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Original Research

Open Access Special Issue

Match-to-match variations in external load measures during congested weeks in professional male soccer players

  • Rui Silva1
  • Halil Ibrahim Ceylan2
  • Georgian Badicu3
  • Hadi Nobari4,5,6
  • Sílvio Afonso Carvalho7
  • Tiago Sant’Ana1
  • Bruno Mendes8
  • Yung-Sheng Chen9
  • Filipe Manuel Clemente1,10

1Escola Superior Desporto e Lazer, Instituto Politécnico de Viana do Castelo, Rua Escola Industrial e Comercial de Nun’Álvares, 4900-347 Viana do Castelo, Portugal

2Physical Education and Sports Teaching Department, Kazim Karabekir Faculty of Education, Ataturk University, 25030 Erzurum, Turkey

3Department of Physical Education and Special Motricity, University Transilvania of Brasov, 500068 Brasov, Romania

4Department of Physical Education and Sports, University of Granada, 18010 Granada, Spain

5Department of Exercise Physiology, Faculty of Sport Sciences, University of Isfahan, 81746-7344 Isfahan, Iran

6HEME Research Group, Faculty of Sport Sciences, University of Extremadura, 10003 Cáceres, Spain

7Associação de Futebol de Bragança, 5300-379 Bragança, Portugal

8Faculty of Human Kinetics, University of Lisboa, 1649-004 Lisboa, Portugal

9Department of Exercise and Health Sciences, University of Taipei, 11153 Taipei, Taiwan

10Instituto de Telecomunicações, Delegação da Covilhã, 1049-001 Lisboa, Portugal

DOI: 10.31083/jomh.2021.063 Vol.17,Issue 4,September 2021 pp.207-217

Submitted: 01 May 2021 Accepted: 01 June 2021

Published: 30 September 2021

*Corresponding Author(s): Georgian Badicu E-mail:

PDF (2.21 MB)


Objectives: This study aimed to analyze within-week and within-match external load variations in male soccer players over three consecutive matches during a congested week.

Methods: The study cohort included nineteen elite professional male players (age: 26.5 ± 4.3 years) from a European First League team. Players were monitored daily over a full season using measurements collected by global positioning systems (GPSs). GPS-derived measures of total distance (TD), high-speed running (HSR), high metabolic load (HML), and maximal speed (maxSpeed) were collected during each match.

Results: TD and HML intensity were meaningfully lower during the second half of the season than the first half for all weeks (p < 0.05), regardless of the number of matches. Also, the standardized differences for both metrics presented moderate-to-strong effect sizes. Although no significant differences between halves were found for HSR or maxSpeed (p > 0.05), these measures presented inconsistently minimum-to-strong effect sizes in some matches in overall weeks.

Conclusion: The findings of this study revealed that TD and HML distances were significantly different between halves for all weeks, regardless of the number of matches. Meanwhile, HSR and maxSpeed measures presented no significant differences across matches overall.


External load; Load monitoring; Sports science; Performance; GPS

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Rui Silva,Halil Ibrahim Ceylan,Georgian Badicu,Hadi Nobari,Sílvio Afonso Carvalho,Tiago Sant’Ana,Bruno Mendes,Yung-Sheng Chen,Filipe Manuel Clemente. Match-to-match variations in external load measures during congested weeks in professional male soccer players. Journal of Men's Health. 2021. 17(4);207-217.


[1] Travassos B, Davids K, Araújo D, Esteves PT. Performance analysis in team sports: Advances from an Ecological Dynamics approach. International Journal of Performance Analysis in Sport. 2013; 13: 83–95.

[2] Clemente F, Silva R, Arslan E, Aquino R, Castillo D, Mendes B. The effects of congested fixture periods on distance-based workload indices: A full-season study in professional soccer players. Biology of Sport Vols. 2021; 38: 37–44.

[3] Hader K, Rumpf MC, Hertzog M, Kilduff LP, Girard O, Silva JR. Monitoring the Athlete Match Response: can External Load Variables Predict Post-match Acute and Residual Fatigue in Soccer? A Systematic Review with Meta-analysis. Sports Medicine Open. 2019; 5: 48.

