Skip to main content

The Relationship Between Training Load and Injury, Illness and Soreness: A Systematic and Literature Review

Abstract

Background

Clinically it is understood that rapid increases in training loads expose an athlete to an increased risk of injury; however, there are no systematic reviews to qualify this statement.

Objective

The aim of this systematic review was to determine training and competition loads, and the relationship between injury, illness and soreness.

Methods

The MEDLINE, SPORTDiscus, CINAHL and EMBASE databases were searched using a predefined search strategy. Studies were included if they analysed the relationship between training or competition loads and injury or illness, and were published prior to October 2015. Participants were athletes of any age or level of competition. The quality of the studies included in the review was evaluated using the Newcastle–Ottawa Scale (NOS). The level of evidence was defined as strong, ‘consistent findings among multiple high-quality randomised controlled trials (RCTs)’; moderate, ‘consistent findings among multiple low-quality RCTs and/or non-randomised controlled trials (CCTs) and/or one high-quality RCT’; limited, ‘one low-quality RCT and/or CCTs, conflicting evidence’; conflicting, ‘inconsistent findings among multiple trials (RCTs and/or CCTs)’; or no evidence, ‘no RCTs or CCTs’.

Results

A total of 799 studies were identified; 23 studies met the inclusion criteria, and a further 12 studies that were not identified in the search but met the inclusion criteria were subsequently added to the review. The largest number of studies evaluated the relationship between injuries and training load in rugby league players (n = 9) followed by cricket (n = 5), football (n = 3), Australian Football (n = 3), rugby union (n = 2),volleyball (n = 2), baseball (n = 2), water polo (n = 1), rowing (n = 1), basketball (n = 1), swimming (n = 1), middle-distance runners (n = 1) and various sports combined (n = 1). Moderate evidence for a significant relationship was observed between training loads and injury incidence in the majority of studies (n = 27, 93 %). In addition, moderate evidence exists for a significant relationship between training loads and illness incidence (n = 6, 75 %). Training loads were reported to have a protective effect against injury (n = 9, 31 %) and illness (n = 1, 13 %). The median (range) NOS score for injury and illness was 8 (5–9) and 6 (5–9), respectively.

Limitations

A limitation of this systematic review was the a priori search strategy. Twelve further studies were included that were not identified in the search strategy, thus potentially introducing bias. The quality assessment was completed by only one author.

Conclusions

The results of this systematic review highlight that there is emerging moderate evidence for the relationship between the training load applied to an athlete and the occurrence of injury and illness.

Implications

The training load applied to an athlete appears to be related to their risk of injury and/or illness. Sports science and medicine professionals working with athletes should monitor this load and avoid acute spikes in loads. It is recommended that internal load as the product of the rate of perceived exertion (10-point modified Borg) and duration be used when determining injury risk in team-based sports. External loads measured as throw counts should also be monitored and collected across a season to determine injury risk in throwing populations. Global positioning system-derived distances should be utilised in team sports, and injury monitoring should occur for at least 4 weeks after spikes in loads.

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

Fig. 1

References

  1. Gamble P. Reducing injury in elite sport-is simply restricting workloads really the answer? NZ J Sports Med. 2013;40(1):34–6.

    Google Scholar 

  2. Dennis R, Farhart R, Goumas C, et al. Bowling workload and the risk of injury in elite cricket fast bowlers. J Sci Med Sport. 2003;6(3):359–67.

    CAS  Article  PubMed  Google Scholar 

  3. Hulin BT, Gabbett TJ, Blanch P, et al. Spikes in acute workload are associated with increased injury risk in elite cricket fast bowlers. Br J Sports Med. 2014;38:708–12.

    Article  Google Scholar 

  4. Busso T. Variable dose-response relationship between exercise training and performance. Med Sci Sports Exerc. 2003;35(7):1188–95.

    Article  PubMed  Google Scholar 

  5. Hägglund M, Waldén M, Magnusson H, et al. Injuries affect team performance negatively in professional football: an 11-year follow-up of the UEFA Champions League injury study. Br J Sports Med. 2013;47(12):738–42.

    Article  PubMed  Google Scholar 

  6. Ekstrand J, Waldén M, Hägglund M. A congested football calendar and the wellbeing of players: correlation between match exposure of European footballers before the World Cup 2002 and their injuries and performances during that World Cup. Br J Sports Med. 2004;38(4):493–7.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  7. 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.

    Article  PubMed  Google Scholar 

  8. Halson SL. Monitoring training load to understand fatigue in athletes. Sports Med. 2014;44(2):139–47.

    Article  PubMed Central  Google Scholar 

  9. Foster C. Monitoring training in athletes with reference to overtraining syndrome. Med Sci Sports Exerc. 1998;30(7):1164–8.

    CAS  Article  PubMed  Google Scholar 

  10. Foster C, Florhaug JA, Franklin J, et al. A new approach to monitoring exercise training. J Strength Cond Res. 2001;15(1):109–15.

    CAS  PubMed  Google Scholar 

  11. Piggott B. The relationship between training load and incidence of injury and illness over a pre-season at an Australian Football League Club. J Aust Strength Cond. 2009;17(3):4–17.

    Google Scholar 

  12. Hellard P, Avalos M, Guimaraes F, et al. Training-related risk of common illnesses in elite swimmers over a 4-yr period. Med Sci Sports Exerc. 2015;47(4):698–707.

    Article  PubMed  Google Scholar 

  13. 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.

