure is important because leisure is judged to be the mostenjoyable of all activities, as reflected by the ratings of inherent
pleasure in Table 1. For all young violinists there is a reliable
negative correlation between amount of leisure time andamount of time on music-related activities, r(28) = —0.37, p<.O5.
Estimates of Weekly Duration of Various Activities
It is possible that some of the results found with the time-consuming method of collecting and analyzing diaries could have

378

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

been obtained with more efficient methods. In this section weanalyze the time these students estimated spending on the different activities during a current week as well as their retrospective estimates for the time they practiced alone earlier in theircareer. We first consider the estimates for a current typicalweek, which the violinists made prior to the diary week. Estimates for practice alone are reported, then the estimates forsleep and leisure.
Our analysis of the diaries showed that the violinists maintained practice alone with the violin at a stable level across theentire week. We therefore expected that they could accurately
estimate the amount of weekly practice on the basis of their
daily practice. An ANOVA of the estimated weekly amount ofpractice revealed no reliable differences between the two bestgroups of violinists, who estimated 29.8 hr of practice alone.
The two best groups were found to estimate a reliably greater
amount of practice than the music teachers did, 29.8 vs. 13.4;
F{\, 27) = 38.68, p < .001. A repeated-measures ANOVA, including the estimates for the current week and the diary data,
revealed that the estimates for the current week were reliably
higher by 5.2 hr than the amount assessed from the diaries, F(l,27) = 15.39, p < .001, and that this overestimate did not differ
across the three groups. The two measures of practice alone
were highly correlated for all young violinists, r(28) = 0.74,/?<.001.
A closer analysis revealed that 85% of the best two groups
and 50% of the music teachers expressed their estimated weekly
amount of practice during the typical week as a daily amount
multiplied by 7 days or as an integer value that was an exact
multiple of seven. Debriefing interviews suggested that the estimates for a typical week reflected a level of daily practice towhich the violinists aspired rather than the level they actuallyattained. Hence estimates of weekly practice appear to be valid, albeit biased, indicators of actual practice, and the bias
does not differ among the three groups.
The estimates of sleep during a typical week revealed nodifferences between the best and good violinists, but a reliably

higher average for the best and good than the mean for themusic teachers, F(1, 27) = 5.42, p < .05. A repeated-measures
ANOVA for estimated sleep and sleep assessed by the diary
revealed no differences between the best and the good violinists, but a reliable main effect for the contrast between the best
and good violinists and the music teachers, F(\, 27) = 7.21, p <.05. The estimates indicated 3.5 hr of sleep less per week thanthe diary measure, F(l, 27) = 10.19, p < .005, and there were no
reliable interactions with the group contrasts. The correlation
between estimated sleep and sleep assessed through the diaries
was reliable, r(28) = 0.49, p < .01. Most of the violinists (83%)
estimated their weekly sleep as a multiple of seven.
The estimated amount of leisure revealed a different patternof results than that assessed from the diaries. An ANOVA uncovered no differences between the best and the good violinists, but reliably lower estimates for the music teachers than the
average for the best and good violinists, F(\, 27) = 5.25, p < .05.
A repeated-measures ANOVA for the estimated amount of leisure and the amounts derived from the diaries found no reliable
main differences between groups. The estimated amount ofleisure was 7.4 hr lower than that derived from the diaries, F(l,27) = 13.46, p < .001, and the interaction of the difference
between the best vs. the good violinists was reliable, F(l, 27) =6.66, p < .05. The estimated amounts of leisure and theamounts of leisure assessed from the diaries are shown for all
three groups in Figure 7.
The best violinists, who spent the least amount of time on
leisure, made estimates closely matching the amounts measured for the diary week. The estimates of the other two groups
are much lower than the leisure time measured for the diary
week. Not surprisingly, the correlation between estimates anddiary assessments was low, r(28) = .082, p > .05. Only half of thesubjects estimated the weekly leisure time as a multiple ofseven.
In sum, the violinists could give reasonably accurate estimates of the weekly duration of stable, habitual activities, suchas sleep and amount of practice alone. All subjects, except thoseTHE ROLE OF DELIBERATE PRACTICEin the best group, were very inaccurate in their estimates of
spontaneous activities such as leisure time.
Retrospective Estimates of Practice During MusicalDevelopment
Our findings on practice alone imply that subjects should be
able to accurately report not just their current level of practice,
but past levels of practice as well. Practice alone is viewed as themost important activity for improvement of violin performance, and its daily amount is remarkably stable. The effortfulnature of practice suggests that subjects monitor its duration
carefully and hence should be able to estimate it even after longretention intervals. Our earlier analyses showed that concurrent
estimates of weekly duration of practice alone are highly correlated with the durations recorded in the diaries. These retrospective estimates are likely to have a larger error component,
but they should not be systematically biased. The one caveat isthat subjects might report the level of practice to which they
aspired rather than the actual amount. However, the correlation between aspired and actual amounts appears to be quite
high for all three groups of young violinists. In addition, thewidely held view that very talented musicians need to practiceless than other musicians would yield a bias in the opposite
direction of what the skill-acquisition framework predicts;
namely, the best or "most talented" violinists would be inclined
to underestimate their past amount of practice to support theirbeliefs that they are very talented.
At the end of the extended biographical interview, all of our
subjects estimated the average number of hours of practicealone with the violin per week for each year since they had
started playing the violin. Figure 8 illustrates that for all fourgroups the reported amount of practice increases monotonically from the start of practice until the age of 20.
The theoretically most interesting index of amount of practice is the total amount of practice accumulated at a given age.
The weekly estimates of practice alone can easily be converted
to estimated yearly amounts by multiplication of the number ofweeks in a year. The number of hours of practice accumulated379

by a violinist at a given age can be easily calculated by adding
the yearly estimates at and below that age. The average numberof hours of accumulated practice for each of the four groups isshown in Figure 9 as a function of age.
To avoid any confounding influences from the activities at
the music academy, we statistically analyzed the amount ofpractice the young violinists had accumulated by age 18. At thisage, the best young violinists had accumulated an average of
7,410 hr of practice, which is reliably different from 5,301 hr,
the average number of hours accumulated by the good violinists, F(l, 27) = 4.59, p < .05. The average of the best two groups
was reliably different from that of the music teachers, who had
accumulated 3,420 hr of practice by age 18, F(l, 27) = 11.86, p <.01. Hence, there is complete correspondence between the skill
level of the groups and their average accumulation of practicetime alone with the violin.

380

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

A further test of the relation between performance and practice is provided from the amount of practice accumulated by
the professional middle-aged violinists at age 18. The averagefor middle-aged violinists is 7,336 hr, which is so close to theaverage of 7,410 hr for the best young violinists, that the difference is not statistically significant. Presumably the middleaged violinists were selected by international-level orchestras
because they had the same skill level in early adulthood as thebest young violinists currently have. The high degree of correspondence between these two groups' retrospective estimatesof practice alone during their music development thus supports
the validity of these estimates.

Summary of Results of Study 1
Confirming our theoretical framework, the violinists in allgroups rated practice alone as the most relevant activity for
improving violin performance. Among all the activities rated
highly relevant, practice alone is unique: A violinist can extend
its duration at will because no external resources, such as availability of teachers or audiences, are involved. An analysis of theweek-long diaries showed that the two best groups of young
violinists did not differ from each other in their amount ofpractice alone with the violin, but they practiced almost threetimes longer than the music teachers. The violinists were able
to estimate their weekly practice, and their estimates werehighly correlated with the calculated durations from the diary
week. From retrospective estimates of weekly practice during
their musical development, the amount of accumulated estimated practice alone by age 18 was calculated. The accumulated amount of practice for the best young violinists was indistinguishable from that of professional middle-aged violinists
belonging to international-level orchestras. This finding was
expected because the most likely professional career for thebest violinists is membership in a first-rate orchestra. The good
violinists had accumulated fewer hours of practice alone by age
18, but reliably more than the music teachers had.
Beyond the internal consistency of the retrospective estimates of practice alone, it is possible to compare the weekly
estimates from our study to concurrent estimates of amounts ofpractice by young award-winning musicians from two German
studies (Kaminski et al., 1984; Ruoff, 1981). These musicians
are biographically similar to the violinists in our best groupand were assessed with a diary procedure at two different ages.
At age 13 the award-winning musicians practiced 13.7 hr per
week (Ruoff, 1981), an amount close to the 12.2 hr estimated byour best group and higher than the 8.8 and 6.2 hr per week
estimated by the good and music teacher groups, respectively.
At age 17, the practice of the award-winning musicians averaged
15.5 hr per week (Kaminski et al., 1984) compared with the
19.2,16.8, and 9.1 hr per week estimated by the best, good, andmusic teacher groups. The agreement between the estimates ofour best violinists and the award-winning violinists' diary data
is reasonably close and is consistent with the hypothesis that thebest violinists practice more than the good violinists during
early adolescence and more than the music teachers during
their entire developmental period. In a recent study Sloboda
and Howe (1991) interviewed more than 40 students (aged 1018) in a music school, where about half of the students weresuperior to school standards. They found no reliable differencein the estimated amount of daily practice between their twogroups of superior and average musicians. The difference between the results and our own can be explained by the more
select samples of musicians studied by us and Kaminski et al.
(1984). Consistent with this interpretation, the estimatedamount of daily practice for their subjects was only half that ofour subjects' estimates for the comparable age period. Furthermore, only a fraction (14%) of Sloboda and Howe's (1991) subjects were totally self-motivated to practice, which raises someissues as to whether the practice of most of their subjects meetsthe criteria for deliberate practice.
Consistent with our theoretical framework, the violinists
rated practice alone as requiring effort. The analysis of the diaries revealed that uninterrupted sessions of practice alone werelimited to a duration between 1 and 1.5 hr, a finding that is
consistent with extended laboratory studies on practice. For thetwo best groups practice was systematically distributed during
the day and was particularly high in the late morning. Twofindings provide intriguing evidence of the effortful characterof practice. First, violinists rated sleep as highly relevant for
improvement of violin performance. Second, the analysis indicated that the violinists napped to recover from practice. The
two best groups of violinists with the highest levels of practicewere found to nap more in the afternoon than did the group ofmusic teachers. Furthermore, the duration of napping decreased during the weekend, when ample time for relaxing activities such as leisure was available. Another study provides similar findings. World-class musicians interviewed by Samuel(1987) rated practice as extremely important, especially during
development. A majority of these subjects (65%) judged sleep asimportant, and many musicians reported taking afternoon
naps, especially before a public performance.
The diary-based analyses of the amount and distribution ofpractice showed clear differences between the music teachers
and the two best groups, but no difference between the twobest groups. The two more accomplished groups differed in theaccumulated amount of estimated practice, and the best groupspent less time on leisure than the good group did during thediary week. Most interestingly, the subjects in the best groupwere able to estimate quite accurately the time they allocated toleisure, whereas the good violinists underestimated their leisure time during the diary week by more than 11 hr. With ourfinding that, compared with the good violinists, the best violinists tended to spend more time on music-related activities,
these results suggest that our most accomplished subjects show
a greater involvement in music and organize their time better,
especially their leisure time.
It is important to note that our study shows only that theamount and distribution of practice is related to the level of
performance of adult musicians. In fact, many additional factors consistent with the skill-acquisition framework could attenuate the differences among our three groups. Sosniak (1985)
found that international-level pianists had spent considerable
efforts to seek out the very best musical teachers during theirmusical development. Furthermore, it is likely that an analysisof the detailed activities during practice alone would reveal
qualitative differences between violinists at different advanced
levels of performance (Gruson, 1988; Miklaszewski, 1989).

THE ROLE OF DELIBERATE PRACTICE

Study 2The purpose of the second study was to extend the findings
from the violinists to another domain of expertise and, mostimportant, to obtain experimental measures of performance inskill-related tasks that could then be related to measures ofcurrent and accumulated practice. To determine whether theprevious findings could be replicated for subjects with more
extreme differences in proficiency than the violinists had, we
compared a group of young expert pianists with a group ofamateur pianists. The data reported in this study are from alarger investigation including two more groups, one of elderly
professional pianists and another group of elderly amateur
pianists. Recent research on expert piano performance(McKenzie, Nelson-Schultz, & Wills, 1983; Palmer, 1989;
Shaffer, 1981; Sloboda, 1983) has shown that it is possible torecord the sequence of piano keystrokes and analyze motor
skills differentiating pianists at different levels of performance.
In his dissertation Krampe (1991) designed a battery of tasks
ranging from nonmusical tasks, such as choice reaction time, to
actual performances of a musical piece to study four groups ofexpert vs. amateur and younger vs. older pianists. Unfortunately, we could not find a large group of young pianists who
met the selection criteria used for the best violinists in Study 1.
Instead, we recruited a sample of expert pianists from the Music Academy of Berlin according to selection criteria similar to
the good violinists in Study 1. The amateur pianists werematched for sex and equated for mean age with the expert pianists.
As with Study 1 we first provide biographical data, then thereport of the 1-week diary and retrospective estimates of pastpractice. We report on the battery of nonmusical and musicaltasks and finally relate the performance on the musical tasks toour estimates of accumulated practice. Our main prediction
was that we would be able to predict differences in proficiency
in the skill-related tasks at least as well from our measures ofaccumulated practice as from the differences in the pianists'
level of expertise.

MethodSubjects
Twelve expert pianists (8 men and 4 women) and 12 amateurs (7 men
and 5 women) equated for mean age (24.3 years) participated in the
study. The expert pianists were students in advanced soloist classes atthe "Hochschule der Kuenste," a Berlin music academy. All expert
pianists were students but had already started to perform in publicconcerts. Fifteen amateurs recruited through newspaper and campus
ads were students in academic or vocational training programs. To
make the amateurs comparable to the experts, we specified that theamateurs had to play classical music and be able to successfully play apiece by Bach used in the musical performance task. Three amateurs
failed this criterion. The estimates of practice alone during early development were also collected from two age-matched samples of 12 older
experts and 12 amateur pianists with the average age of 59.8 years.

Apparatus
An electronic keyboard (Yamaha CB-300 Clavinova) and a MacII
computer were used for monitoring experiments and collecting data381

for all tasks except for the digit-symbol substitution test. That test wasadministered in the paper-and-pencil version.

Procedure
Data were collected during two sessions separated by 7-12 days.
During the first session subjects participated in an abbreviated versionof the interview in Study 1. They provided detailed biographical information and estimated the average amount they had practiced alone
every week for each year of their lives since they started practicing.
Then followed the first experiment, the complex movement coordination task, which challenged the speed and accuracy of subjects' bimanual movement coordination. The task was to play a series of nine keystrokes either with one hand or simultaneously with both hands. Eachfinger was assigned to one of five adjacent, white keys on the piano; nolateral movements were required. We manipulated the complexity ofhand coordination by having subjects perform either with single hands(left or right), mirror image movements for both hands, or different
movements for opposite hands. The tasks were presented as strings ofnine numbers, each number indicating which finger of a given hand
was to be used in performance. A display with the relevant task information appeared on the computer screen and remained for subjects'
inspection during performance. Motor demands were identical acrosstasks: the same series were used for the left and right hands; bimanualtasks were generated by combining the single-hand tasks. Conditions
were tested in ascending order of complexity. Instructions encouraged
the subjects to play accurately and rapidly while maintaining a steady
tempo. The single-hand condition consisted of two series of keystrokes
for each hand; the two bimanual conditions involved playing two different series each. In addition to warm-up, each task consisted of an
initial block of 6 and a second block of 12 practice trials. During thesecond block of practice trials, subjects received graphic feedback on
accuracy, speed, and the timing of single keystrokes (steadiness). Only
the data from the third block of 6 trials were used in the analysis.
Following the first experiment toward the end of Session 1, subjects
were introduced to the diary procedure. The introduction, recordingof daily activities during a 7-day period between Sessions 1 and 2, andcoding of activities were identical to the procedures described forStudy 1. Session 2 started with the debriefing for the diary procedure.
The musical performance task, following debriefing for the diary procedure in Session 2, required subjects to give three successive performancesof the Prelude No. 1 in C-major ("Wohltemperiertes Klavier")
by J. S. Bach. Subjects were given up to 15 min of practice to work out
an interpretation and then attempted to replicate this interpretation
three times while being as consistent as possible across performances.
Musicians consider the piece to be technically very simple; at the sametime it leaves room for musical interpretation. All subjects were able toperform the piece fluently except for the two amateurs, who were notincluded in the analyses for this reason. Force and onset-offset times
for single keystrokes were recorded with the apparatus described previously; high-speed tape recordings were also generated for later evaluation. Following the musical performance task, subjects completed apaper-and-pencil version of the Digit-Symbol Substitution Test (DS), a
subtest of the WAIS that is considered a measure of general perceptuomotor speed. A two-choice reaction time task (CRT) required speeded
responses of pressing either one of two assigned keys on the piano
keyboard. Both tasks are often used to measure cognitive-motor
speed. Three finger tapping tasks involving their right, left, and alternate forefingers, respectively, were used as measures of simple motor
efficiency. Following an auditory start signal subjects had to tap as fast
as they could for 15 s. Tasks were terminated by an auditory signal.