[4] Gabbett T. The Training-Performance Puzzle: how can the Past Inform Future Training Directions? Journal of Athletic Training. 2020; 55: 874–884.

[5] Nédélec M, McCall A, Carling C, Legall F, Berthoin S, Dupont G. Recovery in soccer: part ii-recovery strategies. Sports Medicine. 2013; 43: 9–22.

[6] Impellizzeri FM, Marcora SM, Coutts AJ. Internal and External Training Load: 15 Years on. International Journal of Sports Physiology and Performance. 2019; 14: 270–273.

[7] Gabbett T, 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. British Journal of Sports Medicine. 2017; 51: 1451–1452.

[8] Malone J, Lovell R, Varley MC, Coutts AJ. Unpacking the Black Box: Applications and Considerations for Using GPS Devices in Sport. International Journal of Sports Physiology and Performance. 2017; 12: S218–S226.

[9] Akenhead R, Nassis GP. Training Load and Player Monitoring in High-Level Football: Current Practice and Perceptions. International Journal of Sports Physiology and Performance. 2017; 11: 587–593.

[10] Nédélec M, McCall A, Carling C, Legall F, Berthoin S, Dupont G. Recovery in Soccer. Sports Medicine. 2012; 42: 997–1015.

[11] Rojas-Valverde D, Gutiérrez-Vargas R, Rodríguez-Montero A, Pereira LA, Loturco I, Martín-Rodríguez S. Reduced muscle contractile function in elite young soccer players after a short-congested fixture period. Proceedings of the Institution of Mechanical Engineers. 2019; 233: 249–257.

[12] Wollin M, Thorborg K, Pizzari T. Monitoring the effect of football match congestion on hamstring strength and lower limb flexibility: Potential for secondary injury prevention? Physical Therapy in Sport. 2018; 29: 14–18.

[13] Lundberg TR, Weckström K. Fixture congestion modulates post-match recovery kinetics in professional soccer players. Research in Sports Medicine. 2018; 25: 408–420.

[14] Silva JR, Rumpf MC, Hertzog M, Castagna C, Farooq A, Girard O, et al. Acute and Residual Soccer Match-Related Fatigue: a Systematic Review and Meta-analysis. Sports Medicine. 2018; 48: 539–583.

[15] Julian R, Page RM, Harper LD. The Effect of Fixture Congestion on Performance during Professional Male Soccer Match-Play: a Systematic Critical Review with Meta-Analysis. Sports Medicine. 2021; 51: 255–273.

[16] Springham M, Williams S, Waldron M, Strudwick AJ, Mclellan C, Newton RU. Prior workload has moderate effects on high-intensity match performance in elite-level professional football players when controlling for situational and contextual variables. Journal of Sports Sciences. 2020; 38: 2279–2290.

[17] Carling C, Gall F, Dupont G. Are physical performance and injury risk in a professional soccer team in match-play affected over a prolonged period of fixture congestion? International Journal of Sports Medicine. 2012; 33: 36–42.

[18] 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 Journal of Sports Medicine. 2014; 5: 47–53.

[19] Dellal A, Lago-Peñas C, Rey E, Chamari K, Orhant E. The effects of a congested fixture period on physical performance, technical activity and injury rate during matches in a professional soccer team. British Journal of Sports Medicine. 2015; 49: 390–394.

[20] Clemente FM, Silva R, Chen YS, Aquino R, Praça GM, Paulis JC, et al. Accelerometry-workload indices concerning different levels of participation during congested fixture periods in professional soccer: A pilot study conducted over a full season. International Journal of Environmental Research and Public Health. 2021; 18: 1–9.

[21] Clemente F, Silva R, Ramirez-Campillo R, Afonso J, Mendes B, Chen Y. Accelerometry-based variables in professional soccer players: Comparisons between periods of the season and playing positions. Biology of Sport. 2020; 37: 389–403.

[22] Beato M, Coratella G, Stiff A, Iacono AD. The Validity and between-Unit Variability of GNSS Units (STATSports Apex 10 and 18 Hz) for Measuring Distance and Peak Speed in Team Sports. Frontiers in Physiology. 2018; 9: 1288.

