Journal of Physical Education and Sport ® (JPES), Vol. 24 (issue 8), Art 226, pp. 2040 - 2048, August 2024
online ISSN: 2247 - 806X; p-ISSN: 2247 – 8051; ISSN - L = 2247 - 8051 © JPES

Original Article
Match running performance in male professional soccer players:
Interactive effect of score-line and playing position.
ARTHUR PEREIRA VENTURA1, ANDERSON SANTIAGO TEIXEIRA2, RODRIGO MENDONÇA
TEIXEIRA3, RODRIGO LEAL DE QUEIROZ THOMAZ DE AQUINO4, JOSÉ FRANCISCO DE SOUSA
NETO SEGUNDO5, CHELLSEA HORTÊNCIO ALCÂNTARA SILVA6, TIAGO CETOLIN7, PEDROAUGUSTO MOHR8, JULIANO FERNANDES DA SILVA9.
1,2,3,5,6,7,9Research Center for Development of Football and Futsal, Sports Center, Federal University of Santa
Catarina, BRAZIL;
1
Faculty of Sport, University of Porto, PORTUGAL;
2,7,8
Physical effort Laboratory, Sports Center, Federal University of Santa Catarina, BRAZIL;
3,6
Faculty of Physical Education and Physiotherapy, Federal University of Amazonas, BRAZIl;
4
LabSport, Department of Sports, Center of Physical Education and Sports, Federal University of Espírito Santo,
BRAZIL.
Published online: August 31, 2024
Accepted for publication : August 15, 2024
DOI:10.7752/jpes.2024.08226
Abstract:
Time-motion analysis has grown substantially in recent decades with the aim of monitoring players' work rate
profiles during a match. This study investigated how current score-line (i.e. winning, drawing, losing) andplaying position interact to influence match running performance (i.e. total distance, and the distances covered at
different intensities) in male professional soccer players. A total of 193 individual match observations of 42
outfield players (goalkeepers excluded) from the Brazilian national leagues were analyzed. The players werecategorized into four positions: central defenders (n = 10), full-backs (n = 9), midfielders (n = 14), and forwards(n = 9). The following running variables were retained: total distance (TD), walking (0 to 6 km·h-1), jogging (6.1
to 12 km·h-1), low (LIR: 12.1 to 15 km·h-1), medium (MIR: 15.1 to 19 km·h-1), and high intensity running (HIR:
19.1 to 23 km·h-1), sprint (> 23 km·h-1), and high intensity activity (HIA: sum of MIR + HIR + sprint). Overall,drawing status decreased distances walking and increased TD, jogging, LIR, MIR, HIR, and HIA compared towinning and losing status. Forwards and full-backs covered greater sprint distance during drawing than losing
status. Central defenders accumulated less sprint distances during drawing and winning conditions than otherpositions. Lastly, full-backs and forwards when drawing and winning, respectively, covered longer sprint
distances than midfielders. These findings may help coaches to better understand the influence of contextual
factors on running performance of Brazilian elite-level soccer players, in addition to offering relevant
information for the development of individualized training programs.
Key Words:Performance analysis; match status; football association; global positioning system; match
external load
Introduction
In football, physical demands have increased considerably in recent decades (Bradley & Ade, 2018) due
to the dynamism and unpredictability of the workload during the match, especially in matches with a busy
schedule and in decisive matches during the competition (Clemente et al., 2021). In order to reduce the risk of
injuries and promote match preparedness, head coaches and strength and conditioning coaches have beenmonitoring the physical performance of their players during matches in order to obtain relevant information tocreate effective training and recovery strategies (Hader et al., 2019). With the advancement of technology andthe development of computerized tracking devices (Pons et al., 2019; Castellano, Alvarez-Pastor & Bradley,2014), time-motion analysis has become more applicable for monitoring players' work rate profiles (Teixeira etal., 2021), becoming a data collection approach capable of quantifying their running performance during thematch (Bradley & Ade, 2018).
Time-motion analysis is a topic of current interest in team-sports and is seen as a valuable tool thatallows coaches to objectively assess the performance of their teams at an individual and collective level
throughout the match (Castells et al., 2016). In a soccer context, time-motion analysis has contributed
considerably to our understanding of the physical demands experienced by players in elite-level competition(Chmura et al., 2018; Aquino et al., 2018; Modric et al., 2019). Given that soccer is dominated by strategic
factors, a large portion of the studies with time-motion analysis have reported the effects of positional andcontextual factors (Paul et al., 2015) such as playing position (Redwood-Brown et al., 2018; Di Salvo et al.,2007), quality of opposition (Aquino et al., 2017), match location (Paraskevas et al., 2020), and match outcome
2040---------------------------------------------------------------------------------------------------------------------------------Corresponding Author: ARTHUR PEREIRA VENTURA, E-mail: arthurpventura@gmail.com

