Relationships Between Training Load Indicators and Training Outcomes in Professional Soccer

Abstract

Background

In professional senior soccer, training load monitoring is used to ensure an optimal workload to maximize physical fitness and prevent injury or illness. However, to date, different training load indicators are used without a clear link to training outcomes.

Objective

The aim of this systematic review was to identify the state of knowledge with respect to the relationship between training load indicators and training outcomes in terms of physical fitness, injury, and illness.

Methods

A systematic search was conducted in four electronic databases (CINAHL, PubMed, SPORTDiscus, and Web of Science). Training load was defined as the amount of stress over a minimum of two training sessions or matches, quantified in either external (e.g., duration, distance covered) or internal load (e.g., heart rate [HR]), to obtain a training outcome over time.

Results

A total of 6492 records were retrieved, of which 3304 were duplicates. After screening the titles, abstracts and full texts, we identified 12 full-text articles that matched our inclusion criteria. One of these articles was identified through additional sources. All of these articles used correlations to examine the relationship between load indicators and training outcomes. For pre-season, training time spent at high intensity (i.e., >90 % of maximal HR) was linked to positive changes in aerobic fitness. Exposure time in terms of accumulated training, match or combined training, and match time showed both positive and negative relationships with changes in fitness over a season. Muscular perceived exertion may indicate negative changes in physical fitness. Additionally, it appeared that training at high intensity may involve a higher injury risk. Detailed external load indicators, using electronic performance and tracking systems, are relatively unexamined. In addition, most research focused on the relationship between training load indicators and changes in physical fitness, but less on injury and illness.

Conclusion

HR indicators showed relationships with positive changes in physical fitness during pre-season. In addition, exposure time appeared to be related to positive and negative changes in physical fitness. Despite the availability of more detailed training load indicators nowadays, the evidence about the usefulness in relation to training outcomes is rare. Future research should implement continuous monitoring of training load, combined with the individual characteristics, to further examine their relationship with physical fitness, injury, and illness.

This is a preview of subscription content, access via your institution.

Fig. 1

References

  1. 1.

    Smith DJ. A framework for understanding the training process leading to elite performance. Sports Med. 2003;33(15):1103–26. doi:10.2165/00007256-200333150-00003.

    Article  PubMed  Google Scholar 

  2. 2.

    Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. J Strength Cond Res. 2001;15(1):109–15. doi:10.1519/00124278-200102000-00019.

    CAS  PubMed  Google Scholar 

  3. 3.

    Kenttä G, Hassmén P. Overtraining and recovery: a conceptual model. Sports Med. 1998;26(1):1–16. doi:10.2165/00007256-199826010-00001.

    Article  PubMed  Google Scholar 

  4. 4.

    Ekstrand J, Hägglund M, Waldén M. Injury incidence and injury patterns in professional football: the UEFA injury study. Br J Sports Med. 2011;45(7):553–8. doi:10.1136/bjsm.2009.060582.

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Ekstrand J, Hägglund M, Waldén M. Epidemiology of muscle injuries in professional football (soccer). Am J Sports Med. 2011;39(6):1226–32. doi:10.1177/0363546510395879.

    Article  PubMed  Google Scholar 

  6. 6.

    Orhant E, Carling C, Cox A. A three-year prospective study of illness in professional soccer players. Res Sports Med. 2010;18(3):199–204. doi:10.1080/15438627.2010.490462.

    Article  PubMed  Google Scholar 

  7. 7.

    Bush M, Barnes C, Archer DT, et al. Evolution of match performance parameters for various playing positions in the English Premier League. Hum Mov Sci. 2015;39:1–11. doi:10.1016/j.humov.2014.10.003.

    Article  PubMed  Google Scholar 

  8. 8.

    Bengtsson H, Ekstrand J, Hägglund M. Muscle injury rates in professional football increase with fixture congestion: an 11-year follow-up of the UEFA Champions League injury study. Br J Sports Med. 2013;47(12):743–7. doi:10.1136/bjsports-2013-092383.

    Article  PubMed  Google Scholar 

  9. 9.

    Dupont G, Nedelec M, McCall A, et al. Effect of 2 soccer matches in a week on physical performance and injury rate. Am J Sports Med. 2010;38(9):1752–8. doi:10.1177/0363546510361236.

    Article  PubMed  Google Scholar 

  10. 10.

