ORIGINAL PAPER
Weekly variations of biomechanical load variables in professional soccer players: comparisons between playing positions
 
More details
Hide details
1
Department of Physical Education and Sports Sciences, Al-Kitab University, Kirkuk, Iraq
 
2
Escola Superior Desporto e Lazer, Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal
 
3
Instituto de Telecomunicações, Delegação da Covilhã, Lisbon, Portugal
 
 
Submission date: 2020-03-15
 
 
Acceptance date: 2020-05-17
 
 
Publication date: 2021-02-07
 
 
Hum Mov. 2021;22(3):19-34
 
KEYWORDS
TOPICS
ABSTRACT
Purpose:
The purpose of the present study was fourfold: (i) to describe the weekly variations of acute external load measures during a professional soccer season; (ii) to analyse the variability of external load measures within weeks; (iii) to analyse the acute:chronic workload ratio of players during the process; and (iv) to analyse the differences of external load measures between playing positions.

Methods:
Twenty professional soccer players (age: 24.9 ± 3.5 years; body mass: 71.6 ± 18.7 kg; height: 168.8 ± 41.4 cm) from the same team competing in the First Portuguese League (Europe) voluntarily participated in this study. They were daily monitored with a Global Positioning System (GPS) and the following external load variables were extracted per session: (i) total distance; (ii) running distance; (iii) high-speed running distance; (iv) distance at maximal speed; (v) distance at high accelerations; and (vi) players’ training load. The acute load and acute:chronic workload ratio were weekly calculated for each of the GPS measures.

Results:
Week-by-week variations ranged from –57% to +115%, depending on the playing position and the variable measured. The within-week variability revealed coefficients of variation between 48% and 55%, depending on the measure. Considering the differences in mean load between playing positions, significant differences between players were found for the majority of the variables, with the only exceptions being maximal speed and high accelerations distances.

Conclusions:
Great between-week variations in the acute load as well as the variability of load within weeks were found. It was observed that acute load was position-dependent.

REFERENCES (43)
1.
Gabbett TJ, Nassis GP, Oetter E, Pretorius J, Johnston N, Medina D, et al. The athlete monitoring cycle: a practical guide to interpreting and applying training monitoring data. Br J Sports Med. 2017;51(20):1451–1452; doi: 10.1136/bjsports-2016097298.
 
2.
Lambert MI, Borresen J. Measuring training load in sports. Int J Sports Physiol Perform. 2010;5(3):406–411; doi: 10.1123/ijspp.5.3.406.
 
3.
Halson SL. Monitoring training load to understand fatigue in athletes. Sports Med. 2014;44(Suppl. 2):139–147; doi: 10.1007/s40279-014-0253-z.
 
4.
Bourdon PC, Cardinale M, Murray A, Gastin P, Kellmann M, Varley MC, et al. Monitoring athlete training loads: consensus statement. Int J Sports Physiol Perform. 2017;12(Suppl. 2):S2-161–S2-170; doi: 10.1123/IJSPP.2017-0208.
 
5.
Carling C, Bradley P, McCall A, Dupont G. Match-to-match variability in high-speed running activity in a professional soccer team. J Sports Sci. 2016;34(24):2215–2223; doi: 10.1080/02640414.2016.1176228.
 
6.
Hoppe MW, Baumgart C, Slomka M, Polglaze T, Freiwald J. Variability of metabolic power data in elite soccer players during pre-season matches. J Hum Kinet. 2017;58(1):233–245; doi: 10.1515/hukin-2017-0083.
 
7.
Jeong T-S, Reilly T, Morton J, Bae S-W, Drust B. Quantification of the physiological loading of one week of “pre-season” and one week of “in-season” training in professional soccer players. J Sports Sci. 2011;29(11):1161–1166; doi: 10.1080/02640414.2011.583671.
 
8.
Clemente FM, Rabbani A, Ferreira R, Araújo JP. Drops in physical performance during intermittent small-sided and conditioned games in professional soccer players. Hum Mov. 2020;21(1):7–14; doi: 10.5114/hm.2020.88148.
 
9.
Clemente FM, Sarmento H. The effects of small-sided soccer games on technical actions and skills: a systematic review. Hum Mov. 2020;21(3):100–119; doi: 10.5114/hm.2020.93014.
 
10.
Castellano J, Blanco-Villaseñor A, Álvarez D. Contextual variables and time-motion analysis in soccer. Int J Sports Med. 2011;32(6):415–421; doi: 10.1055/s-0031-1271771.
 