ARTHUR PEREIRA VENTURA, ANDERSON SANTIAGO TEIXEIRA, RODRIGO MENDONÇA TEIXEIRA,RODRIGO LEAL DE QUEIROZ THOMAZ DE AQUINO, JOSÉ FRANCISCO DE SOUSA NETO SEGUNDO,CHELLSEA HORTÊNCIO ALCÂNTARA SILVA, TIAGO CETOLIN, PEDRO AUGUSTO MOHR,JULIANO FERNANDES DA SILVA--------------------------------------------------------------------------------------------------------------------------------------(i.e., the final result of the match) (Aquino et al., 2017). Another situational variable that has received someattention from soccer professionals and specialists is the influence of the score-line state (also described as match
status) on different aspects of match-related performance (Paul et al., 2015; Redwood-Brown et al., 2018).
The score-line can be viewed as a measure of performance accomplishment and hence, it may influence
the player’s physical effort and technical/tactical performance as a goal is conceded or scored throughout thematch (O’donoghue & Tenga, 2001). There are two main approaches to investigate the effects of score-line insoccer. The first approach considers score-line in relation to the match status during the game (e.g. whether ateam is winning, drawing, or losing) (O’donoghue & Tenga, 2001; Bloomfield et al., 2005; Lago-Peñas et al.,2010), while the second investigates the number of goals that have been scored by each team (e.g. 1-0, 2-0, 2-1,
and so on) or goal difference (GD) (-2, -1, 0, +1, +2) (Redwood-Brown et al., 2018; Buchheit et al., 2018).
There have been controversial findings among studies regarding effects of score-line state on matchrunning performance in soccer players, with some studies supporting that score-line affects running performance(Redwood-Brown et al., 2018; Buchheit et al., 2018) while other studies do not (Bloomfield et al., 2005;
Redwood-Brown et al., 2012). Lago et al. (2010) reported no association between total distance (TD) and scoreline during Spanish Premier League matches (2005-2006 season). In contrast, O’Donoghue and Robinson (2016)
and Redwood-Brown et al. (2018) showed that players covered longer TD when drawing than when winning or
losing during English Premier League matches (2011-2012 and 2013-2014 seasons). For low intensity activities,
Lago et al. (2010) observed that for each minute drawing compared with losing, the distance covered walking
and jogging (0 to 11 km.h-1) and at low-speed running (11.1 to 14.0 km.h-1) increased by 3.7 m and 1.7 m,
respectively. For high intensity activities (HIA), O’Donoghue and Tenga (2001) observed that players performed
significantly more HIA when drawing than when winning or losing. This finding is supported by RedwoodBrown et al. (2018) and Buchheit et al. (2018) who found an inverted “U” shaped association between HIA (>14.4 km·h-1) and score-line state, with greater distances covered when goal difference was zero (i.e., drawing)
and reduced distances covered when goal difference was either positive (i.e., winning: +1, +2) or negative (i.e.,
losing: -1, -2). Conversely, earlier studies did not show an effect of score-line state on the percentage of timespent at HIA (Bloomfield et al., 2005), distance covered at moderate-speed running (14.1 to 19.1 km.h-1),
distance covered at high-speed running (above 14.4 km.h-1) (Lago-Peñas et al., 2010; Redwood-Brown et al.,2012), and sprinting actions (> 23.0 or 25.2 km.h-1) (Lago-Peñas et al., 2010; Redwood-Brown et al., 2018;
O’donoghue & Robinson, 2016) in elite professional soccer players.
A key positional variable to be considered along with score-line state is the playing position(Bloomfield et al., 2005; Redwood-Brown et al., 2018). Findings on the independent effect of playing position
on match running performance are robust and well-documented in the soccer literature (Di Salvo et al., 2007;
Paul et al., 2015). Nonetheless, the interactive effect between score-line and playing position on match running
performance in soccer has not received much attention in the literature. Bloomfield et al. (2005) and RedwoodBrown et al. (2018) did not find any interaction effect between score-line and playing position. Redwood-Brown
et al. (2012) and Lago-Peñas et al. (2021) reported that forwards and defenders displayed higher work-rate when
their teams were winning and losing, respectively. Of interest, these previous studies (with the exception of
Lago-Peñas et al. (2021)) are limited to 3 positional roles (defenders, midfielders, and forwards), while players
serving tactical roles on the side regions of the pitch were not analyzed. To date, studies addressing theindependent and interactive effects of score-line and playing position on match running performance in Braziliansoccer players are unknown. This is of practical relevance, as evidence suggests that different leagues in distinct