Results
Biographic BackgroundAll experts had more than 14 years of playing experience;amateurs had between 5 and 20 years of experience. Amateurs

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K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

had started with piano instruction at an average age of 9.9 years
and were reliably older than expert pianists, who started at 5.8
years of age, F(l, 22) = 7.00, p < .02. On average experts hadreceived 19.1 years of formal instruction from 4.7 teachers. In
comparison, the amateurs had received 9.9 years of instruction
and had studied with 3 different teachers on average. The differences in years of formal instruction, F(\, 22) = 29.36, p <.001, and number of teachers, F(l, 22) = 10.00, p < .01, weresignificant. All of the expert subjects and 50% of the amateur
subjects were receiving formal instruction at the time of investigation. All but one expert subject had participated in open
competitions (M = 3.6, SE = .73); only two amateur subjects
had ever participated in a competition at a local level. Whereas
amateur subjects were more likely to play at least one additional
instrument (M = 1.25, SE = .22), this was the exception forexpert pianists (M = .25, SE =.18); this difference was reliable,
F(\, 22) = 12.57, p < .01, and illustrates the experts' focus on
improvement on their main instrument.
Diaries
The experts spent a total of 56.75 hr on music-related activities during the diary week. In comparison, the amateurs spent
only 7.02 hr, F{\, 22) = 348, p < .001. As in Study 1, we analyzed
the amount and distribution of practice alone, the most relevant activity for improvement in the skill, and also examineddata on sleep and leisure time.
Practice alone. During diary week, the experts spent 26.71
hr in solo practice at the piano; the amateurs spent 1.88 hr. Thisdifference was, of course, significant, F(l, 22) = 93.98, p < .001.
An analysis of the amount of practice as a function of weekday
had to be limited to the experts because the amateurs did notpractice at all on most days. No reliable difference between
weekdays was found. Figure 10 shows the distribution of practice activities across the time of the day averaged across weekdays.
To analyze the distribution of practice across time of the day,we computed the amount of practice during five intervals as
described in Study 1. This analysis was also restricted to thedata on the expert pianists. It revealed no interaction between

weekday and interval and no main effect for weekday. The effect of interval did not reach significance, F(4, 44) = 2.57, p <.052. An analysis of the length of practice sessions showed thatthe experts practiced longer (87.90 min) than the amateurs(46.00 min), F(l, 20) = 15.25, p < .001. These average durations
are probably overestimates as shorter breaks (< 15 min) between
consecutive sessions were probably not recorded in the diaries.
Sleep. The weekly amount of sleep did not differ for theexperts and the amateurs and averaged 56.86 hr per week. A
repeated measures ANOVA revealed a main effect of weekday,
F(6, 132) = 4.01, p < .002, which did not interact with skill
level. To locate the effect, we performed pairwise t tests contrasting the mean of each day with the means of other days. Six
out of 42 possible comparisons were significant, all involving
contrasts between a working day and either Saturday or Sunday.
These results indicate that both groups of pianists tended tosleep longer during the weekend (M= 8.68 hr) than during theworking week (M= 7.91 hr). The average duration of napping
was only 0.63 hr per week and did not reliably differ between
the two groups.
Leisure. A repeated measures ANOVA was performed on
the amount of leisure time for each day during the diary week.
The amount of leisure time, 4.66 hr per day, did not differ forexperts and amateurs. As in Study 1, however, we obtained asignificant effect of weekday, F(6,132) = 11.04, p < .001. Elevenout of 21 post hoc comparisons were significant, and 8 of these
involved contrasting a working day with a weekend day. Subjects considerably increased their leisure time during the weekend days (M = 6.22 hr) compared with the working week (M =4.05 hr).

Retrospective Estimates of Practice During MusicalDevelopment
To determine how good our subjects were at estimating how
long they practiced each week we compared the measures obtained from the diaries with the estimate for the current year. A
repeated measures ANOVA with type of assessment as a withinsubjects factor yielded a main effect of type of assessment, F(l,22) = 4.81, p < .05, and a main effect of skill level, F(l, 22) =350, p < .001, but no interaction. Both experts and amateurs
overestimated their amount of practice during the diary week
by an average of 5.2 hr, in agreement with the results of Study 1.
Figure 11 shows the average amount of weekly practice as
estimated by amateur and expert subjects as a function of age
until age 20, the age of the youngest subject. Although expert
subjects show the same linear increase in the amount of practice that was found for the violinists, there is little change inamateurs' training level after the mean starting age (9.9 years).
Following the procedure in Study 1, we calculated the averageamount of practice accumulated by a given age for each group(see Figure 12). At the age of 18 the expert pianists had accumulated 7,606 hr of practice, which is reliably different from the
1,606 hr of practice accumulated by the amateurs, F(\, 22) =26.29, p < .001. The estimated amount of practice accumulatedby age 18 for the group of older expert pianists did not differ
from that of the younger experts, F(l, 22) = 1.74, p > .20. Similarly, the accumulated amount of practice for the older ama-

THE ROLE OF DELIBERATE PRACTICE

383

puter recordings of keystrokes. The average force pianists applied to the 16 keystrokes in each bar was computed, and three
Pearson correlation coefficients corresponding to the similarity between the three successive performances were calculated.
The average Pearson r was .695 for the amateurs and .866 for theexpert pianists. Single correlation coefficients were z transformed and submitted to a repeated measures ANOVA. The
analysis yielded a main effect of skill level, F(l, 22) = 11.95, p <.01, indicating that experts were more consistent in expressing
dynamic changes in terms of loudness than amateurs. This
main effect was not dependent on which two of the three performances were compared.
Performance in Skill-Related Tasks

teurs did not reliably differ from that of the younger amateurs,F(l,22)=.83,p>.35.
Performance on Tasks Unrelated to Music
Performance in the two nonmusic tasks, the DS and the CRT
tasks, did not distinguish between experts and amateurs. Only
three subjects made errors on the DS. The mean digit-symbolscore was 69.0 and did not differ for the two groups, F(l, 22) =1.18, p> .25.' The mean error rate in the CRT was 4.2% with nodifferences between groups. The mean reaction time was 422
ms; again, differences between groups were not significant,F(\, 22) = 1.09, p > .30. These results confirm the assumptionthat domain-specific mechanisms, rather than more general
cognitive-motor abilities, are responsible for experts' superior
performance. The findings are in line with earlier proposals by
Lashley (1951) and Shaffer (1982), who suggested that integrated complex representations ratherthan rapid serial processing govern speed and fluency in a complex motor skill.
Music Performance: Validation of Differences in Piano
Performance
Two measures were derived from the musical performancetask: expert ratings on the musical quality of the interpretationand the consistency of dynamic changes applied across thethree successive performances of the piece. Three expert raters
evaluated tape recordings of the second interpretation separately for each subject. The evaluation consisted of seven scales
ranging from 0 to 10. The reliability of the rating instrument
was very high (Cronbach's alpha = .94 for both groups; a = .94
for amateurs, a = .79 for experts, on the basis of all 21 items).
Ratings were collapsed across scales and averaged for the threeraters. The average rating for expert pianists' performance was
6.4 (SE = .21) compared with 4.7 (SE = .42) for the amateur
group. The expert raters' overall evaluation of musical performance was reliably higher for the expert pianists, F(l, 22) =12.74, p<.01.
Thirty-two bars were used for statistical analyses of com-

Tests of homogeneity of variances revealed that the meanlatencies between successive keystrokes (interstroke latencies)
were not normally distributed within skill groups. We therefore
analyzed the interstroke latencies for the simple tapping tasks
and the three conditions of the complex movement coordination experiment by log-transforming the latencies at the level ofsingle intervals.2
Simple tapping tasks. Interstroke intervals from the threetapping tasks were analyzed with a repeated measures ANOVA
with two orthogonal contrasts comparing left vs. right forefinger tapping and single vs. alternate finger tapping. Both withinsubjects contrasts were significant, indicating that right-index
tapping was faster than left-index finger tapping, F(l, 22) =21.63, p < .001, and alternate tapping was faster than single
forefinger tapping, F(l, 22) = 476, p < .001. The second contrast showed a reliable interaction with skill level, F(l, 22) =8.19, p < .01, indicating that expert pianists' increase in speed
when the task allowed overlapping of movements between alternate fingers was proportionally larger than for the amateurs
as shown in Figure 13. The overall effect of skill level was reliable, F(\, 22) = 26.63, p < .001; experts were faster on each ofthese tasks than amateurs.
Complex movement coordination tasks. Performance on
single hand tasks was averaged for left and right hands, and themean log-interstroke latencies were calculated for the last blockof six criterion trials on each condition. A repeated measures
ANOVA was performed, contrasting single-hand performance
1

There are no available German norms for this specific version of
the digit-symbol substitution test. Two recent studies at the Max
Planck Institute for Human Development and Education in Berlin
show that the mean performance of groups of subjects with compara
ble age and educational background range between 59 and 66. Hence,the performance of the two groups of expert and amateur pianists iscomparable although somewhat higher.
2
After log transformation the data approached a normal distribu
tion, where the mean and median coincide. The common procedure ofanalyzing the median of observed latencies will hence give similar
results but entails somewhat less statistical power. An analysis basedon medians gave the exact same results as those reported below with
one exception. Namely, interaction between skill level and alternate
finger tapping was not reliable. The correlation between the medians
and the averages of the log-transformed latencies ranged from .94 to .99
with an average of .98.

384

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

with the two bimanual tasks and comparing the two bimanual
conditions, namely, mirror-image movements and different
movements in opposite hands. Both contrasts were significant
indicating that the complexity manipulation acted as predicted: Single-hand movements were faster than the average ofthe two bimanual tasks, F(\, 22) = 92.34, p < .001, and different movements in opposite hands were slower compared tomirror-image movements in both hands, F(l, 22) = 53.39, p <.001. The second contrast showed a reliable interaction withskill level, F(l, 22) = 5.91, p < .05. This indicates that thecomplexity of bimanual coordination impaired the amateurs'
performance more than the experts' performance. The main

effect of skill level was significant, F(l, 22) = 65.98, p < .001.
The main effect and the interaction are illustrated in Figure 14.
Relation Between Accumulated Practice andPerformance in Skill-Related Tasks
One premise of our theoretical framework is that performance increases monotonically according to the power law(J. R. Anderson, 1982; Newell & Rosenbloom, 1981). Accumulated practice was thus log-transformed prior to analyses. A
hierarchical regression approach was used on all measures of
performance in skill-related tasks. The skill-level factor was

385

THE ROLE OF DELIBERATE PRACTICE

entered first. Then accumulated practice (log values) was entered as a second step so that we could determine whether thisvariable could predict within-group interindividual variationthat the skill factor could not capture. As a third step, the skill
level factor was removed from the regression equation so that
we could determine the degree to which accumulated practicealone could account for task performance. Table 2 gives the R2(amount of variance explained) associated with the successive
implementation of the three regression models and the significance levels for the relevant F tests.
The table illustrates two major findings. First, expert pianists had a clear advantage in all measures of skill-related performance; all R2s in the first row are significant. Second, accumulated practice could account for the skill difference as well as
the skill factor could; there was no significant reduction invariance explained when skill level was removed from theequation for any of the variables (3rd row). Furthermore, accu-

mulated practice accounted for additional variance withingroups for the complex movement coordination tasks when
added to the skill-level factor. Inspection of the beta weights
revealed that the relation was in the predicted direction: Thosesubjects who had practiced more did better in the experimentseven when skill level was statistically controlled for. Figure 15
illustrates the relation between accumulated amounts of practice and performance for the three conditions of the complex
movement coordination experiment.
To determine whether the additional variance accounted forby accumulated practice was merely reflecting differences incurrent practice intensity, we performed a separate set of control analyses. Current amount of practice (the number of hours
practiced during the diary week) was entered prior to accumulated practice into the regression equations for each variable
listed in Table 2. The emerging pattern of results was as reported before. This analysis shows that the effects of accumu-

Table 2
Performance in Skill-Related Tasks as Accounted for by Skill Level and Accumulated Amountsof Practice in Study 2 (R2s and Significance ofF Change)
Complex movement coordination
Simple tapping
Skill level only
R2 added withaccumulated
practice
R2 removed withskill level
Accumulated
practice only

.43***

Alternate.47***

Single-handmovements.74***

Mirror-image
movements.67***

Different
movements.66***

.02

.02

.06

.05*

.09**

08*

.04

.03

.01

.04

.01

.01

.53***.42***.52***.75***.75***.73***

Right.55***

Left*p<.05. **p <.01. ***p <.001.

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K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

2.4

lated practice remain predictive of current performance even
if the impact of current level of training is statistically controlled for.
Another question in this context was whether general motor
ability would predict interindividual differences in task performance once the effects of past practice were partialed out as
implied by Keele and Hawkins (1982). To test this claim, weentered each of the simple tapping measures to the regression
equations for the three complex tasks as predicted by accumulated practice. In no case did any of the three variables add
significant variance to the model. This analysis shows that theinterindividual differences in performance in simple motor
tasks do not predict performance differences in similar but
inherently more complex tasks once the effects of prior practice
are accounted for.

Summary of Results of Study 2
Consistent with our predictions, we found large differencesin the histories of deliberate practice for expert pianists andamateurs. At no point during development did the two groups
accumulate comparable amounts of practice, or, as we would
infer, attain comparable levels of performance. The expert
pianists started on the average 4 years earlier than the amateurs. Their average amount of practice increased each year
until it attained its current high level, whereas the amateurs
maintained their early levels until adulthood. The current
amount of practice assessed from the diaries is more than 10times higher for the experts than for the amateurs. Even the
average length of their practice sessions differed. During thediary week experts were fully engaged in music and spent close
to 60 hr on music-related activities. Their practice was evenly
distributed across the entire week, and the length of practicesessions was limited, in accord with our theoretical expectations. We found no differences in the weekly allocation of restful activities, such as sleep and leisure, between the expert pian-ists and the amateurs, who also were students in domains otherthan music. For both groups the amount of sleep and leisureincreased during the weekend, the pattern normally seen instudies of samples of the general population (Robinson et al.,1972). It is difficult to assess the influence of the musical instrument on the differences between the expert pianists andthe two best groups of expert violinists. In the next section we
discuss differences in starting ages between the two groups.
However, in most important respects the pattern of results isremarkably consistent for the expert pianists and violinists.
We initially proposed three levels of investigation to decompose the complex skill of playing the piano: efficiency of peripheral motor functions, coordination of complex bimanual movements, and the ability to consistently vary movement parameters in expressive musical performance. Findings from all
experimental tasks designed to test these components were inline with our predictions: The data revealed considerable differences between experts and amateurs. The differences between skill groups increased with the hypothesized level of taskcomplexity in the simple finger tapping tasks as well as in the
more complex movement coordination tasks. Clearly experts
can overcome the processing constraints in the more difficult
task conditions. These constraints seem to arise mostly fromrequirements for bimanual coordination and have been documented for untrained subjects in earlier studies (Kelso, Southard, & Goodman, 1979; Klapp, 1979). Shaffer (1981) demonstrated that expert pianists show superior abilities for independent timing of movements in opposite hands. Our results arealso in line with findings for a skill that in several ways is related to playing the piano, namely typing. A recurrent finding
has been that expert typists' speed advantage is most pronounced for rapidly alternating keystrokes between hands(Gentner, 1988; Salthouse, 1984; Shaffer, 1976), whereas the differences for repetitive movements of the same finger are normally the smallest.
The skill advantage in our study was limited to those tasks

THE ROLE OF DELIBERATE PRACTICE

387

that presumably reflect components of skilled performance; noskill differences were apparent in the two far transfer tasks.
Interindividual differences in skill-related tasks could be predicted from accumulated amounts of practice, as predicted,
even when current levels of training were statistically controlled for. Predictions that were based on the power law modelof practice were as good as those based on the skill level factor;
predictability was even reliably better for the complex movement coordination tasks that were designed to maximize performance differences supposedly underlying the skill.
Although our study does not directly disconfirm the assertions that general cognitive-motor abilities account for performance in a complex skill (e.g., Keele & Hawkins, 1982), it ishard to see how our findings could be reconciled with thoseaccounts. The absence of skill effects in the two far transfer
tasks is not in line with these explanations. Furthermore, theregression analyses reported here support the notion that skills(even simple tapping skills) are gradually acquired rather thaninherited as stable cognitive-motor dispositions.
The Framework Applied to Several Domains ofExpertise
The central thesis of our framework is that expert performance is the result of an extended process of skill acquisition
mediated by large, but not excessive daily amounts of deliberate
practice. In the domain of music, we showed that individual
differences in adult levels of performance were correlated withthe past and current amount of deliberate practice at a given
age, in particular the age of 18, when performers in music arenormally selected for higher levels of professional training. Because our methodology for assessing the current and pastamounts of deliberate practice is new, we further explicate therelation between performance and deliberate practice by considering research findings in music and other domains of expertise.
Our framework predicts a monotonic relation between thecurrent level of performance and the accumulated amount ofdeliberate practice for individuals attaining expert performance. The general shape of this relation is illustrated by thesolid line in Figure 16. It is relatively rare that domains of expertise have a univariate performance variable that quantifies theperformance for individuals at different ages and levels of performance. The best examples are individual track and field
events in sports, for which the performance of any individual
can be measured. Particularly in sports, but in other domains as
well, developmental and maturational factors are known to influence performance as a function of age. For example, age-related changes in height may directly or indirectly influence
performance in certain sports. For these reasons in virtually all
domains individuals are grouped by age for external evaluationand competitions. Consequently, many studies report performance as a function of age. If performance is graphed as afunction of age, where the first data point corresponds to anindividual's introduction to the domain and start of deliberate
practice, we expect a monotonic relation similar to the solidline in Figure 16, although the exact functional form of thecurve is not important.
To evaluate acquired musical skills, J. G. Watkins (1942) de-signed a test to assess the level of performance of a musicalpiece by 151 cornet players who had had from 1 to 10 years ofprior practice. Music performance was related to the number ofyears of practice by a functional form very similar to the solidline in Figure 16. Longitudinal studies of elite performers
found that their recorded performance at younger ages showsmonotonic improvement even well after the age of 18 when
physical maturation is completed. Curves for the personal best
performance on an event as a function of age and training for
elite performers (see Ericsson, 1990, for some examples) haveroughly the shape shown by the solid line in Figure 16 until acontestant attains the highest performance of his or her career.
The rating system in chess has properties of an interval scale,and Elo (1978) found that the earlier chess ratings increased in asimilar manner as a function of age well through their twenties
for three groups of elite chess players.
When we consider the evidence for the 10-year rule of preparation to attain international-level performance, even when individuals started during adolescence and adulthood, a rather
continuous acquisition of expert performance is implicated.
Evidence for the accumulated effects of deliberate practice on
expert performance is clearer when we examine mediating skill
components, such as increases in amount of accessible knowledge, where the acquisition process is well established in laboratory studies. Differences in expert performance have been successfully related to tests measuring the amount of relevant
knowledge and procedures in chess (Pfau & Murphy, 1988),
mathematics (Webb, 1975), and sports (French & Thomas,
1987). The organization and accessibility of knowledge has also
been shown to distinguish individuals at different levels of expertise in physics (Chi, Glaser, & Rees, 1982), medicine (Feltovich, Johnson, Moller, & Swanson, 1984; P. E. Johnson et al.,1981), and social science (Voss, Greene, Post, & Penner, 1983).
Unlike the rapid decay of acquired knowledge seen in laboratory studies, repeated application and use of knowledge overextended periods leads to remarkably good retention of the388