    Ekstrand J, Hägglund M, Kristenson K, et al. Fewer ligament injuries but no preventive effect on muscle injuries and severe injuries: an 11-year follow-up of the UEFA Champions League injury study. Br J Sports Med. 2013;47(12):732–7. doi:10.1136/bjsports-2013-092394.

    Article  PubMed  Google Scholar 

  11. 11.

    Impellizzeri FM, Rampinini E, Marcora SM. Physiological assessment of aerobic training in soccer. J Sports Sci. 2005;23(6):583–92. doi:10.1080/02640410400021278.

    Article  PubMed  Google Scholar 

  12. 12.

    Viru A, Viru M. Nature of training effects. In: Garrett WE, Kirkendall DT, editors. Exercise and sport science. Philadelphia: Lippincott Williams & Wilkins; 2000. p. 67–95.

    Google Scholar 

  13. 13.

    Bouchard C, Rankinen T. Individual differences in response to regular physical activity. Med Sci Sports Exerc. 2001;33(6 Suppl):S446–51. doi:10.1097/00005768-200106001-00013 (discussion S52–3).

  14. 14.

    Bahr R, Krosshaug T. Understanding injury mechanisms: a key component of preventing injuries in sport. Br J Sports Med. 2005;39(6):324–9. doi:10.1136/bjsm.2005.018341.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Halson SL. Monitoring training load to understand fatigue in athletes. Sports Med. 2014;44(Suppl 2):S139–47. doi:10.1007/s40279-014-0253-z.

    Article  PubMed  Google Scholar 

  16. 16.

    Foster C. Monitoring training in athletes with reference to overtraining syndrome. Med Sci Sports Exerc. 1998;30(7):1164–8. doi:10.1097/00005768-199807000-00023.

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Jobson SA, Passfield L, Atkinson G, et al. The analysis and utilization of cycling training data. Sports Med. 2009;39(10):833–44. doi:10.2165/11317840-000000000-00000.

    Article  PubMed  Google Scholar 

  18. 18.

    McGregor SJ, Weese RK, Ratz IK. Performance modeling in an olympic 1500-m finalist: a practical approach. J Strength Cond Res. 2009;23(9):2515–23. doi:10.1519/JSC.0b013e3181bf88be.

    Article  PubMed  Google Scholar 

  19. 19.

    Dellaserra CL, Gao Y, Ransdell L. Use of integrated technology in team sports: a review of opportunities, challenges, and future directions for athletes. J Strength Cond Res. 2014;28(2):556–73. doi:10.1519/JSC.0b013e3182a952fb.

    Article  PubMed  Google Scholar 

  20. 20.

    Aughey RJ. Applications of GPS technologies to field sports. Int J Sports Physiol Perform. 2011;6(3):295–310.

    Article  PubMed  Google Scholar 

  21. 21.

    Cummins C, Orr R, O’Connor H, et al. Global positioning systems (GPS) and microtechnology sensors in team sports: a systematic review. Sports Med. 2013;43(10):1025–42. doi:10.1007/s40279-013-0069-2.

    Article  PubMed  Google Scholar 

  22. 22.

    Borresen J, Lambert MI. The quantification of training load, the training response and the effect on performance. Sports Med. 2009;39(9):779–95. doi:10.2165/11317780-000000000-00000.

    Article  PubMed  Google Scholar 

  23. 23.

    Clarke DC, Skiba PF. Rationale and resources for teaching the mathematical modeling of athletic training and performance. Adv Physiol Educ. 2013;37(2):134–52. doi:10.1152/advan.00078.2011.

    Article  PubMed  Google Scholar 

  24. 24.

    Taha T, Thomas SG. Systems modelling of the relationship between training and performance. Sports Med. 2003;33(14):1061–73. doi:10.2165/00007256-200333140-00003.

    Article  PubMed  Google Scholar 

  25. 25.

    Wallace LK, Slattery KM, Coutts AJ. A comparison of methods for quantifying training load: relationships between modelled and actual training responses. Eur J Appl Physiol. 2014;114(1):11–20. doi:10.1007/s00421-013-2745-1.

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Calvert TW, Banister EW, Savage MV, et al. A systems model of the effects of training on physical performance. IEEE Trans Syst Man Cybern. 1976;2:94–102. doi:10.1109/TSMC.1976.5409179.

    Article  Google Scholar 

  27. 27.

    Banister EW, Calvert TW, Savage MV, et al. A systems model of training for athletic performance. Aust J Sports Med. 1975;7:57–61.

    Google Scholar 

  28. 28.