countries exhibit unequal physical demands (Dellal et al., 2011). Therefore, data collected in England, Spain, andAsia cannot be generalized to other national league matches or other tournaments.
Given the importance of understanding how contextual factors can affect physical demand in soccer
match-play from different leagues outside the European continent, the current study was designed to examine theinteractive effect of score-line and playing position on match running performance in male professional soccer
players during home matches in the main Brazilian national leagues. Unlike previous works, this study used theglobal positioning system (GPS) as a data collection device and applied a manual approach to data processing sothat it was possible to make time cuts with greater precision in the different match status, which is extremely
important since fluctuations in the players' activities may occur according to moments of win, draw, or lose.
Material & methods
Participants and Match Data
Match performance data were collected during 17 and 12 official matches of the first and second
division of the Brazilian National League, respectively, during the 2017 season. The sample included 18 and 24
professional outfield soccer players who were playing for a single professional soccer team from each division inthis respective season. The final league positions of the teams were 18th and 12th at the end of the season in thefirst and second division, respectively. We did not find any significant differences between the divisions for thematch running performance outcomes. Thus, all match performance data were pooled, yielding a total sample
composed of 42 outfield soccer players. A total of 193 individual match observations (average of 4.60----------------------------------------------------------------------------------------------------------------------------2041
JPES ® www.efsupit.roARTHUR PEREIRA VENTURA, ANDERSON SANTIAGO TEIXEIRA, RODRIGO MENDONÇA TEIXEIRA,RODRIGO LEAL DE QUEIROZ THOMAZ DE AQUINO, JOSÉ FRANCISCO DE SOUSA NETO SEGUNDO,CHELLSEA HORTÊNCIO ALCÂNTARA SILVA, TIAGO CETOLIN, PEDRO AUGUSTO MOHR,JULIANO FERNANDES DA SILVA--------------------------------------------------------------------------------------------------------------------------------------observations per player [minimum = 1; maximum = 16]) were made of outfield players (goalkeepers excluded).
All players were classified into four positional roles: central defenders (n=10; 53 individual observations), fullbacks (n=9; 42 individual observations), midfielders (n=14; 57 individual observations), and forwards (n=9; 41
individual observations). Players who did not play for the full match time (i.e., on the pitch for the whole 90min) were excluded from the subsequent analyses. In addition, in order to minimize the known effects of thematch location on running performance metrics (Aquino et al., 2017), only home matches were considered forthis study. All players gave their written consent after a full explanation of the purpose of the study and theexperimental design. This study was approved (number: 2.572.259) by the research ethics committee of theFederal University of Santa Catarina (CAAE: 46455015.3.0000.0121) according to resolution 466/2012 of the
National Health Council for research with human beings.
Experimental ProceduresThis is an observational study, with post-hoc analysis. Matches were divided into three episodes basedon evolving match status. These episodes were classified as ‘‘winning’’, ‘‘drawing’’, or ‘‘losing’’ according to
the score-line at the time: ahead, level, or behind, respectively. During a match, the maximum and minimum
number of episodes observed was six and one (i.e., when the reference team analyzed in this study was drawing
throughout the 90 min of the match), respectively. The total number of episodes for the 29 sampled matches was
77 [44 drawing, 17 winning, and 16 losing]. Of these 29 matches, the reference teams analyzed in this study won
3 and 6 matches, drew 9 and 2 matches, and lost 5 and 4 matches for the first and second division national
league, respectively. The total relative time spent in a score-level state equal to +3, +2, +1, 0, -1, -2, and -3
during the sampled matches is illustrated in Figure I. Match running performance was measured by a global
positioning system (GPS) during all matches. All running performance metrics for each of these match episodes
were downloaded post-match to a computer and analyzed using a customized software package (Prozone
kinetics 1.02.033, Leeds, England). The moments when goals were scored in each match were computed using
the match reports available on the website of the Brazilian Football Confederation (CBF) to determine the scorelevel state of the reference teams in each of the episodes (i.e., whether drawing, winning, or losing).