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

knowledge even after years or decades of disuse. Bahrick andHall (1991) found considerable retention of knowledge of mathematics for content from a successive sequence of courses withthe exception of the most advanced mathematics course taken.
Similarly, once an individual has acquired a reasonably highlevel of skill, it is possible for that individual to attain an aboveaverage performance or even regain the original performanceafter a brief period of retraining. A moderate level of acquired
skill in typing (Baddeley & Longman, 1978; Hill, 1934,1957;
Hill, Rejall, & Thorndike, 1913), language (Bahrick, 1984), andother domains (Farr, 1987) appears to decay slowly and can be
rapidly reacquired.
The demonstrations of retained skill without recent practiceas well as of regaining a considerable level of skill with limited
current practice are relevant to our framework for a couple ofreasons. First, such demonstrations might appear to show acomplete dissociation of current practice and performance.
Given that acquired skill resulting from prior accumulated
practice cannot be observed, it could easily be incorrectly attributed to native talent. Second, the relatively small amount ofpractice required to maintain or regain a previously acquired
level of nonelite performance is quite different from the massive amount of practice required originally to attain that level or
improve even more. Furthermore, elite performers rarely experience problems from long periods of inactivity because once
they take up systematic practice they continue practicing at a
uniformly high level, and we assume that the amount of deliberate practice necessary to specifically maintain earlier attainedlevels of performance is negligible for active young experts.
Our framework postulates that individual differences in performance at a given age are a function of acquired characteristics, which in turn are directly related to the accumulated
amounts of deliberate practice. Given the earlier reviewed evidence for the stability of daily and weekly amounts of practice,
it is possible to approximate the accumulated amount of practice on the basis of weekly estimates. There are two sources ofindividual differences. First is the number of years of deliberate
practice, which is a linear function of starting age. In the General Discussion we discuss the possibility that assessed talentprior to practice is the cause for initiating practice early. Second, individual differences in the weekly amount of practice at
a given time will influence the rate of increase of accumulated
practice and the current level of performance. Current performance and current level of practice are determined concurrently and the direction of causality cannot be determined on
temporal grounds. In the following review of evidence on
weekly amounts of practice, we discuss additional evidence on
the direction of causality.
Relation Between Starting Age and Performance
During childhood and adolescence the performance of anindividual is evaluated by comparison to those of other individuals of the same age. An individual starting at an earlier age
would have accumulated more deliberate practice and thus
have acquired a higher level of performance. An individual exhibiting a higher performance at any age would be more likely
to be given resources and support by the environment. The
dashed line in Figure 16 illustrates performance as a function ofage for an individual who starts practicing later in life than theindividual represented by the solid line. In this ideal case, thedashed line is simply shifted to the right, which gives the individual with the earlier starting age a higher performance level at
all ages. Even in a more realistic case, where the performancelevel of individuals starting later would initially increase faster,
the advantage of an early start would remain. In many different
domains elite performers tend to start deliberate practice andinstruction at remarkably young ages. In this section we consider the starting ages of music performers, athletes, and chessplayers. Information about world-class and eminent performers
will also be included as their development is assumed to matchor surpass the top-level expert performers.
A discussion of music performers requires a separate review
for different instruments. Consistent with the observation that
it is more difficult fora child to play a normal-sized violin thana piano, we found that our four groups of expert violinists wereolder when they started than were the expert pianists, F(\, 40)= 9.60, p<. 01. This comparison is shown in Table 3. Although
we found no statistically reliable differences among the starting
ages of the different groups of adult violinists, these violinists
started almost 3 years later than a group of the best solo violinists of the 20th century (Heizmann, Krampe, & Ericsson,1993), F(1, 41) = 18.88. p < .001. Only those 13 violinists who
had had a solo career for more than 20 years and were mentioned by both Roth (1982, 1987) and Schwarz (1983), threemain reference books, as internationally famous violinists bornin the 20th century were included in this group of outstanding
performers. Expert pianists in Study 2 started instruction atnearly the same age as the age given by Sosniak (1985) for pianists who win international competitions, which is similar tointernationally famous pianists from the 20th century (Heizmann et al, 1993). Expert pianists in their fifties and sixties(Krampe, 199!) had a starting age of 7.8 years, which was considerably older than for the young experts in Study 2 and thefamous pianists. The starting ages for amateur pianists are reliably older, as we reported in Study 2. It appears necessary for
professional musicians to start earlier than most of the amateurs in the same domain. The large sample of elite music performers studied by Manturzewska (1990) contained no individual who had started later than age nine.
In sports, the time at which an individual first engages in theactivity is much less closely linked to the start of deliberate
practice than to the start of competition in an event after theindividual joins a team. Table 3 summarizes data on starting
ages for athletes at different levels of performance in swimming, gymnastics, running, and tennis.
Chess differs from music and sports in that chess is not normally studied under the close supervision of professional
teachers and coaches who direct daily practice activities. Evenin chess, however, some critical events and indicators enable us
to assess players' early exposure and occupation with the game.
To be able to play chess, a beginner must receive an explanationof the rules, and a chess board has to be available. Hence thestarting age for playing chess is fairly distinct and can be easily
reported, especially by chess players. Krogius (1976) presented
biographical data on world-famous chess masters born in the
19th and 20th centuries. The oldest starting age among Krogius' grand masters was 17. For chess players born in this cen-THE ROLE OF DELIBERATE PRACTICE

tury, the oldest starting age is 14, and the mean starting age is 9
years. We found that in Krogius' data, the starting age is closely
correlated, r(38) = 0.48, p < .001, with the age of players' firstachievement of an international level of performance. According to Mayr (1989), a small sample of contemporary grand masters reported starting at about 7 years of age, a finding thatsuggests a historical trend toward younger starting ages. The
starting age for a larger sample of chess masters was 10.5 yearsof age. The age at which contemporary grand masters joined achess club is reliably younger than the age for contemporary
national-level chess masters in Mayr's sample (Ericsson, TeschRomer, & Krampe, 1990).
Consistent with our hypothesis, we find that the higher thelevel of attained elite performance, the earlier the age of first
exposure as well as the age of starting deliberate practice. In
some domains such as music and ballet, it is generally foundthat elite performers have started well before the age when mostchildren first gain access to training.
Weekly Amount of Practice and Performance During theDevelopment of Elite Performance
Once individuals have started with deliberate practice, additional differences in accumulated practice can be due to individual differences in the weekly amount of deliberate practiceat the same ages. The dashed line in Figure 16 illustrates a casewith a higher level of weekly practice, which would give an
individual a uniform advantage compared with the individualwith the same starting age but with less weekly practice (dottedline). This case is similar to the differences in weekly practiceintensity between the four groups of violinists in Study 1.
In our review of practice in the domain of music, we foundevidence for the claim that deliberate practice is a specific typeof music-related activity, which is judged to be most relevant for
improvement of music performance, effortful, and less inherently enjoyable than leisure and several other music-related activities. Individual differences in the amount of deliberate practice in music at the same ages were found to correlate withcurrent and future music performance, even sometimes in theabsence of reliable differences in the overall amount of timespent on music-related activities. Given that the distinction be-389

tween deliberate practice and other domain-related activities isnew, it is difficult to find available data relating performanceand weekly amounts of deliberate practice. We review available
evidence on indicators of deliberate practice in sports, wherecoaches supervise training and also in chess, where individuals
are assumed to acquire their skill without explicit guidance.
On the basis of interviews and questionnaires, future elite
performers have been found to spend a large amount of time
per week on their domain even at a young age: 20 hr per weekby tennis players around age 13 (Monsaas, 1985) and 24-30 hr
per week by swimmers around age 11 (Kalinowski, 1985).
Given that these childrens' and adolescents' activities are forthe most part supervised by coaches, it can be inferred that asignificant portion of this time is spent in deliberate practice.
Better estimates of current levels of practice have been obtainedby Kaminski et al. (1984) who used a diary procedure to assessthe duration of actual practice for national-level swimmers, iceskaters, and gymnasts at ages 15-16. These athletes practiced
about 16 hr per week, almost 3 hr more than the athletes below
the national level practiced. These pure estimates of practicecannot be directly compared with the retrospective estimates
for the international-level athletes (Kalinowski, 1985; Monsaas, 1985), but they appear to be considerably lower. On thebasis of the questionnaire responses from a large sample ofmale runners, 17-18 years old, Sack (1975) estimated the frequency of training during a week for runners at different levelsof performance. Runners at the national level trained 4.9 times
per week; runners at regional and local levels trained 4.2 and3.2 times per week, respectively. Apart from the number ofparticipations at national championships, the best predictor of
the subjects' best running performance was the frequency of
training (r = .56). Questionnaire items referring to motivation(e.g., "regular training" and "training during holidays") werereliably correlated with both frequency of practice and performance. The performance of adult marathon runners in a race
can be predicted with high accuracy from the regularity andamount of practice during the 9 weeks preceding the race (Hagan, Smith, & Gettman, 1981). The length of training runs andthe total distance covered per week accounted for nearly half ofthe variance in actual running times on the marathon. Even
better evidence for the relation between performance and390

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

amount of practice comes from recommended training schedules for different levels of competitive runners (Glover &Schuder, 1988). Championship competitors not only take moretime practicing and cover longer running distances than advanced and basic competitors, but they spend proportionallymore time on training directed at improving endurance andspeed, such as interval training and fartlek. An analysis of the
training schedules of the world's best long-distance runners
shows that they uniformly put a major emphasis on speed work
(Noakes, 1991), which is typically completely absent in the
training of recreational runners. A recent interview study(Sachs, 1991) of conditions inducing the enjoyable state called"runners' high" showed the importance of a comfortable paceduring an extended run and the absence of any strain to run
fast, which seems to preclude deliberate practice.
Unfortunately, we did not find any systematic data on theamount of time elite chess players spend playing and studying
chess. There are, however, some unique data available about
improved competence in chess as a function of age (Elo, 1978).
With the Elo Rating System, it is possible to assess the chessskills of young chess players with the same interval scale used
for adults. By analyzing the development of chess skills in many
individuals who reached world class, international level, andnational level, Elo (1978) found that at 11-12 years of age, differences in chess playing ability were relatively small. At thatage, all three groups of subjects played at the level of average
adult chess players. Large improvements in ability were observed for the players during adolescence (12-18 years of age).
From the ages of 18-22, improvements started leveling off anddifferences in ability between the three groups remained relatively unchanged. These results are unique within the threedomains considered in this article because musical performance is not rated on an age-independent scale, and physicalgrowth during adolescence seriously confounds available measures of performance in sports.
Even less information is available on the way full-time chessplayers allocate their time to chess-related activities. Charness(1991) estimates that the actual time spent playing chess games
at tournaments, chess clubs, and private games constitutes only
a fraction of the time available to chess players and that theygive more time to individual study and analysis of chess positions and published chess games. In informal interviews, chessmasters report spending around 4 hr a day analyzing publishedchess games of master-level players. Selecting the next moves insuch games provides an informative learning situation in which
players compare their own moves against those selected in an
actual game. A failure to select the move made by the chessmasters forces the chess players to analyze the chess position
more carefully to uncover the reasons for that move selection.
There exists also a large body of chess literature in which worldclass chess players explicitly comment on their games and encyclopedias documenting the accumulated wisdom on various
types of chess openings and middle-game tactics and strategies.
An examination of biographies of world-class chess players(Karpov & Roshal, 1980; Korchnoi, 1978) shows, contrary tocommon belief that chess players develop their chess skills independently, that these elite players have worked closely with individuals (other more advanced players, often chess masters) who
explicitly taught them about chess and introduced them to theliterature on chess. Of particular interest are Bobby Fischer andJudit Polgar, who attained their international grand master status at the youngest recorded age, namely age 15. Bobby Fischer
learned the rules of chess at age 6 and in the same year hestarted studying his first book of chess games (F. Brady, 1973).
As a result of his mother's initiative, at age 7 Bobby got in touchwith the president of the Brooklyn Chess Club, who tutored
Bobby on a weekly schedule for several years and actively supported Bobby's chess career. At age 12 Bobby joined the Manhattan Chess Club, which was one of the strongest in the world.
Around that time he started close interactions with the strong
chess master Jack Collins several times a week and got freeaccess to Collins' outstanding library of chess books. From thatpoint Bobby started collecting chess books, and in 1973 he had
about 400 books and thousands of magazines and journals (FBrady, 1973). According to Brady (1973), Bobby Fischer became the best educated chess theoretician in modern times.
Judit Polgar was tutored in chess by her father from age 4 (J.
Radford, 1990) or, at least, age 5 (McFadden, 1992) and carefully coached by her father. Judit did not attend regular school
and was allowed to spend all the time with her parents, whowere both teachers.
Consistent with our framework, we find that elite performers
spend much time on deliberate practice and, in those cases inwhich amount of weekly deliberate practice has been recorded,
high level of performance is associated with higher levels ofdeliberate practice at the same age. Another striking, but not
surprising, finding is that the amount of weekly practice forindividuals maintaining regular practice increases with age, accumulated practice, and performance. Given the early starting
ages and the high level of practice of the expert performers theavailable data do not allow an analysis of the independent andinteractional effects of those variables. Furthermore, the structure of training programs in virtually any domain adapts thedeliberate practice activities to suit the level of current performance. Increased complexity and proficiency of acquired skills
and characteristics leads to increased performance and allows
for engagement in more challenging deliberate practice activities for a longer period of time. This would be particularly clear
for domains with endurance activities, such as long-distancerunning. In our framework we expect that increased level ofacquired skill and performance would increase the maximal
level of deliberate practice that can be sustained over extended
periods of time without exhaustion.
In our framework accumulated deliberate practice causes acquired skill and characteristics, which in turn cause performance, and some of these characteristics increase the maximal
amounts of possible practice. It is, of course, possible that nonacquired factors, such as innate talent, might influence performance directly. A performance advantage resulting from suchfactors can allow individuals, essentially by definition, to complete the same activities (including deliberate practice) for
longer times with the same amount of effort. Although thismechanism provides an account for individual differences inwork-related activities, where the goal is to maximize theamount produced, we believe that it cannot be extended todeliberate practice for the following reasons: The goal of deliberate practice is not "doing more of the same." Rather, it involves
engaging with full concentration in a special activity to improve

THE ROLE OF DELIBERATE PRACTICE
one's performance. As deliberate practice is not inherently enjoyable, there doesn't seem to be any reason for engaging in it or
prolonging its duration unless the individuals and theirteachers believe that their performance improves as a result.
Many other domain-related activities are judged to more enjoyable than deliberate practice and they should be preferred.
Hence, there doesn't seem to be any reason for engaging indeliberate practice, and especially prolonging its duration, unless the individuals and their teachers believe that their performance improves as a result.
Further evidence against the hypothesis that higher levels of
performance cause an elevated level of deliberate practice isfound for adult elite performers. The general level of deliberate
practice has been increased in many domains in the recent
past. For example, the training distances in swimming were
almost doubled in preparation for Olympic Games in 1972 (Kalinowski, 1985). The steady improvement of world records insports is generally recognized to reflect more practice and, inparticular, the faster improvement of world records for womenis believed to be due to disproportionate increase in the levelsof training for women (Wells, 1991). In Study 1 we found differences in accumulated practice but no differences in the current
levels of deliberate practice for the best and the good expert
violinists. The daily amount of around 4 hr of deliberate practice was also found for the expert pianists, raising the possibility of a more general limit on the maximal amount of deliberate
practice that can be sustained over extended time without exhaustion.
Maximal Levels of Deliberate Practice Sustained Over
Extended Periods
According to our framework, elite performers attempt tomaximize the improvement of performance all through theirdevelopment and, thus, should reach in adulthood the highest
stable levels of deliberate practice that they can sustain without
exhaustion. During adolescence, the daily lives of future elite
performers are quite constrained by school activities. In spite ofthis, Kaminski et al. (1984) found that young elite performers inmusic and various types of sports, such as gymnastics, swimming, and ice-skating, spent more than 15 hr on weekly practice. Furthermore, this amount did not differ systematically
across domains. When expert performers make a full-timecommitment to the domain, our studies showed that they
spend between 50 and 60 hr per week on domain-related activities. Less than half of that time (about 25 hr per week) is spent
on deliberate practice, and this time is distributed across theentire week in practice sessions of limited duration. Our analyses of rest and relaxation were consistent with our claim thatthese individuals had attained a level of deliberate practice limited not by available time but by available resources for effortfulpractice.
A similar pattern holds true for professional athletes. Elite
long-distance runners usually run twice a day and cover distances from 65 to 140 miles every week of the year (Hagan et al.,
1981; Wallingford, 1975). From published reports in the magazine Runner's World on the weekly practice schedules of professional long-distance runners who are in complete control of theduration and distribution of practice, it is clear that the vast391

majority of runners practice every day except for days during
the weekend with competitions. A normal day of practice consists of a session before lunch and a more strenuous session in
the afternoon. The duration of a training session is about 45-90
min and the daily total of deliberate practice amounts to 2-3 hr.
The total time including preparation, warm-up, massage, andso forth, is considerably longer. Similar estimates are reported
for other types of sports, such as swimming (Reilly, 1990b) andcycling (Burke, Faria, & White, 1990). Athletes' pursuit of mostother types of sports is characterized by maximal efforts totrain without inducing exhaustion and burnout (Reilly &Secher, 1990). Similar to musicians, the amount of deliberate
practice is not limited by available time; professional athletes
spend their "free" time on recuperation and relaxing activities.
Olympic athletes sleep for close to 8 hr and in addition take ahalf-hour nap each day (Coleman, 1986). Many elite runners
take a nap between daily workouts (Glover & Schuder, 1988).
The complete focus on a single domain by elite performers inmusic and sports is further evidence that their efforts to reach
their highest performance in that domain are maximal.
Studies of international-level performers have included artists and scientists as well as athletes and musicians. The studies
reported in a book edited by Bloom (1985a) show several clear
parallels between the development of artists and scientists on
the one hand and that of athletes and musicians on the other.
\fears of intensive preparation under the supervision of a master invariably precede the attainment of international recognition. Consistent with the data on athletes and musicians, eminent scientists are completely absorbed in their vocation so "asto seriously limit all other activity" (Roe, 1953, p. 49). The degree of commitment has been quantified in a couple of sources(Bruner, 1983; J. R. Hayes, 1981) to suggest that scientists must
work 80 hr per week for an extended time to have a chance ofreaching an international level in their field. Although our theoretical framework supports the full commitment to the domain
it takes issue with the implication that one should maximize
the number of hours of any domain-related activity. Instead wesuggest that one should identify those activities that are most
likely to result in the desired achievements.
In science an eminent achievement nearly always corresponds to a new theory or idea presented in the written publication of a persuasive argument. The deliberate activities that arenecessary for producing such a rare result consist of focusedand extended work developing and refining generated theoretical solutions to selected general problems. We believe that during the process of writing scientists develop and externalize
their arguments. The written products can be successively criticized and improved by the scientists themselves, even after long
delays, and also easily shared with other scientists for evaluationand comments. The writing of expert authors on new topics isdeliberate and constitutes an extended knowledge-transforming process, quite unlike the less effortful knowledge-telling
approach used by novice writers (Scardemalia & Bereiter,
1991). In support of the importance of writing as an activity,
Simonton (1988) found that eminent scientists produce a muchlarger number of publications than other scientists. It is clear
from biographies of famous scientists that the time the individual spends thinking, mostly in the context of writing papers
and books, appears to be the most relevant as well as demand-