    Busso T. Variable dose-response relationship between exercise training and performance. Med Sci Sports Exerc. 2003;35(7):1188–95. doi:10.1249/01.MSS.0000074465.13621.37.

    Article  PubMed  Google Scholar 

  29. 29.

    Perl J. PerPot: a metamodel for simulation of load performance interaction. Eur J Sport Sci. 2001;1(2):1–13. doi:10.1080/17461390100071202.

    Article  Google Scholar 

  30. 30.

    Edelmann-Nusser J, Hohmann A, Henneberg B. Modeling and prediction of competitive performance in swimming upon neural networks. Eur J Sport Sci. 2002;2(2):1–10. doi:10.1080/17461390200072201.

    Article  Google Scholar 

  31. 31.

    Colby MJ, Dawson B, Heasman J, et al. Accelerometer and GPS-derived running loads and injury risk in elite Australian footballers. J Strength Cond Res. 2014;28(8):2244–52. doi:10.1519/JSC.0000000000000362.

    Article  PubMed  Google Scholar 

  32. 32.

    Gabbett TJ. Reductions in pre-season training loads reduce training injury rates in rugby league players. Br J Sports Med. 2004;38(6):743–9. doi:10.1136/bjsm.2003.008391.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Gabbett TJ. The development and application of an injury prediction model for noncontact, soft-tissue injuries in elite collision sport athletes. J Strength Cond Res. 2010;24(10):2593–603. doi:10.1519/JSC.0b013e3181f19da4.

    Article  PubMed  Google Scholar 

  34. 34.

    Gabbett TJ, Ullah S. Relationship between running loads and soft-tissue injury in elite team sport athletes. J Strength Cond Res. 2012;26(4):953–60. doi:10.1519/JSC.0b013e3182302023.

    Article  PubMed  Google Scholar 

  35. 35.

    Rogalski B, Dawson B, Heasman J, et al. Training and game loads and injury risk in elite Australian footballers. J Sci Med Sport. 2013;16(6):499–503. doi:10.1016/j.jsams.2012.12.004.

    Article  PubMed  Google Scholar 

  36. 36.

    Veugelers KR, Young WB, Fahrner B, et al. Different methods of training load quantification and their relationship to injury and illness in elite Australian football. J Sci Med Sport. 2016;19(1):24–8. doi:10.1016/j.jsams.2015.01.001.

    Article  PubMed  Google Scholar 

  37. 37.

    Akubat I, Patel E, Barrett S, et al. Methods of monitoring the training and match load and their relationship to changes in fitness in professional youth soccer players. J Sports Sci. 2012;30(14):1473–80. doi:10.1080/02640414.2012.712711.

    Article  PubMed  Google Scholar 

  38. 38.

    Brink MS, Nederhof E, Visscher C, et al. Monitoring load, recovery, and performance in young elite soccer players. J Strength Cond Res. 2010;24(3):597–603. doi:10.1519/JSC.0b013e3181c4d38b.

    Article  PubMed  Google Scholar 

  39. 39.

    Brink MS, Visscher C, Arends S, et al. Monitoring stress and recovery: new insights for the prevention of injuries and illnesses in elite youth soccer players. Br J Sports Med. 2010;44(11):809–15. doi:10.1136/bjsm.2009.069476.

    Article  PubMed  Google Scholar 

  40. 40.

    Gabbett TJ, Whyte DG, Hartwig TB, et al. The relationship between workloads, physical performance, injury and illness in adolescent male football players. Sports Med. 2014;44(7):989–1003. doi:10.1007/s40279-014-0179-5.

    Article  PubMed  Google Scholar 

  41. 41.

    Owen AL, Wong DP, Dunlop G, et al. High-intensity training and salivary immunoglobulin-A responses in professional top-level soccer players: effect of training intensity. J Strength Cond Res. 2014. doi:10.1519/JSC.0000000000000380 (Epub 2014 Jan 19).

    Google Scholar 

  42. 42.

    Castagna C, Impellizzeri FM, Chaouachi A, et al. Effect of training intensity distribution on aerobic fitness variables in elite soccer players: a case study. J Strength Cond Res. 2011;25(1):66–71. doi:10.1519/JSC.0b013e3181fef3d3.

    Article  PubMed  Google Scholar 

  43. 43.

    Castagna C, Impellizzeri FM, Chaouachi A, et al. Preseason variations in aerobic fitness and performance in elite-standard soccer players: a team study. J Strength Cond Res. 2013;27(11):2959–65. doi:10.1519/JSC.0b013e31828d61a8.