Figure I. Time spent (%) in different score-line states. Relative values (absolute values in minutes)
Match Running Performance
Player match performance was tracked using a GPS system with an operational sampling frequency of
10 Hz (K-Gps; K-Sport, Montelabbate, Italy). The reliability and validity of the GPS have been described indetail elsewhere (Castagna et al., 2019; Riboli et al., 2020). During the matches, all players wore the same GPS
devices, inserted into a purpose-built backpack and positioned on the upper part of their back. Each device wasturned on between 15-30 min before each match to allow acquisition of the satellite signal. All match data were
initially analyzed using a customized software package (Prozone kinetics 1.02.033, Leeds, England) and theninserted into a custom-made Microsoft Excel spreadsheet designed to provide all measures of match running
performance. The GPS outputs used for analysis in this study were as follows: total distance covered (TD),walking (speed from 0 to 6 km.h-1); jogging (speed from 6.1 to 12 km.h-1); low intensity running (LIR: speed
from 12.1 to 15 km.h-1); medium intensity running (MIR: speed from 15.1 to 19 km.h-1); high intensity running(HIR: speed from 19.1 to 23 km.h-1); sprint (SPR: speed > 23 km.h-1); and high intensity activity (HIA: sum of
MIR + HIR + sprint) (Di Salvo et al., 2007). All these variables were expressed as relative distance covered in
one minute (m.min-1). Furthermore, the number of sprints (NS > 23 km.h-1) and absolute peak match speed(PMS) were retained for subsequent analyses.
2042---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roARTHUR PEREIRA VENTURA, ANDERSON SANTIAGO TEIXEIRA, RODRIGO MENDONÇA TEIXEIRA,RODRIGO LEAL DE QUEIROZ THOMAZ DE AQUINO, JOSÉ FRANCISCO DE SOUSA NETO SEGUNDO,CHELLSEA HORTÊNCIO ALCÂNTARA SILVA, TIAGO CETOLIN, PEDRO AUGUSTO MOHR,JULIANO FERNANDES DA SILVA--------------------------------------------------------------------------------------------------------------------------------------Statistical Analysis
Data are presented as mean ± standard deviation. The Shapiro Wilk test was used to test the normalityof the data. When the normality assumption was violated, a Box-Cox transformation was performed. To examine
the independent and combined effects of score-line and playing position, repeated measures two-way ANOVA
was performed for all running performance metrics, assuming score-line (drawing, winning, or losing) andplaying position (central defender, full-back, midfielder, and forward) as fixed factors and participants as arandom factor. Whenever a significant F-value was obtained, a post hoc test with a Tukey’s adjustment was