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K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

ing activity. Biographies report that famous scientists such as C.
Darwin, (E Darwin, 1888), Pavlov (Babkin, 1949), Hans Selye(Selye, 1964), and Skinner (Skinner, 1983) adhered to a rigid
daily schedule where the first major activity of each morning
involved writing for a couple of hours. In a large questionnaire
study of science and engineering faculty, Kellogg (1986) foundthat writing on articles occurred most frequently before lunch
and that limiting writing sessions to a duration of 1-2 hr was
related to higher reported productivity. Many scientists involved in laboratory studies, teaching, and administrationmust cope with external constraints on their time that may
partially determine how they schedule writing and thinking. In
this regard, it is particularly interesting to examine the way inwhich famous authors allocate their time. These authors often
retreat when they are ready to write a book and make writing
their sole purpose. Almost without exception, they tend toschedule 3-4 hr of writing every morning and to spend the restof the day on walking, correspondence, napping, and other lessdemanding activities (Cowley, 1959; Plimpton, 1977).
Further evidence that elite performers try to maximize theeffectiveness of their deliberate activities is found in their preference for engaging in them at a certain time of day. The preferred
time of day for deliberate activities differs across domains. Scientists and authors consistently chose to use mornings for demanding writing, and athletes prefer afternoons for their moststrenuous practice sessions. Research on the effects of the timeof day (Folkard & Monk, 1985) shows that simple perceptualmotor performance is enhanced in the afternoon and early evening, whereas intellectually demanding activities are enhancedin the morning. Systematic studies confirm that performanceof elite athletes is reliably higher in the afternoon and evening
than in the morning (Winget, DeRoshia, & Holley, 1985).
Across several different types of domains, elite performers
are found to engage in similarly high levels of selected activities,
such as deliberate practice. The complete focus on the domain
provides most of these individuals with much available time,
yet the time for deliberate practice occupies only a fraction ofthat time, with clear preferences about the best time of day. The
amount of time they spend on practice and other highly relevant activities appears to be limited by how long the demanding activity can be continued with sustained benefits rather
than by the available time.
An Account of Individual Differences in Elite
Performance in Terms of Deliberate PracticeIn our framework we distinguish between two types of elite
performance: expert and eminent performance. Expert performance reflects the mastery of the available knowledge orcurrent performance standards and relates to skills that masterteachers and coaches know how to train. Eminent performancerequires that the individual go beyond the available knowledge
in the domain to produce a unique contribution to the domain,
hence it is, by definition, not directly instructable. Our framework proposes that the probability of making eminent contributions is related to the amount of deliberate efforts directed
toward that goal.
Our framework makes stronger claims for the acquisition ofexpert performance. We argue that expertise and expert perfor-

mance are the result of extensive engagement in relevant practice activities supervised by teachers and coaches and that individual differences in ultimate performance can largely be accounted for by differential amounts of past and current levels ofpractice. Across many domains of expertise, a remarkably consistent pattern emerges: The best individuals start practice atearlier ages and maintain a higher level of daily practice. Moreover, estimates indicate that at any given age the best individuals in quite different domains, such as sports and music, spend
similar amounts of time on deliberate practice. In virtually all
domains, there is evidence that the most important activity—
practice, thinking, or writing—requires considerable effort andis scheduled for a fixed period during the day. For those exceptional individuals who sustain this regular activity for months
and years, its duration is limited to 2-4 h a day, which is afraction of their time awake.
Contrary to the popular "talent" view that asserts that differences in practice and experience cannot account for differencesin expert performance, we have shown that the amount of a
specific type of activity (deliberate practice) is consistently
correlated with a wide range of performance including expertlevel performance, when appropriate developmental differences (age) are controlled. Because of the high costs to the individuals and their environments of engaging in high levels ofdeliberate practice and the overlap in characteristics of deliberate practice and other known effective training situations, one
can infer that high levels of deliberate practice are necessary toattain expert level performance. Our theoretical framework canalso provide a sufficient account of the major facts about thenature and scarcity of exceptional performance. Our accountdoes not depend on scarcity of innate ability (talent) and hence
agrees better with the earlier reviewed findings of poor predictability of final performance by ability tests.
We attribute the dramatic differences in performance between experts and amateurs-novices to similarly large differences in the recorded amounts of deliberate practice. Furthermore, we can account for stable individual differences in performance among individuals actively involved in deliberate
practice with reference to the monotonic relation between accumulated amount of deliberate practice and current level of
performance. The individuals who start early and practice at
the higher levels will have a higher level of performancethroughout development (the solid line in Figure 16) than those
who practice equally hard but start later (line with long dashes).
The differences in performance between subjects with thesame starting age but differing levels of practice are shown in
Figure 16, where the line with long dashes shows the performance associated with a high level of practice and the dottedline a lower level of practice.
Figure 16 illustrates how our framework can account for
many common observations about skill acquisition and stable
individual differences in performance. Individuals with a later
starting age for deliberate practice will experience rapid initial
improvements and may feel that they will in a few years attainthe level of individuals with earlier starting ages and thus higher
performance at comparable ages. However, because the rate of
improvements with practice decreases and becomes less perceptible, the difference between the two groups remains distinct,
and an attribution of greater talent for the group with earlier

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THE ROLE OF DELIBERATE PRACTICE
starting ages is natural. In the current system with age-matchedevaluation of performance, it is impossible for an individualwith less accumulated practice at some age to catch up with thebest individuals, who have started earlier and maintain maximal levels of deliberate practice not leading to exhaustion. As
noted earlier, the amount of possible practice appears to slowly
increase with accumulated practice and skill. Hence, individuals intent on catching up may suddenly increase the amount ofdeliberate practice to the level or even above the level of the best
performers. Within months these individuals are likely to encounter overuse injuries and exhaustion and may terminate
their engagement in the domain convinced that the best performers are qualitatively different. Furthermore, the differencein accumulated deliberate practice in late adolescence for thegood and best violinists is remarkably large and to eliminate
this difference the good violinists would have to practice anadditional 5 h per week beyond their current optimal level ofweekly practice for more than 8 full years.
The problem of overcoming differences in skill resulting
from accumulated practice is further amplified by the continuous selection of individuals because of the costs associated withthe maintenance of deliberate practice. In all domains there is
only a small number of positions in which individuals can freely
continue their efforts to attain eminent performance without
severe occupational constraints. Prior to that, the best training
environments with master teachers and coaches carefully selectthe individuals with the best performance in late adolescence.
Institutions providing grants and master teachers have strong
restrictions on the maximum age of applicants. From the startof training, the individual and his or her teachers and parents
constantly monitor and compare the current performance tothat of other individuals of the same age in the domain to assess
whether the costs in time, effort, and money associated withsustaining high levels of deliberate practice are warranted. Ahigh level of performance, whether it is due to acquired skill orto innate talent, will always be the best predictor of future
performance and will therefore attract motivational support
and necessary resources. The majority of individuals in thedomain are not provided these resources because of their lower
current performance at the relevant ages with lost opportunities for further development.
In addition, our theoretical framework can easily account forchanging levels of performance in different historical times
and in different cultures by corresponding differences in theencouragement and availability of deliberate practice. Wells(1991) attributed the big differences in athletic performance
between men and women, which are currently decreasing as afunction of changing sex-role expectations, to differential "opportunities for participation at an early age and the availabilityof expert coaching" (p. 49).
In summary, our framework can account for a wider range of
empirical characteristics of exceptional performance than thetalent view. Although we are reluctant to accept individual differences in innate abilities (talent) and any important role ofthese differences in determining expert performance, we do
not rule out the importance of individual differences in general. In fact, within our framework we would expect that several"personality" factors, such as individual differences in activity
levels and emotionality may differentially predispose individ-

uals toward deliberate practice as well as allow these individuals to sustain very high levels of it for extended periods. We
now turn toward a reevaluation of the evidence linking expert
performance and innate abilities and characteristics reviewed
in the introduction. Once individuals have started deliberate
practice, it is virtually impossible to distinguish the role of natural ability (innate talent) from that of acquired characteristics
and skill in their current level of performance. This is particularly true as the effects of extended practice, especially at youngages, are much more far reaching than commonly believed possible. In the General Discussion we review evidence on thepossibility that early signs of natural ability (talent) are thecause of especially early start of practice, as well as the reverse
possibility that characteristics assumed to reflect innate talent
are the result of deliberate practice.

General Discussion
In a couple of respects our findings and those from the literature we reviewed are consistent with two of the three factors
Galton (1869/1979) thought necessary for attaining eminent
performance. The necessity for 10 years of preparation is clearlyconsistent with Galton's requirement of motivation and perseverance. The quantified role of deliberate practice corresponds
nicely with Galton's prerequisite of "adequate power of doing agreat deal of very laborious work" (p. 37). Although both ofthese factors could be plausible loci for heritable differences,
Galton and subsequent researchers in genetics have emphasized that a third factor, namely, innate ability, is the major
source of heritable differences that determine eminent performance.
The best information about the innate attributes characterizing the best performers can be gained by careful examination
and analysis of critical attributes that distinguish these individuals from less successful individuals. Because innate differences have traditionally been viewed as impossible to modify,
researchers have been interested primarily in innate differences that can be detected in children at very early ages andthus aid parents, teachers, and coaches in guiding these children into the domain appropriate to their talents. Selecting adomain is more difficult if, as Galton believed, general talents
predispose a child for eminence in almost any domain. If there
is such a thing as a general talent, availability and the child's
early interest in a domain would govern the selection of a domain for early start of practice. Both the hypotheses of generaland domain-specific talents would predict that a child would
exhibit signs of talent after a short period of exposure to thedomain. This raises the possibility that talent revealed earlyprovides the environmental support and motivation for the
early start of practice and the high levels of deliberate practiceobserved while individuals are attaining expert performance.
According to this hypothesis, early talent is the cause of increased practice, and the correlation between practice and elite
performance is confounded by differences in initial talent.
In the following discussion we reexamine the evidence, citedin the introduction to this article, for the role of innate differences in the attainment of expert performance. The dichotomy
between characteristics that can be modified and those thatcannot may not be valid when we examine the effects of over

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K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

10,000 h of deliberate practice extended over more than a decade. We first consider the possibility that many of the physicalcharacteristics of elite performers are the result of adaptation to
many years of intense training and are not a direct expression ofgenes. We then discuss the abilities and characteristics displayed by children and "idiot savants" and consider whether
these abilities are acquired through normal learning and adaptation. We discuss the relation between early performance andlate performance in the acquisition of skill and expert performance, and we review evidence on the qualitative differencesthat emerge with extensive practice. We review evidence for therole of early talent and parent-offspring relations in acquired
performance. Finally, we offer an alternative account in termsof "perceived talent" and predisposition to deliberate practice.
Distinct Physical Characteristics of Elite Performers
Perhaps the most commonly cited evidence for innate talentis that elite athletes in many types of events have unique physical advantages. The physical and anatomical differences between elite athletes and less successful athletes or even normal
adults are often simply assumed to reflect pure genetic factors.
However, some of these differences may not be innate but instead may be the result of physiological adaptations to extremely intense practice extended over many years. If thesecharacteristics are purely genetic, it should be possible to demonstrate that they are inherited and that they are manifest in
the absence of any special environmental influences. Ideally, it
should be possible to specify the biochemical mechanisms that
control the emergence of these characteristics.
Height is an excellent example of a characteristic for which
the genetic mechanism has clearly been demonstrated. It is
well-known that genetic factors closely determine height in industrialized countries with adequate nutritional support (Wilson, 1986). In developing countries such as Mexico (Malina &Bouchard, 1991), the average height of well-nourished individuals can be as much as 7 inches higher than the average heightof undernourished individuals. The age at which the highest
increases in height are observed during development also appears to be genetically determined (Malina & Bouchard, 1991).
Environmentally induced differences in the height of newbornmonozygotic twins disappear during development (Wilson,
1986). Moreover, the primary method of altering height, except
for reduction by surgery, consists of supplementary injectionsof growth hormone during development. All of this persuasive
evidence compels us to attribute adult height primarily to genetic factors when nutritional requirements are met.
One might assume that all or most morphological characteristics of the bodies of adults are similarly determined primarily
by genetic factors. Studies comparing elite athletes to other athletes and nonathletes have revealed systematic differences insizes of hearts, lungs, bones, and muscles; proportions of slowtwitch and fast-twitch muscles; amount of fat; number of capillaries supplying blood to muscles; as well as in aerobic power
and ability. Many of these differences were originally believed
to be almost completely determined by genetic factors in thenormal population of adults. Considerable empirical work has
shown, however, that these differences have only a moderate
genetic component (Bouchard, 1986). In a recent study Fagard,

Bielen, and Amery (1991) found reasonably high genetic components for maximal aerobic and anaerobic power even whendifferences in the amount of exercise and other life-style factors
were controlled. However when testing was made at submaximal levels—more comparable to normal activity levels—theamount of exercise and other life-style factors accounted for all
systematic variance. This result suggests that many physiological characteristics are the result of adaptation to a level of daily
activity.
For older sedentary adults, additional scheduled walks improve aerobic ability, whereas young adults require sustained
training at around 75% of maximal heart rate to realize improvements (Ericsson, 1990; Haskell, 1989). Extended exercise
programs show that aerobic ability is not fixed but can be dramatically changed. After a year of exercise, adults can increase
their aerobic activity up to 35% and in some instances up to
50% (Haskell, 1989). However, to reach the aerobic ability ofelite endurance athletes, average nonathletes would have to increase their aerobic ability by 75%. In Haskell's (1989) view, thisfact supports the role of genetic factors; but Haskell's inferenceis based on extrapolation from training programs for fully developed adults, programs that last a fraction of the duration
known to be required to attain expert-level performance insports.
Detailed examinations of the anatomical changes resulting
from intense exercise reveal that the human body is remarkably
adaptable. The number of capillaries supplying blood to muscle fibers changes after a few weeks of practice (Salmons &Henriksson, 1981). Increased numbers of mitochondria, as wellas other biochemical changes, which increase the efficiency ofmetabolic processes, result from extended exercise (C. Williams, 1990). Even the characteristics of muscle fibers can bechanged, namely from fast-twitch to slow-twitch and vice versa.
Although this conversion of muscle fibers has been documented in animal research (Salmons & Henriksson, 1981), a
review by Howald (1982) showed that the fiber conversion demonstrated in animals can be generalized to human skeletal muscles. There is good evidence that environmental conditions caninfluence the volume of the lungs. Greksa (1988) examined
individuals of the same ethnic and racial background who atvarious ages moved from locations at sea-level to a location atover 10,000 feet. He found that the younger the age at the timeof the move to high altitude, the larger the lung capacity and thedepth of chest.
The best evidence linking intensive training directly to observed changes in heart size comes from longitudinal studies ofyoung athletes attaining expert performance and of older athletes terminating their careers and practice regimens. Elovianio
and Sundberg (1983) found that elite long-distance runners acquired greater aerobic power and larger heart volumes during a
5-year period of training but showed no initial superiority at age
14. Rost (1987) found during a longitudinal study of children
from age 8 to 11 that heart volumes increased much more inyoung swimmers than in nontrained children (control). It appears that at least 1 year of intense training is required before
the size of a human heart begins to change. Similarly, once
athletes terminate their training the increased heart sizes remain, but in the absence of exercise the heart volume regresses
to within normal range over a 10-year period; Rost (1987) re-THE ROLE OF DELIBERATE PRACTICE
ports a volume reduction of 42% in one case. Howald (1982)
reports case studies of top athletes who were forced to stop or
reduce training because of injuries. Drastic decrements in thepercentage of their slow-twitch fibers occurred within 6 months
to 1 year.
Because most sports involve only some of the muscles in thebody, it is possible to contrast these intensively trained muscles
with other muscles in the same athletes. Tesch and Karlsson(1985) examined the size and frequency of fast- and slow-twitch
fibers in the muscles of different types of elite athletes as well asof students serving as control subjects. They found that differences in the percentage of slow-twitch fibers in elite athletes'muscles occur only for muscles specifically trained for a sport(legs in runners and back muscles in kayakers), with no differences for untrained muscles.
Some physiological changes, such as heart enlargements, require years of increasingly intense practice to emerge and takeyears to regress once training is stopped. For example, Eriksson, Engstrom, Karlberg, Saltin, and Thoren (1971) found thatswimmers' aerobic ability decreased by 29% five years after
training had stopped. The increased lungs and hearts of theseswimmers had not changed yet. Other changes are gained andlost more rapidly. For example, aerobic power in bicyclists(Burke et al., 1990) increases over 50% during the competitive
season every year. Female gymnasts reduce the proportion of
their body fat from average levels by 50% during the competitive season (Reilly & Secher, 1990). Within a week of no training, swimmers lose on average 50% of the respiratory capacityof their muscles (Reilly, 1990b), but regaining this capacity
takes considerably longer during retraining.
In sum, most anatomical characteristics, unlike height, areremarkably adaptable to intense physical activity extended overlong periods of time. Detailed biochemical mechanisms mediating the transformation of the phenotype of muscle fibers in
response to intense physical activity (Booth, 1989) and generalmechanisms for influence of environmental factors on developmental outcomes are now being proposed and evaluated (Gottlieb, 1992). Many extreme physical characteristics in elite athletes are the result of the same adaptive processes that determine similar characteristics in the normal population, and theextreme differences in these attributes correspond to theequally extreme differences in the amount and intensity ofpractice between these two groups.
A reasonable objection to the generalizability of the effects oftraining for all adults can be made on the basis of the large
dropout rate for adults from exercise programs (Martin & Dubbert, 1985). It is apparently not possible to motivate all people
to engage in regular exercise. Research on the effects of extended exercise in animals has demonstrated that intensive exercise results in conversion of muscle fibers (Pette, 1984) andenlargement of hearts (Harpur, 1980). The primary method for
motivating animals to exercise vigorously is punishment, forexample, running on a treadmill with a slope to avoid a bar
giving electric shock or swimming with or without additional
weights. However, similar but less pronounced effects havebeen attained from animals that voluntarily run in a wheel
compared with those in a sedentary condition (Harpur, 1980).
Recent research has shown activity-specific physiologicalchanges resulting from extended practice also in the central