11.
Santos PM, Lago-Penas C. Defensive positioning on the pitch in relation with situational variables of a professional football team during regaining possession. Hum Mov. 2019;20(2):50–56; doi: 10.5114/hm.2019.81019.
 
12.
Lacome M, Simpson BM, Cholley Y, Lambert P, Buchheit M. Small-sided games in elite soccer: does one size fit all? Int J Sports Physiol Perform. 2018;13(5):568–576; doi: 10.1123/ijspp.2017-0214.
 
13.
Clemente FM. The threats of small-sided soccer games: a discussion about their differences with the match external load demands and their variability levels. Strength Cond J; doi: 10.1519/SSC.0000000000000526.
 
14.
Clemente FM, Rabbani A, Conte D, Castillo D, Afonso J, Truman Clark CC, et al. Training/match external load ratios in professional soccer players: a full-season study. Int J Environ Res Public Health. 2019;16(17):3057;doi: 10.3390/ijerph16173057.
 
15.
Paul DJ, Bradley PS, Nassis GP. Factors affecting match running performance of elite soccer players: shedding some light on the complexity. Int J Sports Physiol Perform. 2015;10(4):516–519; doi: 10.1123/IJSPP.2015-0029.
 
16.
Rago V, Silva JR, Mohr M, Barreira D, Krustrup P, Rebelo AN. Variability of activity profile during medium-sided games in professional soccer. J Sports Med Phys Fitness. 2019;59(4):547–554; doi: 10.23736/S0022-4707.18.08376-7.
 
17.
Clemente FM, Rabbani A, Kargarfard M, Nikolaidis PT, Rosemann T, Knechtle B. Session-to-session variations of external load measures of youth soccer players in medium-sided games. Int J Environ Res Public Health. 2019;16(19):3612; doi: 10.3390/ijerph16193612.
 
18.
Clemente FM, Silva AF, Clark CCT, Conte D, Ribeiro J, Mendes B, et al. Analyzing the seasonal changes and relationships in training load and wellness in elite volleyball players. Int J Sports Physiol Perform. 2020;15(5):731–740; doi: 10.1123/ijspp.2019-0251.
 
19.
Malone S, Owen A, Newton M, Mendes B, Collins KD, Gabbett TJ. The acute:chronic workload ratio in relation to injury risk in professional soccer. J Sci Med Sport. 2017;20(6):561–565; doi: 10.1016/j.jsams.2016.10.014.
 
20.
Hulin BT, Gabbett TJ, Blanch P, Chapman P, Bailey D, Orchard JW. Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. Br J Sports Med. 2014;48(8):708–712; doi: 10.1136/bjsports-2013-092524.
 
21.
Malone JJ, Di Michele R, Morgans R, Burgess D, Morton JP, Drust B. Seasonal training-load quantification in elite English Premier League soccer players. Int J Sports Physiol Perform. 2015;10(4):489–497; doi: 10.1123/ijspp.2014-0352.
 
22.
Dalen T, Ingebrigtsen J, Ettema G, Hjelde GH, Wisløff U. Player load, acceleration, and deceleration during forty-five competitive matches of elite soccer. J Strength Cond Res. 2016;30(2):351–359; doi: 10.1519/JSC.0000000000001063.
 
23.
Baptista I, Johansen D, Figueiredo P, Rebelo A, Pettersen SA. Positional differences in peak- and accumulated-training load relative to match load in elite football. Sports. 2019;8(1):1; doi: 10.3390/sports8010001.
 
24.
Nikolaidis PT, Clemente FM, van der Linden CMI, Rosemann T, Knechtle B. Validity and reliability of 10-Hz global positioning system to assess in-line movement and change of direction. Front Physiol. 2018;9:228; doi: 10.3389/fphys.2018.00228.
 
25.
Gabbett TJ. The training-injury prevention paradox: should athletes be training smarter and harder? Br J Sports Med. 2016;50(5):273–280; doi: 10.1136/bjsports-2015-095788.
 
26.
Cohen J. Statistical power analysis for the behavioral sciences, 2nd ed. New York: Routledge; 2013.
 
27.
Batterham AM, Hopkins WG. Making meaningful inferences about magnitudes. Int J Sports Physiol Perform. 2006;1(1):50–57; doi: 10.1123/ijspp.1.1.50.
 