performed for multiple comparison. The effect size (ES) was calculated for all ANOVAs using partial etasquared and classified as: > 0.01 (small), > 0.06 (moderate), and > 0.15 (large) (Cohen, 1988). In addition, effectsizes (Cohen’s d) were calculated for all paired comparisons between score-line states and playing positions, andjudged according to the following scale: ≤0.20 (trivial), >0.2 to 0.6 (small), >0.6 to 1.2 (moderate), >1.2 to 2.0(large), >2.0 to 4.0 (very large) (Batterham & Hopkins, 2005). Statistical analysis was carried out using the R
Commander i386 4.0.2 program and the significance level was set at p < 0.05.
Results
The distances covered in each running speed zone for the different score-line states and playing
positions are shown in Table I. There was a significant main effect of score-line for TD (η2 = 0.07, moderate),walking (η2 = 0.07, moderate), jogging (η2 = 0.07, moderate), LIR (η2 = 0.07, moderate), MIR (η2 = 0.09,
moderate), HIR (η2 = 0.10, moderate), and HIA (η2 = 0.11, moderate) (Table I), with players accumulating lessdistances walking (p = 0.01; d = 0.57, small) and covering significantly greater TD (p = 0.05; d = 0.46, small),distances jogging (p ≤ 0.05; d = 0.53 and 0.52, small), distances at LIR (p = 0.03; d = 0.40, small), MIR (p =0.01; d = 0.49, small), HIR (p = 0.03; d = 0.58, small), and HIA (p ≤ 0.05; d = 0.45 and 0.52, small) whendrawing than when they were winning or losing, respectively.
There was also a significant main effect of playing position for all running performance variables (η2 =0.19 to 0.61, large) (Table I). Post-hoc analysis indicated that central defenders covered significantly lower TD
compared to all other positions (p ≤ 0.01; d = 1.23 to 2.43, large to very large), while midfielders covered
significantly greater TD than full-backs (p = 0.04; d = 0.58, small). Central defenders also covered significantly
longer distances walking (p < 0.01; d = 1.40 to 1.99, large) and shorter distances at LIR (p < 0.01; d = -1.49 to 2.70, large to very large), MIR (p < 0.01; d = -1.91 to -2.96, large to very large), HIR (p < 0.01; d = -1.88 to 2.56, large to very large), sprints (in terms of distance and number) (p < 0.01; d = -0.96 to -1.83, moderate tolarge), and HIA (p < 0.01; d = -2.58 to -3.20, very large) than all other playing positions. Midfielders covered
significantly longer distances jogging (p ≤ 0.03; d = 0.67 to 1.20, moderate to large) than central defenders andfull-backs, and longer distances at LIR (p < 0.01; d = 1.29 to 2.70, large to very large) and MIR (p < 0.01; d =0.96 to 2.91, moderate to very large) compared to all other playing positions. Finally, forwards and full-backs
reached higher PMS than central defenders and midfielders (p ≤ 0.01; d = 0.86 to 1.83, moderate to large).
Table I. Descriptive statistics (mean ± SD) for the match running performance variables according to thedifferent score-line states and playing position. F and p-value for the main effects and interaction effects are also
indicated (repeated measures two-way ANOVA outputs).
Repeated Measures Two-Way ANOVA
Playing Position