395

nervous system. After difficult acrobatic training an increased
number of synapses in the cerebellar cortex were found for rats,
but not for rats engaged in extensive physical exercise, whichinstead exhibited a greater density of blood vessels in the same
area (Black, Isaacs, Anderson, Alcantara, & Greenough, 1990).
Replications of the adaptive changes with animals under controlled conditions are likely to be the best obtainable evidence
on generalizability given the problems of motivating random
samples of humans.
Early Demonstrated Abilities Assumed to Reflect Innate
TalentIn the introduction we mentioned several abilities demonstrated by children and idiot savants that have been thought toreflect innate talents and predispositions. In this section we
consider one of these abilities, perfect pitch, in detail. We also
briefly discuss other abilities of idiot savants and some of the
anatomical characteristics of ballet dancers and swimmers.
Perfect pitch (or absolute pitch), the ability to identify isolated musical tones, is considered a sign of musical talent. Often
future elite musicians and musical savants exhibit perfect pitch
at an early age. Qualitatively different processes mediate theperformance of individuals with perfect pitch and that of musicians who lack it. Individuals with absolute pitch tend to confuse tones with the same location in different subscales but nottones having the smallest difference in fundamental frequencies. For example, an untrained subject might confuse C with B,
whereas a subject with perfect pitch would confuse C in one
octave with C in a different octave (Ward & Burns, 1982). Several empirical findings suggest that perfect pitch is an acquired
skill. Individuals with "perfect pitch" differ in their ability tojudge pitches and perform best when judging pitches generated
with the instrument they play. As the tests of ability to recognize pitch get harder, as they do when artificially generated
sinus tones are used, for example, fewer and fewer subjects pass
the tests (Oakes, 1955). In addition, adults can acquire perfect
pitch after extended training. P. T. Brady (1970) demonstrated
that he was able to acquire perfect pitch by an intriguing training procedure, which involved learning to identify a single tone.
Brady reported that once developed, the identification task required little effort and that he did not have to practice purposefully to maintain the skill. No decrement in performance wasreported after 6 months, and only a slight decrement was reported after 13 years (Costall, 1985). Finally, recent research(Cohen & Baird, 1990) provides evidence that normal children,
especially before age 5, more easily recognize notes individually(absolute pitch) before they perceive notes as part of larger musical structures (relative pitch). These findings suggest that subjects with absolute pitch acquire the necessary skill as children
and then simply maintain it for the rest of their lives (Miyazaki,1990). Young children's acquisition of absolute pitch is intriguingly similar to the ease with which they learn a second language (J. S. Johnson & Newport, 1989), and with Japanese subjects learning to make the difficult distinction between [r] and[1] in English (Yamada, 1991).
The importance of early practice and experience for adultability is similarly found in swimming and ballet. Ballet training must start before dancers reach age 11 to gain the necessary

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flexibility of joints. Stress induced during extensive training at
young ages appears necessary for dancers to gain the necessary"turn out" in the different positions of demi-plie at adult ages
(DiTullio et al., 1989; A. Watkins, Woodhull-McNeal, Clarkson, & Ebbeling, 1989). Dancers apparently acquire flexibility
through early training as shown by a longitudinal study (Klemp& Charlton, 1989). In a large group of club swimmers (aged8-17) the only physical measures discriminating this groupfrom a matched control group of other types of athletes were
ankle and shoulder flexibility (Poppleton & Salmoni, 1991).
Statistically controlling for age, these two measures of flexibility were the best predictors of the swimmers' speed; however,no measure of current or past practice was included in theanalysis. Consistent with the hypothesis that increased flexibility is acquired through extended swimming, it is common that
elite swimmers have weak ankles, which are particularly susceptible to injury (Chambliss, 1988).
Certain exceptional abilities in idiot savants have been taken
as evidence that innate talent accounts for exceptional performance. Given the low general level of these individuals' intellectual functioning, it has seemed plausible that exceptional memory for some types of material and exceptional perceptual abilities, such as perfect pitch, reflect inherited basic capacities. But
recent research has shown that these exceptional abilities are
more consistent with acquired skill than with innate talents(Howe, 1990). Often these individuals' performance on tasks
measuring their abilities is exceptional only compared with
their general level of functioning, which is otherwise low (Ericsson & Faivre, 1988). On the other hand, college students' performance on these tasks can be dramatically improved. Training
studies for memory for numbers (Chase & Ericsson, 1982), datecalculation (Addis & O. A. Parsons, unpublished and describedin Ericsson & Faivre, 1988), and mental calculation (Staszewski, 1988) have shown that within weeks, college students
can attain levels of performance outside the range of normal
adult performance. Careful examination of idiot savants andother individuals with exceptional abilities suggests that they
rely on mechanisms similar to those used by trained students,
and that these individuals have had access to necessary information and opportunity to practice prior to the first publicdemonstration of their abilities (Ericsson & Faivre, 1988; Howe,
1990).
The only exceptional performance that has not beenmatched in a training study is certain individuals' immediate
memory for music they have not heard previously. However,even in this case, recent studies refute the possibility that thismemory performance reflects some basic, superior memory
capacity (Charness, Clifton, & MacDonald, 1988; Sloboda,
1991). Superior memory is limited to music of familiar structure and does not transfer to modern atonal music (Sloboda,
Hermelin, & O'Connor, 1985). This finding is consistent with
one from all other instances of exceptional memory (Ericsson,1985), namely, that knowledge mediates superior performance.
In addition, Judd (1988; see Treffert, 1989, for additional references to blind musical savants) has pointed out that most of themusical savants with superior memory for music were blind.
The only way they could learn new pieces of music was tomemorize them by listening to them. Thus blindness provided
the prerequisite motivation to acquire this memory skill. Withextended practice, their memory performance for music increased and reached exceptional levels.
In summary, exceptional abilities observed in children andidiot savants are consistent with all the characteristics of acquired skills. Most of them can be easily acquired by adults
through known training methods, although some of them may
be more easily acquired during childhood. The motivational
factors that lead children and idiot savants to focus their timeand energy on activities that improve performance are still
poorly understood.
General Difficulties of Predicting Ultimate Performance
From Initial Performance: Qualitative Differences
Acquired Through Extended PracticeIn the introduction we briefly reviewed the difficulties ofpredicting the level of expert performance individuals attainafter extended practice. Bound up with the notion of innate
talents, which are revealed during early performance, is thenotion that the same fixed components determine both early
performance and the final level of performance and thus enable
observers to identify and select future exceptional performers aswell as to predict their final achievement after practice. In thissection we briefly review the literature on individual differences in performance as a function of practice in studies of skill
acquisition. We then review some findings on the nature ofindividual differences in expert performance.
Extensive research on skill acquisition with college students
and more representative samples, such as military recruits,
shows that performance on a wide range of tasks improvesmonotonically as a function of many hours of practice. Current
theories (J. R. Anderson, 1982; Fitts, 1964; Fitts & Posner, 1967)
propose that initial performance is mediated by sequential processes, which with additional practice are transformed into asingle direct (automatic) retrieval of the correct response frommemory. This radical change in processing makes it difficult to
identify any locus for individual differences in innate talentthat could influence initial superiority as well as superior final
performance. The most successful attempts to relate individual
differences in ability to individual differences in performance
have dealt with short-term skill acquisition. Evidence fromthese studies suggests that performance during the initial, middle, and final phase of skill acquisition is correlated with different types of abilities in each phase (Ackerman, 1988), initial
performance being correlated with general cognitive abilities
and final performance with perceptual-motor abilities. Thisevidence is consistent with the current theories of skill acquisition. With several hours of practice, cognitive differences are
essentially eliminated, giving way to the more "basic" differences in components associated with perception and motor production. Because, however, the perceptual and motor systems
show great adaptability in response to extended practice (a phenomenon discussed earlier in this article), it may be inappropriate to generalize the findings from relatively simple tasks involving 2-20 h of practice to expert performance acquired during a 10-year period of intense preparation.
Two general findings concerning individual differences inhigh levels of performance imply that expert performance andinitial performance do not have a common basis. First, mostTHE ROLE OF DELIBERATE PRACTICE
individual differences related to levels of elite performance are
due to the amount and organization of knowledge, which everyone agrees must have been acquired. Finally, memory performance for briefly presented stimuli relevant to a given domain
differs as a function of the level of performance in those domains (Chase & Simon, 1973; for a review see Ericsson andSmith, 199 lb), but does not generalize to scrambled versions of
the same stimuli. Hence experts' superior memory performance must be mediated by knowledge about the domain,knowledge that enables them to encode meaningful relations
between the elements of the stimuli.
The second general finding is that expert performers haveacquired skills that enable them to circumvent general memory
and processing limits. Chase and Simon (1973) originally attributed experts' superior memory to chunking in short-term memory. This account has been revised, and the exceptional memory of experts has been shown to reflect rapid storage in longterm memory (Charness, 1976; Frey & Adesman, 1976; Lane &Robertson, 1979). Building on Chase and Ericsson's (1982)
skilled memory theory, Ericsson and Staszewski (1989) concluded that experts acquire memory skill enabling them to rapidly access relevant information in an extended working memory that relies on storage in long-term memory. This acquired
memory skill underlies experts' superior ability to plan andevaluate potential sequences of moves in chess (Charness, 1981,1989), sequences of card exchanges in bridge (Charness, 1989),
and alternative diagnoses in medicine (Patel & Groen, 1991).
The most important implication of these acquired memory
skills is that they enable experts to circumvent the limited storage capacity of short-term memory. Thus these skills eliminate
any restrictive influence of individual differences in this basic
capacity (Ericsson & Smith, 1991b).
In tasks involving motor performance, experts can similarly
circumvent basic limits of sequential processes (Salthouse,1991). It is plausible that after extended practice, the ultimate
reaction time on a simple task depends on the speed of theneural and motor components of the response process in a
simple reaction. However, individual differences in simple reaction time are essentially unrelated to expert performance(Starkes & Deakin, 1984). Furthermore, the speed of motor
processes is faster than would be expected from a sequence ofsimple reactions. Expert typists can type at great speed because
they prepare several typing responses in advance of the next
typing response, a finding which Gentner (1988) documented
by high-speed filming of experts' finger movements on the keyboard. Monitoring of expert typists' eye fixations reveals thatthey look ahead in the text to be typed, and the extent to which
they do so is strongly correlated with their typing speed(Butsch, 1932). Experimental manipulations of the number ofcharacters that are displayed in advance (preview) show that acertain preview is necessary for maximal typing speed. Reduction of preview below that amount decreases typing speed, andwithout preview, expert typists type at speeds comparable tothose of novices (Salthouse, 1984). Experts' typing speed becomes constrained by several new factors, such as the need touse the same finger in consecutive key strokes and independence of movements between and within hands. Similarly,
when expert pianists prepare a musical piece for public performance, they spend considerable time determining how to hit

397

keys with different fingers and thereby minimize such constraints on movement.
The ability to anticipate future events and thus prepare actions in advance is critical in many domains of expertise, particularly in sports. Abernathy and Russel (1987) showed tennis
players pictures of an opponent in different phases of preparing
to serve. They found that with increasing levels of expertise,tennis players can use advance cues, such as location of arms
and racquet, to predict where the tennis ball will hit in theservice area. Shown pictures of an attacking field-hockey
player preparing a shot, national-level field-hockey players canpredict where the ball will go even before the attacking player's
club has made contact with the ball (Starkes, 1987). The important implication of this research is that experts can circumvent
any basic limits on the serial motor processes constraining anovice by using advance cues to prepare movements.
In summary, research on skill acquisition indicates that performance in the initial phases of practice is determined by characteristics quite different from those that determine performance during later phases. Considering that expert performance is acquired during a decade of intense preparation, theevidence suggests that relevant practice activities during development lead to far greater changes in basic perceptual and motor abilities than previously thought. What distinguishes expert
performers is mostly more and better organized knowledge,
which had to have been acquired. Most important, recent research on expertise shows that experts can acquire cognitive
skills enabling them to circumvent the limits of short-term
memory capacity and serial reaction time. This research rulesout the hypothesis that individual differences in those functions will influence and constrain final adult performance andis consistent with the low predictability of performance by ability tests after extended relevant experience (Hulin et al., 1990).
Finally, because the criteria for expert performance in mostdomains change as a function of age and level of performance,
it appears unlikely that the study of early performance will
reveal fixed elements that determine the level of final adultperformance.
The Role of Perceived Talent, Motivation, andPredisposition for Practice
From our search for immutable characteristics corresponding to innate talent, we conclude that individuals acquire virtually all of the distinguishing characteristics of expert performers through relevant activities (deliberate practice). At least
one characteristic, height, cannot be acquired. However, evenheight is imperfectly related to expert performance, and adultheight has a correlation of only around 0.8 with height at ages
younger than 17 to 18 (Malina & Bouchard, 1991), when decisions to start practice are made. Apparently no valid information on innate talent is available during an individual's initial
exposure to the domain. In spite of this, assessments of talentand decisions to initiate deliberate practice are as a rule madeduring this period (Bloom, 1985b). The perception that a childis talented is unquestionably real, and such perceptions motivate parents to provide the time and money to support deliberate practice as well as to encourage their children in a particulardomain. In the normal case (Bloom, 1985b), the child enjoys

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K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

the activities in the domain and is superior in these activities toother children of the same age in the same neighborhood.
Whether enjoyment precedes superior performance or viceversa is not known. In either case, perceived talent and enjoyment of the activities of a domain are ideal preconditions for
initiating the effortful but valuable activity of deliberate practice. Our framework differs from a view that is based on innate
talent in that we emphasize the motivation and enjoyment necessary to start and maintain deliberate practice and the motivation of parents and coaches to support the individuals without
assuming that the initial superior performance reflects immutable characteristics (innate talent).
In this section we show that our framework not only explains
the facts but also gives a better account of them than a framework that is based on innate talent. First, we examine detailed
descriptions of observed talent (Scheinfeld, 1939), and we thenargue that expert performers' familial relations can be accounted for by shared environment. The central argument isfirst that the perception that an individual is talented, that is,
innately equipped and predestined for success in a domain,
leads to the early start of deliberate practice. Second, the individual attains an elite level of adult performance by maintaining a high level of practice. Note that the perception of innate
talents will be relatively immune to disconfirming evidence solong as the talents are kept general and unspecified. As a resultsuch a perception can continue to bolster an individual
throughout his or her development.
The classic studies of innate talent emphasized that talent isobserved very early before the start of deliberate practice.
Scheinfeld (1939) found that the age at which talent is first
noticed is quite young for truly outstanding musicians—anaverage of 4.9 years of age. Scheinfeld's descriptions suggestthat "talent" means promise rather than objective evidence of
unusual capacity. For example, "unusual response to music" atage 3 (p. 238) and "playing violin with two sticks" at age 4 (p.
239) would not be impressive in children at older ages. Examples of talent for the oldest ages (6-7 years) in Scheinfeld's review nearly always involve absolute pitch. These accounts are
consistent with Bloom's (1985b) interviews with parents andteachers of international-level performers; Bloom found thatthe level of talent exhibited by these individuals was only unusual compared with that of other children of a similar age in
the immediate environment. We find this evidence more consistent with demonstrated interest and enjoyment of a domain
than with any superior, innate advantage involving fixed capacities.
To identify these early expressions of interest it is critical that
adults closely observe their children and are willing to support
this interest and provide access to deliberate practice. The importance of the early environment is clearly evident in our finding that children who become elite performers are first exposed
to a domain and start practice at remarkably young ages. At
these young ages it is more plausible that parents' perception of
innate talent, not objective evidence, leads to the start of practice. In fact, evidence of talent does not precede most instancesof very early start of practice. Many parents of precocious children were convinced of the great importance of very early systematic training and attribute the remarkable abilities of theirchildren to the training and not to inherent talent. Howe (1990)

reviewed the education of John Stuart Mill, Norbert Wiener,and William Sidis. An outstanding feature of these early educational efforts was the total elimination of inherently enjoyable
activities such as play and social interaction with other children.
This feature is consistent with our assertion that deliberate
practice is not inherently enjoyable. More recently, a Hungarian
educator, Polgar, announced a similar educational experimentwith his daughters involving early and focused training in chess(J. Radford, 1990). All three daughters developed into highly
skilled chess players (ranked first, second, and sixth in theworld among women chess players in 1992) and the youngest
daughter, Judith, recently became the youngest grand masterever in chess (McFadden, 1992). Given the biological relation
between parent and children, these cases clearly do not rule out
hereditary influences, but they do show that the level of performance can be dramatically accelerated through systematictraining initiated prior to evidence of talent.
Better evidence for our framework would go beyond showing
improvement from practice without knowledge of talent andshow that individuals with negative talent, for example, a disability, have attained great performance through practice. No
theory of expert performance would give individuals with disabilities an advantage or even opportunity compared with normal individuals. Individuals with disabilities have neverthelessattained international-level performance and even won Olympic medals. The gold medal winner at Melbourne in hammer
throwing was born with a paralyzed left arm and devised new
training techniques to overcome the disadvantage of his disability (Jokl, 1958). The first female to win three Olympic gold
medals in the same games, Wilma Rudolph, lost the use of her
left leg at the age of 4 and after intense treatment and practice
was able to walk without braces and reinforced shoes by age 11(Ladd, 1988). In these cases subnormal performance seems tohave motivated the individuals' start to deliberate practice as ameans of reaching normal functioning and then to continue
practice to reach elite levels. Several athletes have experienced
severe injuries, but were able to overcome these disabilities andwin Olympic medals for their performance (Jokl, 1964). One
suffered amputation of the arm used to hold the pistol in shooting. Another, a rider, contracted polio and lost control of herlegs. These examples indicate that training can compensate fordisabilities and has a greater impact than often believed
possible.
The fact that children who later attain expert performance
share their early environment with their parents would seem asatisfactory explanation of familial relations to expert performance. The most often cited examples of families of giftedmusicians are from early music, Johann Sebastian Bach's family
tree being the most striking (Rowley, 1988; Scheinfeld, 1939). In
those times before the advent of professional music teachers,
the transmission of knowledge and skills from parent to child
was natural and did not presuppose any genetic transmission of
innate talent. Similarly, nobody would argue that bilingual children who speak a foreign language have innate abilities forspeaking that particular language. Obviously they have acquired that language through social interaction with their parents or grandparents. Similarly, it is likely that in many cases
parents transmit to their children a substantial amount ofknowledge and motivation in skilled activities in a domain. In a