28.
Fessi MS, Nouira S, Dellal A, Owen A, Elloumi M, Moalla W. Changes of the psychophysical state and feeling of wellness of professional soccer players during pre-season and in-season periods. Res Sports Med. 2016;24(4):375–386; doi: 10.1080/15438627.2016.1222278.
 
29.
Clemente FM, Clark C, Castillo D, Sarmento H, Nikolaidis PT, Rosemann T, et al. Variations of training load, monotony, and strain and dose-response relationships with maximal aerobic speed, maximal oxygen uptake, and isokinetic strength in professional soccer players. PLoS One. 2019;14(12):e0225522; doi: 10.1371/journal.pone.0225522.
 
30.
Kelly DM, Strudwick AJ, Atkinson G, Drust B, Gregson W. Quantification of training and match-load dis tribution across a season in elite English Premier League soccer players. Sci Med Football. 2020;4(1):59–67; doi: 10.1080/24733938.2019.1651934.
 
31.
Clemente FM, Seerden G, van der Linden CMI. Quantifying the physical loading of five weeks of pre-season training in professional soccer teams from Dutch and Portuguese leagues. Physiol Behav. 2019;209:112588; doi: 10.1016/j.physbeh.2019.112588.
 
32.
Djaoui L, Wong DP, Pialoux V, Hautier C, Da Silva CD, Chamari K, et al. Physical activity during a prolonged congested period in a top-class European football team. Asian J Sports Med. 2014;5(1):47–53; doi: 10.5812/asjsm.34233.
 
33.
Gaudino P, Iaia FM, Alberti G, Strudwick AJ, Atkinson G, Gregson W. Monitoring training in elite soccer players: systematic bias between running speed and metabolic power data. Int J Sports Med. 2013;34(11):963–968; doi: 10.1055/s-0033-1337943.
 
34.
Oliveira R, Brito JP, Martins A, Mendes B, Marinho DA, Ferraz R, et al. In-season internal and external training load quantification of an elite European soccer team. PLoS One. 2019;14(4):e0209393; doi: 10.1371/journal.pone.0209393.
 
35.
Powers SK, Howley ET. Exercise physiology: theory and application to fitness and performance, 9th ed. New York: McGraw-Hill Education; 2014.
 
36.
Gabbett TJ. Debunking the myths about training load, injury and performance: empirical evidence, hot topics and recommendations for practitioners. Br J Sports Med. 2020;54(1):58–66; doi: 10.1136/bjsports-2018-099784.
 
37.
Foster C. Monitoring training in athletes with reference to overtraining syndrome. Med Sci Sports Exerc. 1998;30(7):1164–1168; doi: 10.1097/00005768-199807000-00023.
 
38.
Owen AL, Lago-Penñs C, Gómez MÁ, Mendes B, Dellal A. Analysis of a training mesocycle and positional quantification in elite European soccer players. Int J Sports Sci Coach. 2017;12(5):665–676; doi: 10.1177/1747954117727851.
 
39.
Enright K, Green M, Hay G, Malone JJ. Workload and injury in professional soccer players: role of injury tissue type and injury severity. Int J Sports Med. 2020;41(2):89–97; doi: 10.1055/a-0997-6741.
 
40.
Bowen L, Gross AS, Gimpel M, Bruce-Low S, Li FX. Spikes in acute:chronic workload ratio (ACWR) associated with a 5-7 times greater injury rate in English Premier League football players: a comprehensive 3-year study. Br J Sports Med. 2020;54(12):731–738; doi: 10.1136/bjsports-2018-099422.
 
41.
Martín-García A, Gómez Díaz A, Bradley PS, Morera F, Casamichana D. Quantification of a professional football team’s external load using a microcycle structure. J Strength Cond Res. 2018;32(12):3511–3518; doi: 10.1519/JSC.0000000000002816.
 
42.
Dellal A, Wong DP, Moalla W, Chamari K. Physical and technical activity of soccer players in the French First League – with special reference to their playing position. Int SportMed J. 2010;11(2):278–290.
 
43.
Bradley PS, Carling C, Archer D, Roberts J, Dodds A, Di Mascio M, et al. The effect of playing formation on high-intensity running and technical profiles in English FA Premier League soccer matches. J Sports Sci. 2011;29(8):821–830; doi: 10.1080/02640414.2011.561868.
 
eISSN:1899-1955
Journals System - logo
Scroll to top