    Article  PubMed  Google Scholar 

  44. 44.

    Manzi V, Bovenzi A, Impellizzeri MF, et al. Individual training-load and aerobic-fitness variables in premiership soccer players during the precompetitive season. J Strength Cond Res. 2013;27(3):631–6. doi:10.1519/JSC.0b013e31825dbd81.

    Article  PubMed  Google Scholar 

  45. 45.

    Los Arcos A, Martínez-Santos R, Yanci J, et al. Negative associations between perceived training load, volume and changes in physical fitness in professional soccer players. J Sports Sci Med. 2015;14(2):394–401.

  46. 46.

    Thorpe RT, Strudwick AJ, Buchheit M, et al. Monitoring fatigue during the in-season competitive phase in elite soccer players. Int J Sports Physiol Perform. 2015;10(8):958–64. doi:10.1123/ijspp.2015-0004.

    Article  PubMed  Google Scholar 

  47. 47.

    Los Arcos A, Yanci J, Mendiguchia J, et al. Rating of muscular and respiratory perceived exertion in professional soccer players. J Strength Cond Res. 2014;28(11):3280–88. doi:10.1519/JSC.0000000000000540.

  48. 48.

    Carling C, Orhant E. Variation in body composition in professional soccer players: interseasonal and intraseasonal changes and the effects of exposure time and player position. J Strength Cond Res. 2010;24(5):1332–9. doi:10.1519/JSC.0b013e3181cc6154.

    Article  PubMed  Google Scholar 

  49. 49.

    Silva JR, Magalhães JF, Ascensão AA, et al. Individual match playing time during the season affects fitness-related parameters of male professional soccer players. J Strength Cond Res. 2011;25(10):2729–39. doi:10.1519/JSC.0b013e31820da078.

    Article  PubMed  Google Scholar 

  50. 50.

    Silva JR, Rebelo A, Marques F, et al. Biochemical impact of soccer: an analysis of hormonal, muscle damage, and redox markers during the season. Appl Physiol Nutr Metab. 2014;39(4):432–8. doi:10.1139/apnm-2013-0180.

    CAS  Article  PubMed  Google Scholar 

  51. 51.

    Owen AL, Forsyth JJ, Wong DP, et al. Heart rate-based training intensity and its impact on injury incidence amongs elite-level professional soccer players. J Strength Cond Res. 2015;29(6):1705–12. doi:10.1519/JSC.0000000000000810.

    Article  PubMed  Google Scholar 

  52. 52.

    Mallo J, Dellal A. Injury risk in professional football players with special reference to the playing position and training periodization. J Sports Med Phys Fit. 2012;52(6):631–8.

    CAS  Google Scholar 

  53. 53.

    Buchheit M. Monitoring training status with HR measures: do all roads lead to Rome? Front Physiol. 2014;5:73. doi:10.3389/fphys.2014.00073.

    Article  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Haugen TA, Tønnessen E, Seiler S. Anaerobic performance testing of professional soccer players 1995–2010. Int J Sports Physiol Perform. 2013;8(2):148–56.

    Article  PubMed  Google Scholar 

  55. 55.

    Buchheit M, Laursen PB. High-intensity interval training, solutions to the programming puzzle: Part I: cardiopulmonary emphasis. Sports Med. 2013;43(5):313–38. doi:10.1007/s40279-013-0029-x.

    Article  PubMed  Google Scholar 

  56. 56.

    Buchheit M, Laursen PB. High-intensity interval training, solutions to the programming puzzle. Part II: anaerobic energy, neuromuscular load and practical applications. Sports Med. 2013;43(10):927–54. doi:10.1007/s40279-013-0066-5.

    Article  PubMed  Google Scholar 

  57. 57.

    Alexandre D, da Silva CD, Hill-Haas S, et al. Heart rate monitoring in soccer: interest and limits during competitive match play and training, practical application. J Strength Cond Res. 2012;26(10):2890–906. doi:10.1519/JSC.0b013e3182429ac7.

    Article  PubMed  Google Scholar 

  58. 58.

    Sporis G, Jovanovic M, Omrcen D, et al. Can the official soccer game be considered the most important contribution to player’s physical fitness level? J Sports Med Phys Fit. 2011;51(3):374–80.

    CAS  Google Scholar 

  59. 59.