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THE ROLE OF DELIBERATE PRACTICE
recent study in behavioral genetics, Coon and Carey (1989)
compared the music performance of identical and fraternal
twins and found that the environmental correlations were always higher than the genetic ones. (Whether the same findings
would emerge if the study were restricted to expert musicalperformance is unknown; given the low frequency of expert
musicians, an appropriate study of twins would be nearly impossible to conduct.) Similarly, de Garay, Levine, and Carter(1974) interviewed more than 1,200 athletes attending the 1968
Olympic games in Mexico City and found no meaningful familial resemblance in reported physical or motor abilities between
these athletes and their families compared with a referencegroup.
In summary, our review has uncovered essentially no support
for fixed innate characteristics that would correspond to general or specific natural ability and, in fact, has uncovered findings inconsistent with such models. At the same time we recognize that parents and teachers who perceive talent in their children and pupils are motivated to provide them with instruction
and social support. We also recognize that being told by parents
and teachers that they are talented, that is, genetically endowedwith unusual gifts, most likely increases motivation, boosts
self-confidence, and protects young performers against doubts
about eventual success during the ups and downs of the extended preparation. A famous violin teacher, Galamian (1962),
discusses the importance of giving praise to build self-confidence, but warns against too much praise as it causes "them torelax their efforts (p. 106)." Too much recognition at young ages
may lead young musicians to consider themselves as special
individuals—not just musicians—deserving of treatment as
prima donnas in all aspects of everyday life (Gelber, 1990).
Research in social psychology on interpersonal expectationand self-fulfilling prophesies confirms these effects in the laboratory and in everyday settings (Darley & Fazio, 1980; Rosenthal & Rubin, 1978). The important influence of parents'
expectations on their children's performance, interest, and selfjudgments of ability in a domain has been demonstrated forlarge random samples in the general population. Children's andadolescents' perception of their own ability in mathematics is
influenced by their parents' beliefs about their abilities, evenwhen past performance and effort are statistically controlledfor (Parsons, Adler, & Kaczala, 1982). The parents' beliefs ingender differences in talent in mathematics and English influence their perception of their children's abilities more than iswarranted given the objective differences in performance between boys and girls for these two subjects (Eccles, Jacobs &Harold, 1990). Recent studies have uncovered pathways bywhich the parents' beliefs influence children's beliefs in theirown abilities as well as their performance. Harold, Eccles,
Yoon, Aberbach, and Freedman-Doan (1991) have shown how
the child's gender influences the parents' perception of thechild's ability in sports and music, which in turn influences thefrequency of opportunities for relevant activities provided byparents for their children in the corresponding domain. Eccles
and Harold (1991) have linked the influence of gender on thechild's self-concept in English, mathematics, and sports and theinfluence of self-concept on how much free time is spent on
activities in the corresponding domain. Hence, parental beliefs
and expectations tan influence the children's relevant experi-

ences directly by offering opportunities or indirectly bystrengthening motivation and self-confidence for a given activity. In addition, laboratory studies, where amount of experienceis equated, show that implicit theories of stability of abilities are
an important aspect of individuals' self-concept and greatly influence future learning goals and reactions to failure (Dweck &Leggett,1988).
Returning to Galton's framework, we reject any importantrole for innate ability. It is quite plausible, however, that heritable individual differences might influence processes related tomotivation and the original enjoyment of the activities in thedomain and, even more important, affect the inevitable differences in the capacity to engage in hard work (deliberate practice). In this review we have already pointed out the motivational problems associated with persuading adults to start andmaintain exercise programs and with getting children to startand maintain deliberate practice. Individual differences inemotionality and general level of activity are also likely influences on the capacity to engage in sustained practice as well ason the preference or dislike for this type of isolated activity.
Moderate heritabilities have been estimated for these differences (Plomin et al., 1990) and for self-reported interest in especially artistic activities (Grotevant, Scarr, & Weinberg, 1977).
Although we are not aware of any controlled human studies
relating activity levels and emotionality to deliberate practiceand attained level of expert performance, the relation between
productivity and eminence (Simonton, 1984) is at least consistent with such a relation. In addition, Cox (1926) estimated IQ
from early achievements documented in biographies of thehundred most eminent men of recent centuries but concluded
that "high but not the highest intelligence, combined with thegreatest degree of persistence, will achieve greater eminence
than the highest degree of intelligence with somewhat less persistence" (p. 187). The pattern of results from animal studies isremarkably consistent with the importance of such relations
and interesting from an evolutionary perspective. Early behavioral geneticists were able to selectively breed strains of rats that
performed differently on specific learning tasks (McClearn,1962). Contrary to expectation, the superior learning ability ofthese rats was specific to the parameters of the task, such as
types of relevant cues (visual vs. spatial) and types of motivation(hunger vs. escape from water). Furthermore, "bright" and"dull" rats differed in either emotionality or activity or both
(McClearn, 1962). In a classic study, Scott and Fuller (1965)
examined the characteristics and test performance of several
breeds of dogs and found that the only general factor was emotion. Rather than viewing the emotional and activity factors as
variables confounding pure learning factors, K. J. Hayes (1962)
proposed viewing them as integral and necessary prerequisites
for learning and acquired skill in animals as well as humans.
Future research will tell whether individual differences in factors related to individuals' motivation to practice can accountfor any heritable influences in attained levels of performance.
Conclusion
People believe that because expert performance is qualitatively different from normal performance the expert performer
must be endowed with characteristics qualitatively different

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K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

from those of normal adults. This view has discouraged scientists from systematically examining expert performers and accounting for their performance in terms of the laws and principles of general psychology. We agree that expert performance isqualitatively different from normal performance and even thatexpert performers have characteristics and abilities that are
qualitatively different from or at least outside the range of thoseof normal adults. However, we deny that these differences are
immutable, that is, due to innate talent. Only a few exceptions,most notably height, are genetically prescribed. Instead, we
argue that the differences between expert performers and normal adults reflect a life-long period of deliberate effort to improve performance in a specific domain.
Most of our scientific knowledge about improvement andchange comes from laboratory studies of training and practicethat lasted hours, days, and occasionally weeks and months. In
addition, there is a growing body of data on the heritabilities ofvarious abilities and characteristics estimated for twins andparents and their offspring sampled from the general population (Plomin et al., 1990). Although behavioral geneticists carefully point out that their heritability estimates are valid only forthe limited range of practice and skill in the normal environment of the adults studied, it is often incorrectly assumed by lay
people that these estimates can be directly extended to extreme
manipulations of environmental conditions, such as extended
deliberate practice. Most important, the effects of short-term
training cannot be readily extended to the effects of orders ofmagnitude more practice.
A promising direction for research on the effects of extended
activities is to identify activities relevant to some goal and toassess the amount of time individuals allocate to these activities. Recent research has shown that the amount of time individuals spend reading as assessed by diaries is related to memory
for prose even when education and vocabulary are partialed out(Rice, Meyer, & Miller, 1988). The estimated amount of reading is also related to reading ability and, most interestingly,
increases in reading ability (R. C. Anderson, Wilson, & Fielding, 1988). Research on physical fitness has a long tradition of
measuring daily physical activity and exercise, and we havecited the study in which Fagard et al. (1991) assessed the influence of both genetic factors and regular activity on aerobic andanaerobic abilities. It would be ideal to plot the interaction ofgenetic and environmental factors in longitudinal studies
across the entire life span (Rutter, 1989). Within this context,
we view the study of elite performers as particularly interesting
because from early ages their lives appear to maximize theinfluence of environmental activities (deliberate practice) improving a specific type of performance. In a rare study
Schneider, Bos, and Rieder (1993) included environmental factors along with physical characteristics and motivational characteristics of individuals in a longitudinal study of elite tennis
players. Consistent with our framework they found that tennis
performance at ages 11 and 17 was primarily determined byparental support and in particular motivation and tennis-specific skills, where the level of these skills in turn are mainly attributable to assessed levels of motivation and concentration.
We view elite performance as the product of a decade or moreof maximal efforts to improve performance in a domain
through an optimal distribution of deliberate practice. Thisview provides us with unique insights into the potential for andlimits to modifying the human body and mind. Many anatomical characteristics, traditionally believed to be fixed, can adapt
and change in response to intense practice sustained for years.
Substantial change and learning can occur even during childhood, when some changes, such as in certain perceptual-motor
abilities, might be even easier to attain than during adulthood.
Untrained adults can overcome limits on speed and processing
capacity by acquiring new cognitive skills that circumvent theselimits by qualitatively different processes. Further research on
the capacities and characteristics of expert performance will
give us a much deeper understanding of the full range of possible adaptations and methods for circumventing limits (Ericsson& Smith, 1991a).
It does not follow from the rejection of innate limits on acquired performance that everyone can easily attain high levelsof skill. Contemporary elite performers have overcome a number of constraints. They have obtained early access to instructors, maintained high levels of deliberate practice throughout
development, received continued parental and environmental
support, and avoided disease and injury. When one considers in
addition the prerequisite motivation necessary to engage in deliberate practice every day for years and decades, when mostchildren and adolescents of similar ages engage in play andleisure, the real constraints on the acquisition of expert performance become apparent. The commitment to deliberate practice distinguishes the expert performer from the vast majorityof children and adults who seem to have remarkable difficulty
meeting the much lower demands on practice in schools, adulteducation, and in physical exercise programs.
We believe that a more careful analysis of the lives of future
elite performers will tell us how motivation is promoted andsustained. It is also entirely plausible that such a detailed analysis will reveal environmental conditions as well as heritable
individual differences that predispose individuals to engage indeliberate practice during extended periods and facilitate motivating them. Our empirical studies have already shown thatexperts carefully schedule deliberate practice and limit its duration to avoid exhaustion and burnout. By viewing expert performers not simply as domain-specific experts but as experts inmaintaining high levels of practice and improving performance, we are likely to uncover valuable information about the
optimal conditions for learning and education.
References
Abernathy, B., & Russel, D. G. (1987). Expert-novice differences in an
applied selective attention task. Journal of Sport Psychology, 9, 326345.
Ackerman, P. L. (1988). Determinants of individual differences during
skill acquisition: Cognitive abilities and information processing.
Journal of Experimental Psychology: General, 117, 288-318.
Anderson, J. R. (1982). Acquisition of cognitive skill. Psychological
Review, 89, 369-406.
Anderson, R. G, Wilson, P. T., & Fielding, L. G. (1988). Growth inreading and how children spend their time outside of school. Reading Research Quarterly, 23, 285-303.
Arai, T. (1912). Mental Fatigue. (Report No. 54). New York: Teachers
College, Columbia University Contributions to Education.
Aschaffenburg, G. (1896). Praktische Arbeit unter Alkoholwirking

THE ROLE OF DELIBERATE PRACTICE[Work under the influence of alcohol]. Psychologische Arbeit, 1,
608-626.
Ashworth, C. A. (1992). Skill as the fit between performer resources
and task demands. In The Proceeding of the Fourteenth Annual Cognitive Science Meeting, (pp. 444-449). Hillsdale, NJ: Erlbaum.
Auer, L. (1921). Violin playing as I teach it. New York: Stokes.
Babkin, B. P. (1949). Pavlov: A biography. Chicago: University of Chicago Press.
Baddeley, A. D., & Longman, D. J. A. (1978). The influence of lengthand frequency of training session on the rate of learning to type.
Ergonomics, 21, 627-635.
Bahrick, H. P. (1984). Semantic memory content in permastore: 50
years of memory for Spanish learned in school. Journal of Experimental Psychology: General, 113, 1-29.
Bahrick, H. P., & Hall, L. K. (1991). Lifetime maintenance of highschool mathematics content. Journal of Experimental Psychology:
General, 120, 20-33.
Bailey, D. A., & Martin, A. D. (1988). The growing child and sport:
Physiological considerations. In F. L. Smoll, R. A. Magill, & M. J.
Ash (Eds.), Children in sport (pp. 103-117). Champaign, IL: Human
Kinetics Books.
Baird, L. L. (1985). Do grades and tests predict adult accomplishment?
Research in Higher Education, 23, 3-85.
Baltes, P. B., & Kliegl, R. (1992). Further testing of limits of cognitive
plasticity: Negative age differences in a mnemonic skill are robust.
Developmental Psychology, 28, 121-125.
Bamberger, J. (1986). Cognitive issues in the development of musically
gifted children. In R. J. Sternberg & J. E. Davidson (Eds.), Conceptions of giftedness (pp. 388-413). Cambridge, England: Cambridge
University Press.
Barlow, F. (1952). Mental prodigies. New York: Greenwood Press.
Black, J. E., Isaacs, K. R., Anderson, B. J., Alcantara, A. A., & Greenough, W. T. (1990). Learning causes synaptogenesis, whereas motor
activity causes angiogenesis, in cerebellar cortex of adult rats. Proceedings of the National Academy of Science, 87, 5568-5572.
Bloom, B. S. (1984). The 2 sigma problem. The search for methods ofgroup instruction as effective as one-to-one tutoring. Educational
Researcher, 13, 3-16.
Bloom, B. S. (Ed.), (1985a). Developing talent in young people. New
York: Ballantine Books.
Bloom, B. S. (1985b). Generalizations about talent development. In
B. S. Bloom (ed.), Developing talent in young people (pp. 507-549).
New York: Ballantine Books.
Book, W F. (1924). Voluntary motor ability of the world's champion
typists. Journal of Applied Psychology, 8, 283-308.
Book, W. F. (1925a). Learning to typewrite. New York: Gregg.
Book, W. F. (1925b). The psychology of skill. New York: Gregg.
Book, W F, & Norvell, L. (1922). The will to learn: An experimental
study of incentives in learning. Pedagogical Seminary, 29(A), 305362.
Booth, F. W. (1989). Physical activity as a stimulus to changes in gene
expression in skeletal muscle. In R. S. Williams & A. G. Wallace(Eds.), Biological effects of physical activity (pp. 91-104). Champaign, IL: Human Kinetics Books.
Bouchard, C. (1986). Genetics of aerobic power and capacity. In R. M.
Malina & C. Bouchard (Eds.), Sport and human genetics (pp. 59-88).
Champaign, IL: Human Kinetics Books.
Bower, G. H., & Hilgard, E. R. (1981). Theories of learning (5th ed.).
Englewood Cliffs, NJ: Prentice Hall.
Brady, F. (1973). Bobby Fischer: Profile of a prodigy. New York: Dover.
Brady, P. T. (1970). The genesis of absolute pitch. Journal of the Acoustical Society of America, 48, 883-887.
Brown, M. A., & Mahoney, M. J. (1984). Sport psychology. Annual
Review of Psychology, 35, 605-625.

401

Bruner, J. (1983). In search of mind. New York: Harper & Row.
Bryan, W L., & Harter, N. (1897). Studies in the physiology and psychology of the telegraphic language. Psychological Review, 4, 27-53.
Bryan, W L., & Harter, N. (1899). Studies on the telegraphic language.
The acquisition of a hierarchy of habits. Psychological Review, 6,345-375.
Burke, E. R., Faria, I. E., & White, J. A. (1990). Cycling. In T. Reilly, N.
Secher, P. Snell, & C. Williams (Eds.), Physiology of sports (pp. 173213). London: E. & F. N. Spon.
Butsch, R. L. C. (1932). Eye movements and the eye-hand span in
typewriting. Journal of Educational Psychology, 23, 104-121.
Caldron, P. H., Calabrese, L. H., Clough, J. D, Lederman, R. J., Williams, G., & Lederman, J. (1986). A survey of musculoskeletal problems encountered in high-level musicians. Medical Problems of Performing Artists, I, 136-139.
Carter, J. E. L., Ross, W D., Aubrey, S. P., Hebbelinck, M., & Borms, J.
(1982). Anthropometry of Montreal Olympic athletes. In J. E. L.
Carter (Ed.), Physical structure of Olympic athletes: Part I(pp. 25-52).
Basel, Switzerland: Karger.
Ceci, S. J. (1990). On intelligence . . . more or less: A bio-ecologicaltheory of intellectual development. Englewood Cliffs, NJ: PrenticeHall.
Chambliss, D. F. (1988). Champions: The making ofOlympic swimmers.
New \brk: Morrow.
Chambliss, D. F. (1989). The mundanity of excellence: An ethnographic report on stratification and Olympic swimmers. Sociological Theory, 7, 70-86.
Charness, N. (1976). Memory for chess positions: Resistance to interference. Journal of Experimental Psychology: Human Learning andMemory, 2,641-653.
Charness, N. (1981). Search in chess: Age and skill differences. Journalof Experimental Psychology: Human Perception and Performance, 7,467-476.
Charness, N. (1989). Expertise in chess and bridge. In D. Klahr & K.
Kotovsky (Eds.), Complex information processing: Theimpact of Herbert A. Simon (pp. 183-208). Hillsdale, NJ: Erlbaum.
Charness, N. (1991). Expertise in chess: The balance between knowledge and search. In K. A. Ericsson & J. Smith (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 39-63). Cambridge,
England: Cambridge University Press.
Charness, N., Clifton, X, & MacDonald, L. (1988). Case study of amusical "monosavant: A cognitive-psychological focus. In I. K.
Obler & D. Fein (Eds.), The exceptional brain: Neuropsychology oftalent and special abilities (pp. 277-293). New York: Guilford Press.
Chase, W G., & Ericsson, K. A. (1981). Skilled memory. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 141-189). Hillsdale, NJ: Erlbaum.
Chase, W G, & Ericsson, K. A. (1982). Skill and working memory. In
G. H. Bower (Ed.), The psychology of learning and motivation (Vol.
16, pp. 1-58). San Diego, CA: Academic Press.
Chase, W G., & Simon, H. A. (1973). The mind's eye in chess. In W G.
Chase (Ed.). Visual information processing (pp. 215-281). San Diego,
CA: Academic Press.
Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds.). (1988). The nature ofexpertise. Hillsdale, NJ: Erlbaum.
Chi, M. T. H., Glaser, R., & Rees, E. (1982). Expertise in problem
solving. In R. S. Sternberg (Ed.). Advances in the psychology of human intelligence (Vol. 1, pp. 1-75). Hillsdale, NJ: Erlbaum.
Clem, J. E. (1955). Techniques of teaching typewriting (2nd ed.) New
York: McGraw-Hill.
Cohen, A. J., & Baird, K. (1990). Acquisition of absolute pitch: The
question of critical periods. Psychomusicology, 9, 31-37.
Coleman, R. M. (1986). Wide awake at 3:00 a.m.: By choice or bychance. New York: Freeman.