[23] Beato M, de Keijzer KL. The inter-unit and inter-model reliability of GNSS STATSports Apex and Viper units in measuring peak speed over 5, 10, 15, 20 and 30 meters. Biology of Sport. 2019; 36: 317–321.

[24] Lutz J, Memmert D, Raabe D, Dornberger R, Donath L. Wearables for integrative performance and tactic analyses: Opportunities, chal-lenges, and future directions. International Journal of Environmental Research and Public Health. 2020; 17: 1–26.

[25] Hoppe MW, Baumgart C, Polglaze T, Freiwald J. Validity and reliability of GPS and LPS for measuring distances covered and sprint mechanical properties in team sports. PloS ONE. 2018; 13: e0192708.

[26] Ferguson CJ. An Effect Size Primer: A Guide for Clinicians and Researchers. Professional Psychology: Research and Practice. 2009; 40: 532–538.

[27] Carling C, Dupont G. Are declines in physical performance associated with a reduction in skill-related performance during professional soccer match-play? Journal of Sports Sciences. 2011; 29: 63–71.

[28] Paul D, Bradley P, Nassis G. Factors affecting match running perfor-mance of elite soccer players: shedding some light on the complexity. International Journal of Sports Physiology and Performance. 2015; 10: 516–519.

[29] Guerrero-Calderón B, Klemp M, Morcillo JA, Memmert D. How does the workload applied during the training week and the contextual factors affect the physical responses of professional soccer players in the match? The International Journal of Sports Science & Coaching. 2021; 1–10.

[30] Soroka A, Lago-Peñas C. The effect of a succession of matches on the physical performance of elite football players during the World Cup Brazil 2014. International Journal of Performance Analysis in Sport. 2016; 16: 434–441.

[31] Andrzejewski M, Konarski MJ, Chmura J, Pluta B. Changes in the activity profiles of soccer players over a three-match training micro cycle. International Journal of Performance Analysis in Sport. 2014; 14: 814–828.

[32] Duhig S, Shield AJ, Opar D, Gabbett TJ, Ferguson C, Williams M. Effect of high-speed running on hamstring strain injury risk. British Journal of Sports Medicine. 2016; 50: 1536–1540.

[33] Malone S, Owen A, Mendes B, Hughes B, Collins K, Gabbett TJ. High-speed running and sprinting as an injury risk factor in soccer: can well-developed physical qualities reduce the risk? Journal of Science and Medicine in Sport. 2018; 21: 257–262.

[34] Osgnach C, Poser S, Bernardini R, Rinaldo R, di Prampero PE. Energy cost and metabolic power in elite soccer: a new match analysis approach. Medicine and Science in Sports and Exercise. 2010; 42: 170–178.

[35] Tierney PJ, Young A, Clarke ND, Duncan MJ. Match play demands of 11 versus 11 professional football using Global Positioning System tracking: Variations across common playing formations. Human Movement Science. 2016; 49: 1–8.

[36] Anderson L, Orme P, Di Michele R, Close GL, Milsom J, Morgans R, et al. Quantification of Seasonal-Long Physical Load in Soccer Players with Different Starting Status from the English Premier League: Implications for Maintaining Squad Physical Fitness. International Journal of Sports Physiology and Performance. 2016; 11: 1038–1046.

[37] Malone S, Roe M, Doran DA, Gabbett TJ, Collins K. High chronic training loads and exposure to bouts of maximal velocity running reduce injury risk in elite Gaelic football. Journal of Science and Medicine in Sport. 2017; 20: 250–254.

[38] Chmura P, Konefał M, Chmura J, Kowalczuk E, Zając T, Rokita A, et al. Match outcome and running performance in different intensity ranges among elite soccer players. Biology of Sport. 2018; 35: 197–203.

[39] Buchheit M, Simpson BM. Player-Tracking Technology: Half-Full or Half-Empty Glass? International Journal of Sports Physiology and Performance. 2017; 12: S2–35–S2–41.

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