    Morgans R, Orme P, Anderson L, et al. An intensive winter fixture schedule induces a transient fall in salivary IgA in English premier league soccer players. Res Sports Med. 2014;22(4):346–54. doi:10.1080/15438627.2014.944641.

    Article  PubMed  Google Scholar 

  60. 60.

    Meeusen R, Duclos M, Foster C, et al. Prevention, diagnosis, and treatment of the overtraining syndrome: joint consensus statement of the European College of Sport Science and the American College of Sports Medicine. Med Sci Sports Exerc. 2013;45(1):186–205. doi:10.1249/MSS.0b013e318279a10a.

    Article  PubMed  Google Scholar 

  61. 61.

    Milanez VF, Ramos SP, Okuno NM, et al. Evidence of a non-linear dose-response relationship between training load and stress markers in elite female futsal players. J Sports Sci Med. 2014;13(1):22–9.

    PubMed  PubMed Central  Google Scholar 

  62. 62.

    Andersson H, Raastad T, Nilsson J, et al. Neuromuscular fatigue and recovery in elite female soccer: effects of active recovery. Med Sci Sports Exerc. 2008;40(2):372–80. doi:10.1249/mss.0b013e31815b8497.

    Article  PubMed  Google Scholar 

  63. 63.

    Gastin PB, Meyer D, Huntsman E, et al. Increase in injury risk with low body mass and aerobic-running fitness in elite Australian football. Int J Sports Physiol Perform. 2015;10(4):458–63. doi:10.1123/ijspp.2014-0257.

    Article  PubMed  Google Scholar 

  64. 64.

    Carling C, Le 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? Int J Sports Med. 2012;33(1):36–42. doi:10.1055/s-0031-1283190.

    CAS  Article  PubMed  Google Scholar 

  65. 65.

    Hulin BT, Gabbett TJ, Lawson DW, et al. The acute:chronic workload ratio predicts injury: high chronic workload may decrease injury risk in elite rugby league players. Br J Sports Med. 2016;50(4):231–6. doi:10.1136/bjsports-2015-094817.

    Article  PubMed  Google Scholar 

  66. 66.

    Cross MJ, Williams S, Trewartha G, et al. The influence of in-season training loads on injury risk in professional rugby union. Int J Sports Physiol Perform. 2016;11(3):350–5. doi:10.1123/ijspp.2015-0187.

    Article  PubMed  Google Scholar 

  67. 67.

    Nassis GP, Gabbett TJ. Is workload associated with injuries and performance in elite football? A call for action. Br J Sports Med. 2016. doi:10.1136/bjsports-2016-095988 (Epub 2016 Mar 3).

    Google Scholar 

  68. 68.

    Nédélec M, McCall A, Carling C, et al. Recovery in soccer: part I—post-match fatigue and time course of recovery. Sports Med. 2012;42(12):997–1015. doi:10.2165/11635270-000000000-00000.

    PubMed  Google Scholar 

  69. 69.

    Akenhead R, Nassis GP. Training load and player monitoring in high-level football: current practice and perceptions. Int J Sports Physiol Perform. 2015. doi: 10.1123/ijspp.2015-0331

  70. 70.

    Hägglund M, Waldén M, Bahr R, et al. Methods for epidemiological study of injuries to professional football players: developing the UEFA model. Br J Sports Med. 2005;39(6):340–6. doi:10.1136/bjsm.2005.018267.

    Article  PubMed  PubMed Central  Google Scholar 

  71. 71.

    Fuller CW, Ekstrand J, Junge A, et al. Consensus statement on injury definitions and data collection procedures in studies of football (soccer) injuries. Br J Sports Med. 2006;40(3):193–201. doi:10.1136/bjsm.2005.025270.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Arne Jaspers.

Ethics declarations

Funding

This review was part of a research project supported by a research grant from the Agency for Innovation by Science and Technology–IWT, Belgium (IWT 130841).

Conflict of interest

Arne Jaspers, Michel Brink, Steven Probst, Wouter Frencken, and Werner Helsen declare that they have no conflicts of interest relevant to the content of this review.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Jaspers, A., Brink, M.S., Probst, S.G.M. et al. Relationships Between Training Load Indicators and Training Outcomes in Professional Soccer. Sports Med 47, 533–544 (2017). https://doi.org/10.1007/s40279-016-0591-0

Download citation

Keywords

  • Physical Fitness
  • Aerobic Fitness
  • Training Load
  • Internal Load
  • Training Outcome