402

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

Converse, P. E. (1972). Country differences in time use. In A. Szalai(Ed.), The use of time: Daily activities of urban and suburban populations in twelve countries (pp. 113-144). The Hague, The Netherlands:
Mouton.
Coon, H., & Carey, G. (1989). Genetic and environmental determinantsof musical ability in twins. Behavior Genetics, 19, 183-193.
Costall, A., (1985). The relativity of absolute pitch. In P. Howell, I.
Cross, & R. West (Eds.), Musical structure and cognition, (pp. 189208). San Diego, CA: Academic Press.
Costill, D. L., Flynn, M. G., Kirwan, J. P., Houmard, J. A., Mitchell,
J. B., Thomas, R., & Park, S. H. (1988). Effects of repeated days ofintensified training on muscle glycogen and swimming performance. Medicine and Science in Sports and Exercise, 20, 249-254.
Cowley, M. (Ed.). (1959). Writers at work: The Paris review interviews.
New York: Viking Press.
Cox, C. M. (1926). Genetic studies of genius, Vol. II. Stanford: Stanford
University Press.
Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper & Row.
Darley, J. M., & Fazio, R. H. (1980). Expectancy confirmation processes arising in the social interaction sequence. American Psychologist, 35, 867-881.
Darwin, F. (1888). (Ed.). The life and letters of Charles Darwin, Vol. I.
London: John Murray.
de Garay, A. L., Levine, L., & Carter, J. E. L. (1974). Genetic and anthropological studies of Olympic athletes. San Diego, CA: Academic
Press.
DiTullio, M., Wilczek, L., Paulus, D., Kinakatis, A., Pollack, M., &Eisenhardt, J. (1989). Comparison of hip rotation in female classicalballet dancers versus female nondancers. Medical Problems in Performing Artists, 4, 154-158.
Doll, J., & Mayr, U. (1987). Intelligenz und Schachleistung—eine Untersuchung an Schachexperten. [Intelligence and achievement inchess—a study of chess masters]. Psychologische Beitrage, 29, 270289.
Dvorak, A., Merrick, N. L., Dealey, W L., & Ford, G. C. (1936).
Typewriting behavior. New York: American Book.
Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach tomotivation and personality. Psychological Review, 95, 256-273.
Eby, F, & Arrowood, C. F. (1940). The history and philosophy of education: Ancient and medieval. Englewood Cliffs, NJ: Prentice Hall.
Eccles, J. S., & Harold, R. D. (1991). Genderdifferences in sport involvement: Applying the Eccles' expectancy-value model. Journal of Applied Sport Psychology, 3, 7-35.
Eccles, J. S., Jacobs, J. E., & Harold, R. (1990). Gender role stereotypes,
expectancy effects, and parents' socialization of gender differences.
Journal of Social Issues, 46. 183-201.
Elo, A. E. (1978). The rating of chessplayers, past and present. London:
Batsford.
Elovianio, R., & Sundberg, S. (1983). A five-year follow-up study on
cardio-respiratory function in adolescent elite endurance runners.
Ada Paedialrica Scandinavia, 72, 357-360.
Ericsson, K. A. (1985). Memory skill. Canadian Journal of Psychology,
39, 188-231.
Ericsson, JC. A. (1988). Analysis of memory performance in terms ofmemory skill. In R. J. Sternberg (Ed.), Advances in the psychology ofhuman intelligence (pp. 137-179). Vol. 4, Hillsdale, NJ: Erlbaum.
Ericsson, K. A. (1990). Peak performance and age: An examination ofpeak performance in sports. In P. B. Baltes & M. M. Baltes (Eds.),
Successful aging: Perspectives from the behavioral sciences (pp. 164195). Cambridge, England: Cambridge University Press.
Ericsson, K. A., & Faivre, I. A. (1988). What's exceptional about exceptional abilities? In I. K. Obler& D. Fein (Eds.), The exceptional brain:

Neuropsychology of talent and special abilities (pp. 436-473). New
York: Guilford Press.
Ericsson, K. A., & Simon. H. A. (1984). Protocol analysis: Verbal reports
as data. Cambridge, MA: MIT Press.
Ericsson, K. A., & Smith, J. (Eds.). (1991a). Toward a general theory ofexpertise: Prospects and limits. Cambridge, England: Cambridge University Press.
Ericsson, K. A., & Smith, J. (1991 b). Prospects and limits of the empirical study of expertise: An introduction. In K. A. Ericsson & J. Smith(Eds.), Toward a general theory of expertise: Prospects and limits (pp.
1-39). Cambridge, England: Cambridge University Press.
Ericsson, K. A., & Staszewski. J. (1989). Skilled memory and expertise:
Mechanisms of exceptional performance. In D. Klahr & K. Kotovsky (Eds.), Complex information processing: The impact of Herbert
A. Simon (pp. 235-267). Hillsdale, NJ: Erlbaum.
Ericsson, K. A.. Tesch-Romer, C, & Krampe, R. (1990). The role ofpractice and motivation in the acquisition of expert-level performance in real life: An empirical evaluation of a theoretical framework. In M. J. A. Howe (Ed.), Encouraging the development of exceptional skills and talents (pp. 109-130). Leicester, England: The British Psychological Society.
Eriksson, B. O., Engstrom, I.. Karlberg, P., Saltin, B., & Thoren, C.
(1971). A physiological analysis of former girl swimmers. Acta Paedialrica Scandinavia, (Suppl. 217), 68-72.
Fagard, R., Bielen, E.. & Amery, A. (1991). Heritability of aerobic
power and anaerobic energy generation during exercise. Journal ofApplied Physiology 70. 357-362.
Farr, M. J. (1987). The long-term retention of knowledge and skills: A
cognitive and instructional perspective. New York: Springer-Verlag.
Feltovich, P. J., Johnson, P. E.. Moller, J. H., & Swanson, D. B. (1984).
LCS: The role and development of medical knowledge in diagnostic
expertise. In W J. Clancey & E. H. Shortliffe (Eds.), Readings inmedical artificial intelligence (pp. 275-319). Reading, MA: Addison-Wesley.
Fitts, P. (1964). Perceptual-motor skill learning. In A. W Melton (Ed.),
Categories of human learning (pp. 243-285). San Diego, CA: Academic Press.
Fitts, P., & Posner, M. I. (1967). Human performance. Monterey, CA:
Brooks/Cole.
Folkard, S., & Monk, T. H. (1985). Circadian performance rhythms. In
S. Folkard &T. H. Monk(Eds), Hours of'work (pp. 37-52). New
York: Wiley.
French, K. E., & Thomas, J. R. (1987). The relation of knowledge development to children's basketball performance. Journal of Sport Psychology, 9, 15-32.
Frey, P. W, & Adesman, P. (1976). Recall memory for visually presented
chess positions. Memory and Cognition, 4, 541-547.
Fry, H. J. H. (1986). Incidence of overuse syndrome in symphony orchestra. Medical Problems of Performing Artists, 1, 51-55.
Gagne, R. M. (1970). The conditions of learning (2nd ed.). New York:
Holt, Rinehart & Winston.
Galamian, I. (1962). Principles of violin playing & teaching. Englewood
Cliffs, NJ: Prentice Hall.
Galton, F, Sir (1979). Hereditary genius: An inquiry into its laws andconsequences. London: Julian Friedman Publishers. (Originally published in 1869).
Gelber, G. S. (J990). Psychological issues encountered in gifted children and adolescents. In F. R. Wilson & F. L. Roehmann (Eds.),
Music and child development (pp. 271-274). St. Louis, MO: MMB
Music.
Gentner, D. R. (1988). Expertise in typewriting. In M. T. H. Chi, R.
Glaser, & M. J. Farr (Eds.), The nature of expertise (pp. 1 -21). Hillsdale, NJ: Erlbaum.

THE ROLE OF DELIBERATE PRACTICE
Getzels, J. W, & Csikszentmihalyi, M. (1976). The creative vision: Alongitudinal study of problem finding in art. New York: Wiley.
Ghiselli, E. (1966). The validity of occupational aptitude tests. New
York: Wiley.
Gibson, E. J. (1969). Principles of perceptual learning and development.
Englewood Cliffs, NJ: Prentice Hall.
Glover, B., & Schuder, P. (1988). The new competitive runners handbook. New York: Penguin Books.
Gottlieb, G. (1992). Individual development and evolution. New York:
Oxford University Press.
Greksa, L. P. (1988). Effects of altitude on the stature, chest depth, andforced vital capacity of low to high altitude migrant children of European ancestry. Human Biology, 60, 23-32.
Grotevant, H. D., Scarr, S., & Weinberg, R. A. (1977). Patterns of interest similarity in adoptive and biological families. Journal of Personality and Social Psychology, 35, 667-676.
Guilford, J. P. (1967). The nature of human intelligence. New York:
McGraw-Hill.
Gustin, W C. (1985). The development of exceptional research mathematicians. In B. S. Bloom (Ed), Developing talent in young people(pp. 270-331). New York: Ballantine Books.
Gruson, L. M. (1988). Rehearsal skill and musical competence: Doespractice make perfect? In J. A. Sloboda (Ed.), Generative processes inmusic: The psychology of performance, improvisation, and composition (pp. 91-112). Oxford, England: Clarendon Press.
Hackney, A. C, Pearman, S. N., & Novack, J. M. (1990). Physiological
profiles of overtrained and stale athletes: A review. Applied Sport
Psychology, 2, 21-30.
Hagan, R. D., Smith, M. G., & Gettman, L. R. (1981). Marathon performance in relation to maximal aerobic power and training indices.
Medicine and Science in Sports Exercise, 13,185-189.
Harold, R. D, Eccles, J. S., Yoon, K. S., Aberbach, A. J., & FreedmanDoan, C. (1991). Parents hold a key to "the land of opportunity" Paper
presented at the Biennial Meeting of the Society for Research inChild Development, Seattle, WA.
Harpur, R. P. (1980). The rat as a model for physical fitness studies.
Comparative Biochemistry and Physiology, 66A, 553-574.
Haskell, W L. (1989). Exercise as a means of maximizing human physical performance and productivity. In R. S. Williams & A. G. Wallace(Eds.), Biological effects of physical activity (pp. 115-126). Champaign, IL: Human Kinetics Books.
Hayes, J. R. (1981). The complete problem solver. Philadelphia, PA:
Franklin Institute Press.
Hayes, K. J. (1962). Genes, drives and intellect. Psychological Reports,
10, 299-342.
Heizmann, S., Krampe, R. Th., & Ericsson, K. A. (1993). Expertisedevelopment over the life-span: From the beginning of training to middleage. Unpublished manuscript, Institute ofCognitiveScience, University of Colorado at Boulder.
Henshaw, E. M., & Holman, P. G. (1930). A note on over-training. British Journal of Psychology, 20, 333-335.
Hill, L. B. (1934). A quarter century of delayed recall. Journal of Genetic Psychology, 44, 231-238.
Hill, L. B. (1957). A second quarter century of delayed recall or relearning at 80. Journal of Educational Psychology, 48, 65-68.
Hill, L. B., Rejall, A. E, & Thorndike, E. L. (1913). Practice in the case of typewriting. Pedagogical Seminary, 20, 516-529.
Hodgson, R., & Miller, P. (1982). Self watching addictions, habits, compulsions: What to do about them. New "fork: Facts on File.
Howald, H. (1982). Training-induced morphological and functionalchanges in skeletal muscle. International Journal of Sports Medicine,
3, 1-12.

403

Howe, M. J. A. (1990). The origins of exceptional abilities. Oxford, England: Basil Blackwell.
Hulin, C. L., Henry, R. A., & Noon, S. L. (1990). Adding a dimension:
Time as a factor in the generalizability of predictive relationships.
Psychological Bulletin, 107, 328-340.
Hunter, J. E., & Hunter, R. F. (1984). Validity and utility of alternative
predictors of job performance. Psychological Bulletin, 96, 72-98.
Huxtable, Z. L., White, M. H., & McCartor, M. A. (1946). A re-performance and re-interpretation of the Arai Experiment in mental fatigue with three subjects. Psychological Monographs, 59(5, Whole
No. 275).
Johnson, J. S., & Newport, E. L. (1989). Critical period effects in second language learning: The influence of maturational state on theacquisition of English as a second language. Cognitive Psychology,
21, 60-99.
Johnson, P. E., Duran, A. S., Hassebrock, F, Moller, J., Prietula, M.,
Feltovich, P. J., & Swanson, D. B. (1981). Expertise and error in diagnostic reasoning. Cognitive Science, 5, 235-283.
Jokl, E. (1958). The clinical physiology of physical fitness and rehabilitation. Springfield, IL: Charles C Thomas.
Jokl, E. (1964). The scope of exercise in rehabilitation. Springfield, IL:
Charles C Thomas.
Judd, T. (1988). The varieties of musical talent. In L. K. Obler & D.
Fein (Eds.), The exceptional brain: Neuropsychology of talent and special abilities (pp. 127-155). New York: Guilford Press.
Juster, F. T, & Stafford, F. P. (Eds). (1985). Time, goods and well-being.
Ann Arbor, Ml: Institute for Social Research, The University ofMichigan.
Kalinowski, A. G. (1985). The development of Olympic swimmers. In
B. S. Bloom (Ed.), Developing talent in young people (pp. 139-192).
New York: Ballantine Books.
Kaminski, G., Mayer, R., & Ruoff, B. A. (1984). Kinder und Jugendliche
im Leistungssport [Children and adolescents in high-performancesports]. Schorndorf, Federal Republic of Germany: Hofmann.
Kao, D.-L. (1937). Plateaus and the curve of learning in motor skill.
Psychological Monographs, 49(3, Whole No. 219).
Karpov, A., & Roshal, A. (1980). Anatoly Karpov: Chess is my life. Elmsford, NY: Pergamon Press.
Keele, S. W, & Hawkins, H. L. (1982). Explorations of individual differences relevant to high level skill. Journal of Motor Behavior, 14,
3-23.
Keller, F. S. (1958). The phantom plateau. Journal of the Experimental
Analysis of Behavior, 1, 1-13.
Kellogg, R. T. (1986). Writing method and productivity of science andengineering faculty. Research in Higher Education, 25, 147-163.
Kelso, J. A. S., Southard, D. L., &Goodman, D. (1979). On the coordination of two-handed movements. Journal of Experimental Psychology: Human Perception and Performance, 5, 229-238.
Klapp, S. T. (1979). Doing two things at once: The role of temporalcompatibility. Memory and Cognition, 7, 375-381.
Klausen, K. (1990). Strength and weight-training. In T. Reilly, N.
Secher, P. Snell, & C. Williams (Eds), Physiology of sports (pp. 41 67). London: E. & F. N. Spon.
Klemp, P., & Charlton, D. (1989). Articular mobility in ballet dancers:
A follow-up study after four years. The American Journal of Sports
Medicine, 77,72-75.
Kliegl, R., Smith, J., & Baltes, P. B. (1989). Testing-the-limits and thestudy of adult age differences in cognitive plasticity of a mnemonicskill. Developmental Psychology, 25, 247-256.
Kliegl, R., Smith, J., & Baltes, P. B. (1990). On the locus and process ofmagnification of age differences during mnemonic training. Developmental Psychology, 26, 894-904.

404

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER

Korchnoi, Y (1978). Chess is my life: Autobiography and games. New
York: Arco.