Running Variables Central Defender Full-Back Midfielder Forward

ScoreLine
EffectFF[p[p-value]
value]
Position
EffectScore-Line

Drawing Winning Losing

Interaction
EffectF[p-value]

TD (m.min-1)

81.57
±
6.05a

93.69
±
12.59b

99.99
±
9.02c

95.13
±
5.08bc96.05±
10.51+

90.78
±
12.12

91.52
±
9.92

24.71
[< 0.01]

3.98[0.02]

0.61 [0.72]

walking (m.min-1)

30.31
±
2.73a

26.42
±
2.80b

24.81
±
2.81b

26.47
±
2.75b

26.02
±
3.54*

26.96
±
3.24

27.99
±
3.41

20.71
[< 0.01]

3.87[0.02]

0.29 [0.93]

jogging (m.min-1)

31.98
±
4.82a

34.48
±
5.34a

38.04
±
5.28b

35.80
±
4.19ab

37.03
±
5.57#

34.24
±
4.92

34.18
±
5.40

7.91
[< 0.01]

3.95[0.02]

0.21 [0.97]

LIR (m.min-1)

9.35
±
2.11a

12.91
±
2.63b

17.31
±
3.60c

13.66
±
1.75b

14.39
±
3.86+

12.81
±
3.98

13.60
±
4.45

48.62
[< 0.01]

3.57[0.03]

0.77 [0.59]

MIR (m.min-1)

6.13
±
1.36a

9.99
±
2.51b

12.55
±
2.81c

10.28
±
1.44b

10.70
±
3.45+

9.15
±
2.91

9.81
±
3.32

51.55
[< 0.01]

4.92
[<
0.01]

0.26 [0.95]----------------------------------------------------------------------------------------------------------------------------2043
JPES ® www.efsupit.roARTHUR PEREIRA VENTURA, ANDERSON SANTIAGO TEIXEIRA, RODRIGO MENDONÇA TEIXEIRA,RODRIGO LEAL DE QUEIROZ THOMAZ DE AQUINO, JOSÉ FRANCISCO DE SOUSA NETO SEGUNDO,CHELLSEA HORTÊNCIO ALCÂNTARA SILVA, TIAGO CETOLIN, PEDRO AUGUSTO MOHR,JULIANO FERNANDES DA SILVA--------------------------------------------------------------------------------------------------------------------------------------HIR (m.min-1)

2.56
±
0.79a

4.84
±
1.52b

5.11
±
1.73b

5.55
±
1.45b

5.07
±
2.08*

4.22
±
1.63

4.03
±
1.47

24.77
[< 0.01]

5.32
[<
0.01]

1.69 [0.13]

SPR (m.min-1)

1.22
±
0.73a

3.38
±
1.66b

2.15
±
1.16c

3.36
±
1.48b

2.82
±
1.81

2.36
±
1.48

1.90
±
0.83

23.10
[< 0.01]

2.11[0.12]

2.65 [0.02]

HIA (m.min-1)

9.92
±
2.24a

18.22
±
3.43b

19.82
±
4.95b

19.19
±
3.43b

18.60
±
6.27#

15.97
±
5.25

15.74
±
4.69

45.57
[< 0.01]

6.22
[<
0.01]

1.01 [0.42]

NS (n)

3.09
±
1.70a

7.61
±
3.76b

5.44
±
2.93b

7.89
±
6.17b

6.26
±
5.29

5.54
±
3.60

5.57
±
2.98

11.09
[< 0.01]

0.15[0.85]

1.36 [0.23]

PMS (km.h-1)

27.41
±
2.32a

29.66
±
1.97b

27.73
±
2.25a

30.29
±
2.43b

28.56
±
2.08

28.63
±
3.21

28.52
±
2.22

10.29
[< 0.01]

0.01[0.98]

1.70 [0.12]

TD: total distance; LIR: low intensity running; MIR: medium intensity running; HIR: high intensity running;
SPR: sprint; HIA: high intensity activities; NS: number of sprints, PMS: peak match speed; Different letters(abc) indicate significant differences between positions; + significantly different from winning; * significantly
different from losing; # significantly different from all other score-line states.
The statistical analysis revealed a significant score-line-by-playing position interaction effect for sprint
distance (η2 = 0.14, moderate), with forwards (3.86 ± 1.63 m.min-1 vs. 1.95 ± 0.40 m.min-1; p = 0.04; d = 1.61,
large) and full-backs (4.33 ± 1.96 m.min-1 vs. 2.26 ± 0.96 m.min-1; p = 0.02; d = 1.34, large) covering greater
sprint distance when they were drawing than when they were losing, respectively (Figure II). In addition, central
defenders covered significantly lower sprint distances during drawing and winning conditions when compared toall other positions (p ≤ 0.04 for all comparisons; d = -0.98 to -2.55, moderato to very large). It was also observedthat full-backs when drawing (4.33 ± 1.96 m.min-1 vs. 2.43 ± 1.12 m.min-1; p = 0.02; d = 1.19, large) andforwards when winning (3.66 ± 1.27 m.min-1 vs. 2.07 ± 1.33 m.min-1; p = 0.01; d = 1.22, large) covered greater
sprint distances than midfielders, respectively (Figure II). No other interaction effect was reported for the otherrunning performance variables (p > 0.05).

