An individualised approach to monitoring and prescribing training in elite youth football players

The concept of how training load affects performance is founded in the notion that training contributes to two specific outcomes, these are developed simultaneously by repeated bouts of training and act in conflict of each other; fitness and fatigue (Banister et al., 1975). The ability to understand these two components and how they interact with training load is commonly termed the “dose-response relationship” (Banister, 1991). The accurate quantification of training load, fitness and fatigue are therefore of paramount importance to coaches and practitioners looking to examine this relationship. In recent years, the advancement in technology has seen a rise in the number of methodologies used to assess training load and specific training outcomes. However, there is a general lack of evidence regarding the reliability, sensitivity and usefulness of these methods to help inform the training process. The aim of this thesis was therefore to improve the current understanding around the monitoring and prescription of training, with special reference to the relationship between training load, fitness and fatigue. Chapter 4 of this thesis looked to establish test re-test reliability. Variables selected for investigation were measures of subjective wellness; fatigue, muscle soreness, sleep quality, stress levels and mood state, assessments of physical performance; countermovement jump (CMJ), squat jump (SJ) and drop jump (DJ) and the assessment of tri-axial accelerometer data; PlayerLoadTM and individual component planes anterior-posterior (PLAP), mediolateral (PLML), and vertical (PLV), were collected during a sub-maximal shuttle run. The results from this investigation suggest that a short three minute sub-maximal shuttle run can be used as a reliable method to collect accelerometer data. Additionally, assessments of CMJ height, SJ height, DJ contact time (DJ-CT) and DJ reactive strength index (DJ-RSI) were all deemed to have good reliability. In contrast, this chapter highlighted the poor test re-test reliability of the subjective wellness questionnaire. Importantly, the minimum detectable change (MDC) was also calculated for all measures within this study to provide an estimate of measurement error and a threshold for changes that can be considered ‘real’. Chapter 5 assessed the sensitivity and reproducibility of these measures following a standardised training session. To assess sensitivity, the signal-to-noise (S: N) ratio was calculated by using the post training fatigue response (signal) and the MDC derived from Chapter 4 (noise). The fatigue response was considered reproducible if the S: N ratio was greater than one following two standardised training sessions. Three measures met the criteria to be considered both sensitive and reproducible; DJ-RSI, PLML and %PLV. All other measures did not meet the criteria. Subjective ratings of fatigue, muscle soreness and sleep quality did show a sensitive response on one occasion, however, this was not reproducible. This might be due to the categorical nature of the data, making detectable group changes hard to accomplish. The subjective wellness questionnaire was subsequently adapted to include three items; subjective fatigue, muscle soreness and sleep quality on a 10-point scale. The test re-test reliability of these three questions was established in Chapter 6, demonstrating that subjective fatigue and muscle soreness have good test re-test reliability. Chapter 6 was comprised of two studies looking to simultaneously establish the dose-response relationship between training load, measures of fatigue (Part I) and measures of fitness (Part II). In Part I training load was strategically altered on three occasions during a standardised training session in a randomised crossover design. In Part II training and match load was monitored over a 6-week training period with maximal aerobic speed (MAS) assessed pre and post. A key objective for both studies was to assess differences in the training load-fitness-fatigue relationship when using various training load measures, in particular differences between arbitrary and individualised speed thresholds. Results from Part I showed a large to very large relationship between training load and subjective fatigue, muscle soreness and DJ-RSI performance. No differences were found between arbitrary and individualised thresholds. In Part II however, individual external training load, assessed via time above MAS (t>MAS), showed a very large relationship with changes in aerobic fitness. This was in contrast to the unclear relationships with arbitrary thresholds. Taking the results from both studies into consideration it was concluded that t>MAS is a key measure of training load if the objective is to assess the relationship with both fitness and fatigue concurrently with one measure. Chapter 7 subsequently looked to validate the training load-fitness-fatigue relationships established in Chapter 6 via an intervention study. The aim was to develop a novel intervention that prescribed t>MAS, in order to improve aerobic fitness, based on the findings from Chapter 6. Additionally, the fatigue response following a standardised training session was assessed pre and post intervention to evaluate the effect the predicted improvements in aerobic fitness would have on measures of fatigue. Results from Chapter 7 indicate a highly predictable improvement in aerobic fitness from the training load completed during the study, validating the use of t>MAS as a monitoring and intervention tool. Furthermore, this improvement in aerobic fitness attenuated the fatigue response following a standardised training session. The final key finding was the very strong relationship between improvements in aerobic fitness and reductions in fatigue response. This further highlights the relationship between t>MAS, fitness and fatigue. In summary, this thesis has helped further current understanding on the monitoring and prescription of training load, with reference to fitness and fatigue. Firstly, a rigorous approach was used to identify fatigue monitoring measures that are reliable, sensitive and reproducible. Secondly, the relationship between training load, fatigue and fitness was clearly established. And finally, it has contributed new knowledge to the existing literature by establishing the efficacy of a novel MAS intervention to improve aerobic fitness and attenuate a fatigue response in elite youth football players.