Krampe, R. T. (1991). Maintaining excellence: Cognitive-motor performance in pianists differing in age and skill level. Unpublished doctoral dissertation, Max Planck Institute for Human Development
and Education, Berlin, Federal Republic of Germany.
Krogius, N. (1976). Psychology in chess. New York: RHM Press.
Ladd, T. (1988). Rudolph, Wilma Glodean. In D. L. Porter (Ed.), Biographical dictionary of American sports: Outdoor sports (pp. 525526). New York: Greenwood Press.
Lamb, D. R. (1984). Physiology of exercise. New York: MacMillan.
Lane, D. M., & Robertson, L. (1979). The generality of levels-of-processing hypothesis: An application to memory for chess positions.
Memory and Cognition, 7, 253-256.
Lashley, K. S. (1951). The problem of serial order in behavior. In L. A.
Jeffress (Ed.), Cerebral mechanisms in behavior (pp. 112-136). New
York: Wiley.
Lehman, H. C. (1953). Age and achievement. Princeton, NJ: Princeton
University Press.
Lesgoid, A. M. (1984). Acquiring expertise. In J. R. Anderson &S. M.
Kosslyn (Eds.), Tutorials in learning and memory: Essays in honor of
Gordon Bower (pp. 31-60). New York: Freeman.
Linn, R. (1982). Ability testing: Individual differences, prediction anddifferential prediction. In A. K. Wigdor& W. R. Garner(Eds.), Ability testing: Uses, consequences, and controversies, Part 11: Documentation Section (pp. 335-388). Washington, DC: National Academy
Press.
MacLaren, D. (1990). Court games: Volleyball and basketball. In T.
Reilly, N. Secher, P. Snell, & C Williams (Eds.), Physiology of sports(pp. 427-464). London: E. & F. N. Spon.
Malina, R. M., & Bouchard, C. (1991). Growth, maturation and physicalactivity. Champaign, IL: Human Kinetics Books.
Manturzewska, M. (1990). A biographical study of the iife-span development of professional musicians. Psychology of Music, 18,112-139.
Martin, J. E., & Dubbert, P. M. (1985). Adherence to exercise. Exercise
and Sport Sciences Review, 13, 137-167.
Maughan, R. J. (1990). Marathon running. In T. Reilly, N. Secher, P.
Snell, & C. Williams (Eds.), Physiology of sports (pp. 121-152). London: E. & F. N. Spon.
Mayr, U. (1989). Personal communication of unpublished data from astudy by J. Doll and U. Mayr (1987). Intelligenz and Schachleistung—eine Untersuchung an Schachexperten [Intelligence and achievement—a study of chess masters]. Psychologische Beitrdge, 29, 270289.
McClearn, G. E. (1962). The inheritance of behavior. In L. Postman(Ed.), Psychology in the making: Histories of selected research problems (pp. 144-252). New York: Knopf.
McFadden, R. D. (1992, February 4). Youngest grandmaster ever is 15,
ferocious (and female). The New York Times, p. Al.
McKenzie, C. L., Nelson-Schulz, J. A., & Wills, B. L. (1983). A preliminary investigation of motor programming in piano performance as afunction of skill level. In D. R. Rogers & J. A. Sloboda (Eds.), The
acquisition of symbolic skills (pp. 283-292). New Vbrk: Plenum
Press.
Miklaszewski, K. (1989). A case study of a pianist preparing a musicalperformance. Psychology of Music, 17, 95-109.
Miyazaki, K. (1990). The speed of musical pitch identification by absolute-pitch possessors. Music Perception, 8, 177-188.
Monsaas, J. A. (1985). Learning to be a world-class tennis player. In
B. S. Bloom (Ed.), Developing talent in young people (pp. 211 -269).
New York: Ballantine Books.
Murray, P. (1989). Poetic genius and its classical origin. In R Murray(Ed.), Genius: The history of an idea (pp. 9-31). Oxford, England:
Basil Blackwell.

Newell, A., & Rosenbloom, P. S. (1981). Mechanisms of skill acquisition and the law of practice. In J. R. Anderson (Ed.), Cognitive skills
and their acquisition (pp. 1-55). Hillsdale, NJ: Erlbaum. Newmark,J., & Lederman, R. J. (1987). Practice doesn't necessarily makeperfect: Incidence of overuse syndromes in amateur instrumentalists.
Medical Problems of Performing Artists, 2, 142-144.
Noakes, T. (1991). Lore of running: Discover the science and spirit ofrunning. Champaign. IL: Leisure Press.
Norman, D. (1976). Memory and attention (2nd ed.). New York: Wiley.
Oakes, W F. (1955). An experimental study of pitch naming and pitch
discrimination reaction. Journal of Genetic Psychology, 86, 237-259.
Palmer, C. (1989). Mapping musical thought to musical performance.
Journal of Experimental Psychology: Human Perception and Performance, 12, 331-346.
Pariser, D. (1987). The juvenile drawings of Klee, Toulouse-Lautrec
and Picasso. Visual Arts Research, 13, 53-67.
Parsons, J. E., Adler, T. F., & Kaczala, C. M. (1982). Socialization ofachievement attitudes and beliefs: Parental influences. Child Development, 53, 310-321.
Patel, V L., & Groen, G. J. (1991). The general and specific nature of
medical expertise: A critical look. In K. A. Ericsson & J. Smith(Eds.), Toward a general theory of expertise (pp. 93-125). Cambridge,
England: Cambridge University Press.
Pette, D. (1984). Activity-induced fast to slow transitions in mammalian muscle. Medicine and Science in Sports and Exercise, 16, 517528.
Pfau, H. D, & Murphy, M. D. (1988). Role of verbal knowledge in chessskill. American Journal of Psychology, 101, 73-86.
Phelps, R. M., & Shanteau, J. (1978). Livestock judges: how muchinformation can an expert use? Organizational Behavior and Human
Performance, 21, 209-219.
Pirolli, P., & Anderson, J. R. (1985). The role of practice in fact retrieval. Journal of Experimental Psychology: Learning, Memory, andCognition, 11, 136-153.
Plan, R. (1966). General introduction. In J. E. Meade & A. S. Parkes(Eds.), Genetic and environmental factors in human ability (pp. ix-xi).
Edinburgh, Scotland: Oliver & Boyd.
Plimpton, G. (Ed.). (1977). Writers at work: The Paris review. Interviews,
second series. New York: Penguin Books.
Plomin, R. (1991). Behavioral genetics. In P. R. McHugh & V A.
McKusik (Eds.), Gem's, brain and behavior (pp. 165-180). New York:
Raven Press.
Plomin, R., DeFries, J. C, & McClearn, G. E. (1990). Behavioral genetics: A primer (2nd ed.). New York: Freeman.
Poppleton, W L., & Salmoni. A. W (1991). Talent identification inswimming. Journal of Human Movement Studies, 20, 85-100.
Radford, J. (1990). Child prodigies and exceptional early achievers. New
York: Free Press.
Radford, P. F (1990). Sprinting. In T. Reilly, N. Secher, P. Snell, & C.
Williams (Eds.), Physiology of sports (pp. 71 -99). London: E. & F. N.
Spon.
Raskin, E. (1936). Comparison of scientific and literary ability: A biographical study of eminent scientists and letters of the nineteenth
century. Journal of Abnormal and Social Psychology, 31, 20-35.
Ravizza, K. (1984). Qualities of the peak experience in sport. In J. M.
Silva III, & R. S. Weinberg Psychological foundations of sport (pp.
452-461). Champaign, IL: Human Kinetics Books.
Reilly, T. (1990a). Football. In T. Reilly, N. Secher, P Snell, & C. Williams (Eds.), Physiology of sports (pp. 371-425). London: E. & F. N.
Spon.
Reilly, T. (1990b). Swimming. In T. Reilly, N. Secher, P. Snell, & C.
Williams (Eds.), Physiology of sports (pp. 217-257). London: E. &F. N. Spon.
Reilly, T, & Secher, N. (1990). Physiology of sports: An overview. In T.

THE ROLE OF DELIBERATE PRACTICE
Reilly, N. Secher, P., Snell, & C. Williams (Eds.), Physiology of sports(pp. 465-485). London: E. & F. N. Spon.
Rice, G. E., Meyer, B. J. F, & Miller, D. C. (1988). Relation of everyday
activities of adults to their prose recall performance. Educational
Gerontology, 14,147-158.
Robinson, J. P., (1985). The validity and reliability of diaries versus
alternative time use measures. In F. T. Juster & F. P. Stafford (Eds.),
Time, goods and well-being (pp. 33-62). Ann Arbor, MI: Institute forSocial Research, The University of Michigan.
Robinson, J. P, Andreyenkov, V G., & Patrushev, V D. (1988). The
rhythm of everyday life: How Soviet and American citizens use time.
Boulder, CO: Westview Press.
Robinson, J. P., Converse, R E., & Szalai, A. (1972). Country differences in time use. In A. Szalai (Ed), The use of time: Daily activities ofurban and suburban populations in twelve countries (pp. 113-144).
The Hague, The Netherlands: Mouton.
Roe, A. (1953). A psychological study of eminent psychologists andanthropologists, and a comparison with biological and physical scientists. Psychological Monographs: General and Applied, 67(Whole
No. 352), 1-55.
Roffwarg, H. P., Muzio, J. N., & Dement, W. C. (1966). Ontogenetic
development of the human sleep-dream cycle, Science, 152, 604619.
Rosenthal, R., & Rubin, D. B. (1978). Interpersonal expectancy effects:
The first 345 studies. The Behavioral and Brain Sciences, 1, H7-A15.
Rost, R. (1987). Athletics and the heart (T. J. Dekornfeld, Trans.). Chicago: Year Book Medical.
Roth, H. (1982). Master violinists in performance. Neptune City, NJ:
Paganinia.
Roth, H. (1987). Great violinists in performance: Critical evaluations ofover 100 twentieth-century virtuosi. Los Angeles, CA: Panjandrum
Books.
Rowley, P. T. (1988). Identifying genetic factors affecting music ability.
Psychomusicology, 7, 195-200.
Ruoff, B. A. (1981). Psychologische Analysen zum Alliag jugendlicher
Leistungssportler. Eine empirische Untersuchung (kognitiver Reprdsenlationen) von Tagesablaufen [Psychological analyses of everyday life in adolescent elite-performance athletes. Empirical studies
of cognitive representations of daily routines]. Miinchen, Federal
Republic of Germany: Minerva.
Rutter, M. (1989). Pathways from childhood to adult life. Journal ofChild Psychology and Psychiatry, 30, 23-51.
Sachs, M. L. (1991). Running—A psychosocial phenomenon. In L.
Diamant (Ed.), Psychology of sports, exercise, and fitness: Social andpersonal issues (pp. 237-247). New York: Hemisphere.
Sack, H.-G. (1975). Sportliche Betaligung und Personlichkeit [Sports
activity and personality]. Ahrensburg, Federal Republic of Germany: Verlag Ingrid Czwalina.
Sack, H.-G. (1980). Zur Psychologie des jugendlichen Leistungssportlers. Eine exemplarische Langsschnitt-Untersuchung anmannlichen und weiblichen Langstreckenldufern tiber einen ZeiIraum von vier Jahren am Ende der Adoleszenz [The psychology ofelite adolescent athletes. A longitudinal study of male and female
long-distance runners over a period of four years towards the end ofadolescence]. Schorndorf, Federal Republic of Germany: Hofmann.
Salmons, S., & Henri ksson, J. (1981). The adaptive response of skeletonmuscle to increased use. Muscle and Nerve, 4, 94-105.
Salthouse, T. A. (1984). Effects of age and skill in typing. Journal of
Experimental Psychology: General, 113, 345-371.
Salthouse, T. A. (1991). Expertise as the circumvention of human processing limitations. In K. A. Ericsson & J. Smith (Eds.), Toward ageneral theory of expertise: Prospects and limits (pp. 286-300). Cambridge, England: Cambridge University Press.
Samuel, I. (1987). Musical maestros. London: Rosters.

405

Scardemalia, M., & Bereiter, C. (1991). Literate expertise. In K. A.
Ericsson & J. Smith (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 172-194). Cambridge, England: Cambridge University Press.
Scheinfeld, A. (1939). You and heredity. New York: Stokes.
Schneider, W, & Shiffrin, R. M. (1977). Control and automatic human
information processing, I: Detection, search, and attention. Psychological Review, 84, 1-66.
Schneider, W, Bos, K., & Rieder, H. (1993). Leistungsprognose bei
jugendlichen Spitzensportlern [Prediction of the performance ofyoung elite athletes]. In J. Eckman, H. Strang, & E. Hahn (Eds.),
Aufmerksamkeil und Energetisierung [Attention and effort].
Gottingen, Federal Republic of Germany: Hogrefe.
Schulz, R., & Curnow, C. (1988). Peak performance and age amongsuper-athletes: Track and field, swimming, baseball, tennis, andgolf. Journal of Gerontology: Psychological Sciences, 43,113-120.
Schwarz, B. (1983). Great masters of the violin. New York: Simon andSchuster.
Scott, J. P., & Fuller, J. L. (1965). Genetics and the social behavior of thedog. Chicago: The University of Chicago Press.
Seashore, C. E. (1967). Psychology of music. New York: Dover. (Originally published in 1938).
Seashore, R. H. (1939). Work methods: An often neglected factor underlying individual differences. Psychological Review, 46, 123-141.
Seibel, R. (1963). Discrimination reaction time for a 1,023-alternativetask. Journal of Experimental Psychology, 66, 215-226.
Selye, H. (1964). From dream to discovery. New \brk: McGraw-Hill.
Shaffer, L. H. (1976). Intention and performance. Psychological Review, 83, 375-393.
Shaffer, L. H. (1981). Performancesof Chopin, Bach, and Bartok: Studies in motor programming. Cognitive Psychology, 13, 326-376.
Shaffer, L. H. (1982). Rhythm and timing in skill. Psychological Review, 89, 109-122.
Shuter-Dyson, R. (1982). Musical ability. In D. Deutsch (Ed.), The psychology of music (pp. 391-412). San Diego, CA: Academic Press.
Silva, J. M., Ill (1990). An analysis of the training stress syndrome incompetitive athletics. Applied Sport Psychology, 2, 5-20.
Simon, H. A., & Chase, W G. (1973). Skill in chess. American Scientist,
61, 394-403.
Simonton, D. K. (1984). Genius, creativity, and leadership. Cambridge,
MA: Harvard University Press.
Simonton, D. K. (1988). Scientific genius: A psychology of science.
Cambridge, England: Cambridge University Press.
Skinner, B. F. (1983). A matter of consequences: Part three of an autobiography. New York: Knopf.
Sloboda, J. A. (1983). The communication of musical metre in piano
performance. Quarterly Journal of Experimental Psychology, 35A,
377-396.
Sloboda, J. A. (1991). Musical expertise. In K. A. Ericsson & J. Smith(Eds.), Toward a general theory of expertise: Prospects and limits (pp.
153-171). Cambridge, England: Cambridge University Press.
Sloboda, J. A., Hermelin, B., & O'Connor, N. (1985). An exceptionalmusical memory. Music Perception, 3, 155-170.
Sloboda, J. A., & Howe, M. J. A. (1991). Biographical precursers ofmusical excellence: An interview study. Psychology of Music, 19,
3-21.
Sosniak, L. A. (1985). Learning to be a concert pianist. In B. S. Bloom(Ed.), Developing talent in young people (pp. 19-67). New York: Ballantine Books.
Starkes, J. L. (1987). Skill in field hockey: The nature of the cognitive
advantage. Journal of Sport Psychology, 9, 146-160.
Starkes, J. L., & Deakin, J. (1984). Perception in sport: A cognitive
approach to skilled performance. In W F. Straub & J. M. Williams

406

K. ERICSSON, R. KRAMPE, AND C. TESCH-ROMER(Eds.), Cognitive sport psychology (pp. 115-128). Lansing, NY: Sport
Science Associates.
Staszewski, J. J. (1988). Skilled memory and expert mental calculation.
In M. T. H. Chi, R. Blaser, & M. J. Farr (Eds.), The nature of expertise(pp. 71-128). Hillsdale, NJ: Erlbaum.
Subotnick, S. I. (1977). A biomechanical approach to running injuries.
Annals of the New York Academy of Sciences, 301, 888-899.
Szalai, A. (Ed.). (1972). The use of time: Daily activities of urban andsuburban populations in twelve countries. The Hague, The Netherlands: Mouton.
Tesch, P. A., & Karlsson, J. (1985). Muscle fiber types and size intrained and untrained muscles of elite athletes. Journal of Applied
Physiology, 59, 1716-1720.
Thorndike, E. L. (1921). The psychology of learning, Vol. II. New York:
Teachers College, Columbia University.
Treffert, D. A. (1989). Extraordinary people: Understanding "idiot savants" New York: Harper & Row.
Trowbridge, M. H., & Cason, H. (1932). An experimental study ofThorndike's theory of learning. Journal of General Psychology, 7,245-288.
Tyler, L. E. (1965). The psychology of human differences. New York:Appleton-Century-Crofts.
VanLehn, K. (1991). Rule acquisition events in the discovery of problem-solving strategies. Cognitive Science, 15, 1-47.
Varon, E. X (1935). The development of Alfred Binet's psychology.
Psychological Monographs, 46(Whole No. 207).
Voss, J. F, Greene, T. R., Post, T. A., & Penner, B. C. (1983). Problemsolving skill in the social sciences. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol.
17, pp. 165-213). San Diego, CA: Academic Press.
Wallingford, R. (1975). Long distance running. In A. W Tayler & F.
Landry (Eds.), The scientific aspects of sports training (pp. 118-130).
Springfield, IL: Charles C Thomas.
Ward, W. D, & Burns, E. M. (1982). Absolute pitch. In D. Deutsch(Ed.), The psychology of music (pp. 431-451). San Diego, CA: Academic Press.

Watkins, A., Woodhull-McNeal, A. P., Clarkson, P. M, & Ebbeling, C.
(1989). Lower extremity alignment and injury in young, preprofessional, college, and professional ballet dancers. Part I. Turnout andknee-foot alignment. Medical Problems in Performing Artists, 4,148153.
Watkins, J. G. (1942). Objective measurement of instrumental performance. (Report No. 860). New York: Teachers College, Columbia
University Contributions to Education.
Webb, N. L. (1975). An exploration of mathematical problem-solving
processes (Doctoral dissertation, Stanford University, 1975). Dissertation Abstracts International, 36, 2689A. (University Microfilms
No. 75-25625)
Welford, A. T. (1968). Fundamentals of skill. London: Methuen.
Wells, C. L. (1991). Women, sport, & performance: A physiological perspective. Champaign, IL: Human Kinetics Books.
Williams, C. (1990). Metabolic aspects of exercise. In T. Reilly, N.
Secher, P.Suell, &C. Williams (Eds.), Physiology of sports (pp. 3-40).
London: E. & F N. Spon.
Williams, T. (1988). My turn at bat: The story of my life. New York:
Simon & Schuster.
Wilson, R. S. (1986). Twins: Genetic influence on growth. In R. M.
Malina & C. Bouchard (Eds.), Sport and human genetics (pp. 1-21).
Champaign, IL: Human Kinetics Books.
Winget, C. M., DeRoshia, C. W, & Holley, D. C. (1985). Circadianrhythms and athletic performance. Medicine and Science in Sports
and Exercise, 17, 498-516.
Woodworth, R. S., & Schlosberg, H. (1954). Experimental psychology.
New York: Holt, Rinehart & Winston.
Yamada, J. (1991). The discrimination learning of the liquids /r/ and/l/ by Japanese speakers. Journal of Psycholinguistic Research, 20,
31-46.
Received April 14, 1992
Revision received December 1 1 , 1 992
Accepted December 11,1992 ■