Figure II. Sprint distance for the different score-line state for each playing position. The values are presented inmean ± standard deviation. * Significantly different from losing; m significantly different from Midfielder; asignificantly different from all other positions.
Dicussion
The current study investigated the independent and interactive effects of score-line and playing
positions on match running performance in elite professional Brazilian soccer players. The main results were: i)in general, drawing status resulted in greater running outputs compared to winning or losing status; ii) central
defenders presented lower distances covered at different speed zones than all other playing positions, with the
exception of distances walking; iii) midfield players demonstrated the highest values of running demands, withthe exception of PMS; iv) interaction effects showed that forwards and full-backs covered greater sprint
distances when they were drawing compared to losing. Furthermore, central defenders covered lower sprint
distances in the drawing and winning status than all other positional roles. Finally, full-backs in drawing status
and forwards in winning status covered greater sprint distances than midfielders.
2044---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roARTHUR PEREIRA VENTURA, ANDERSON SANTIAGO TEIXEIRA, RODRIGO MENDONÇA TEIXEIRA,RODRIGO LEAL DE QUEIROZ THOMAZ DE AQUINO, JOSÉ FRANCISCO DE SOUSA NETO SEGUNDO,CHELLSEA HORTÊNCIO ALCÂNTARA SILVA, TIAGO CETOLIN, PEDRO AUGUSTO MOHR,JULIANO FERNANDES DA SILVA--------------------------------------------------------------------------------------------------------------------------------------A myriad of previous studies have investigated match running performance in professional players(Hands & Jonge, 2020). In top division teams of national leagues, the average TD ranged from 10,274 meters(Australia) to 11,389 meters (Italy), including average high-speed distances (i.e., > 19.8 km·h-1) from 559 meters(Poland) to 1,224 meters (Italy) (Hands & Jonge, 2020). In the elite level Brazilian context (e.g., First Division),few studies have reported these data (Augusto et al., 2021; Barros et al., 2007). In First Division Championshipmatches (editions 2001 to 2004), players covered an average TD of 10,012 meters, including an average highspeed distance (≥ 19 km·h-1) of 1,128 meters (Barros et al., 2007). During the 2017 season of the same national
division, the average TD was 9,623 meters, including an average high-speed distance (≥ 18.1 km·h-1) of 1,033
meters (Augusto et al., 2021). In Second Division Brazilian Championships (editions 2019 and 2020), previous
studies reported TD values ranging from 9,688 to 10,111 meters and distances in high-speed running (> 18.1
km·h-1) from 920 to 1,020 meters (Aquino et al., 2021; Gonçalves et al., 2020). In this study, we verified valuesof TD per minute ranging from ~82 m·min-1 (central defenders) to ~100 m·min-1 (midfielders) and values of
HIR+SPR (≥ 19.1 km·h-1) ranging from ~4 m·min-1 (central defenders) to ~9 m·min-1 (forwards), demonstrating
reduced running outputs compared to other national divisions around the world and previous editions of the Firstand Second Brazilian National Championship. Additional contextual factors (e.g., playing formation, physicalfitness level, environmental conditions) and idiosyncrasies of each competition could explain, at least in part,these discrepancies between studies (Aquino et al., 2019; Krustrup et al., 2003; Mohr et al., 2012).
The running demands of each playing position are well-documented in the scientific literature. A
previous systematic review with elite level national leagues showed that the lowest average TD was covered bycentral defenders (10,178 meters), while the greatest TD was covered by wide midfielders (11,654 meters)(Hands & Jonge, 2020). The distances covered in high-speed running varies according to the speed thresholddefined by each study; however, the general trend was for central defenders to cover the least distance (621meters > 19.8 km·h-1), and wide midfielders to cover the greatest distance (1,216 meters > 19.8 km·h-1). In ourstudy, we also verified these responses. The position-specific profiles reported have benefits in the applied
context, allowing insights into the positional requirements dependent on the player role (Bradley & Ade, 2018).
The score-line is an additional contextual factor that influences the match running performance inprofessional players (Lago-Peñas, 2012). The importance of this situational variable is reflected in changes inteam and player strategies in response to the score-line (Bloomfield et al., 2005). Previous studies suggested thathigh-speed running increases when teams are losing a match compared to winning, in the hope of getting backinto the match (Castellano et al., 2011; Lago-Peñas et al., 2010). For every minute losing, players covered an
extra meter of high-speed running (> 19.1 km·h-1) compared to when winning; and conversely, winning
increased low-speed movements ( Lago-Peñas et al., 2010). Our results (in agreement with Redwood-Brown etal., 2018 and Buchheit et al., 2018) showed that players covered greater distances in various speed zones whendrawing than when winning or losing matches. This may be partially attributed to the fact that both teams whendrawing are trying to make a difference in score-line, likely through transitional play (Buchheit et al., 2018).
Furthermore, these findings suggest that players do not always use their maximal fitness capacity during theentire match (Trewin et al., 2017). In addition, few studies have investigated the interactive effects of playing
position and score-line on match running performance. In the English FA Premier League, midfielders covered alonger distance at high speed running when drawing, defenders longer when losing, and attackers longer when
winning (Redwood-Brown et al., 2012). Similar patterns were observed by Bradley and Noakes (2013) who
found that central defenders performed 17% less and attackers 15% more high speed running during matches
that were heavily won vs heavily lost (score differential ≥ 3 goals). In a large sample of elite soccer players in
the Spanish La Liga (individual observations = 4,249; matches = 297), losing status increased the running
outputs (e.g., TD, HIR, sprints) by defenders, while attacking players showed the opposite trend (Lago-Peñas etal., 2021). Our data demonstrated that forwards and full-backs covered ~100% more sprint distance in drawing
vs. losing status (large effect size). Collectively, these findings support the idea that running demands(particularly sprint distance in this study) of playing positions should be examined according to the score-line.
Additionally, coaches and practitioners should consider these contextual factors to interpret the match running
outputs and to prepare their players for the most intense periods of match-play.
Our study presents some limitations. No control and/or assessment was carried out for otherconfounding match factors, such as quality of opposition, playing formation, effective playing time, andcoaches’ ideas (e.g., strategies when winning, drawing, and losing status). In addition, the technical and tacticalskills were not investigated. Further studies should include this analysis. On the other hand, our study has somestrengths. For example, to the best of our knowledge, this is the first study to investigate the independent andinteractive effects of playing position and score-line in a Brazilian National Championship.
Conclusions
This study shows that the score-line affects the match running performance of outfield soccer players
depending on their playing position. Forwards and full-backs covered greater sprint distances when they weredrawing compared to losing. In addition, drawing status resulted in greater running outputs compared to winning----------------------------------------------------------------------------------------------------------------------------2045
JPES ® www.efsupit.roARTHUR PEREIRA VENTURA, ANDERSON SANTIAGO TEIXEIRA, RODRIGO MENDONÇA TEIXEIRA,RODRIGO LEAL DE QUEIROZ THOMAZ DE AQUINO, JOSÉ FRANCISCO DE SOUSA NETO SEGUNDO,CHELLSEA HORTÊNCIO ALCÂNTARA SILVA, TIAGO CETOLIN, PEDRO AUGUSTO MOHR,JULIANO FERNANDES DA SILVA--------------------------------------------------------------------------------------------------------------------------------------or losing. The least running distances were covered by central defenders (except for walking), while the greatest
distances were covered by midfielders (except for PMS). These findings may help coaches to better understandthe influence of contextual factors on match running performance of Brazilian elite-level soccer players, as wellas provide important information for individualizing additional training load for different positions.
Finally, future research should consider the position of the game and the score of the match to better
understand the factors that influence the variation in physical demand during the game. However, more complex
assessments are needed to understand how these contextual variables may also affect technical and tacticalaspects.
Conflicts of interest No potential conflict of interest was reported by the author(s).
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