    Article  PubMed  Google Scholar 

  14. Cross M, 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. 2015. (Epub 26 Aug 2015).

  15. Lyman S, Fleisig GS, Andrews JR, et al. Effect of pitch type, pitch count, and pitching mechanics on risk of elbow and shoulder pain in youth baseball pitchers. Am J Sports Med. 2002;30(4):463–8.

    PubMed  Google Scholar 

  16. Lyman S, Fleisig GS, Waterbor JW, et al. Longitudinal study of elbow and shoulder pain in youth baseball pitchers. Med Sci Sports Exerc. 2001;33(11):1803–10.

    CAS  Article  PubMed  Google Scholar 

  17. Banister EW. Modeling elite athletic performance. In: Green HJ, editor. Physiological testing of the high-performance athlete. Champaign: Human Kinetics Books; 1991. p. 403–24.

    Google Scholar 

  18. Banister EW, Calvert TW. Planning for future performance: implications for long term training. Can J Appl Sport Sci. 1980;5(3):170–6.

    CAS  PubMed  Google Scholar 

  19. 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. 2015. (Epub 28 Oct 2015).

  20. 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.

    Article  PubMed  Google Scholar 

  21. Timpka T, Jacobsson J, Ekberg J, et al. Meta-narrative analysis of sports injury reporting practices based on the Injury Definitions Concept Framework (IDCF): a review of consensus statements and epidemiological studies in athletics (track and field). J Sci Med Sport. 2015;18(6):643–50.

    Article  PubMed  Google Scholar 

  22. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Fuller CW, Ekstrand J, Junge A, et al. Consensus statement on injury definitions and data collection procedures in studies of football (soccer) injuries. Scand J Med Sci Sports. 2006;16(2):83–92.

    CAS  Article  PubMed  Google Scholar 

  24. Fuller C, Laborde F, Leather R, et al. International rugby board rugby world cup 2007 injury surveillance study. Br J Sports Med. 2008;42(6):452–9.

    CAS  Article  PubMed  Google Scholar 

  25. Pluim BM, Fuller CW, Batt ME, et al. Consensus statement on epidemiological studies of medical conditions in tennis. Br J Sports Med. 2009;43(12):893–7.

    CAS  Article  PubMed  Google Scholar 

  26. Junge A, Engebretsen L, Alonso JM, et al. Injury surveillance in multi-sport events: the International Olympic Committee approach. Br J Sports Med. 2008;42(6):413–21.

    CAS  Article  PubMed  Google Scholar 

  27. Timpka T, Alonso J-M, Jacobsson J, et al. Injury and illness definitions and data collection procedures for use in epidemiological studies in athletics (track and field): consensus statement. Br J Sports Med. 2014;48(7):483–90.

    Article  PubMed  Google Scholar 

  28. Clarsen B, Krosshaug T, Bahr R. Overuse injuries in professional road cyclists. Am J Sports Med. 2010;38(12):2494–501.

    Article  PubMed  Google Scholar 

  29. Clarsen B, Myklebust G, Bahr R. Development and validation of a new method for the registration of overuse injuries in sports injury epidemiology: the Oslo Sports Trauma Research Centre (OSTRC) Overuse Injury Questionnaire. Br J Sports Med. 2013;47(8):495–502.

    Article  PubMed  Google Scholar 

  30. Timpka T, Jacobsson J, Bickenbach J, et al. What is a sports injury? Sports Med. 2014;44(4):423–38.

    Article  PubMed  Google Scholar 

  31. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151(4):264–9.

    Article  PubMed  Google Scholar 

  32. 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.

    Article  PubMed  Google Scholar 

  33. Wells G, Shea B, O’Connell D, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. 2000. Available at: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 17 Oct 2015.

  34. Quigley JM, Thompson JC, Halfpenny N, et al. Critical appraisal of non-randomized controlled studies: a review of recommended and commonly used tools. Value Health. 2014;17(3):A203.

    Article  Google Scholar 

  35. Higgins JP, Green S. Cochrane handbook for systematic reviews of interventions. New York: Wiley Online Library; 2008.

    Book  Google Scholar 

  36. Van Tulder M, Furlan A, Bombardier C, et al. Updated method guidelines for systematic reviews in the Cochrane Collaboration Back Review Group. Spine. 2003;28(12):1290–9.

    PubMed  Google Scholar 

  37. Phillips B, Ball C, Sackett D, et al. Oxford centre for evidence-based medicine—levels of evidence. CEBM levels of evidence (March 2009). Available at: http://www.cebm.net/oxford-centre-evidence-based-medicine-levels-evidence-march-2009/. Accessed 17 Oct 2015

  38. Bahr MA, Bahr R. Jump frequency may contribute to risk of jumper’s knee: a study of interindividual and sex differences in a total of 11,943 jumps video recorded during training and matches in young elite volleyball players. Br J Sports Med. 2014;48(17):1322–6.

    Article  PubMed  Google Scholar 

  39. Visnes H, Bahr R. Training volume and body composition as risk factors for developing jumper’s knee among young elite volleyball players. Scand J Med Sci Sports. 2013;23(5):607–13.

    CAS  PubMed  Google Scholar 

  40. Gabbett TJ. Influence of training and match intensity on injuries in rugby league. J Sports Sci. 2004;22(5):409–17.

    Article  PubMed  Google Scholar 

  41. 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.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  42. Gabbett TJ, Domrow N. Risk factors for injury in subelite rugby league players. Am J Sports Med. 2005;33(3):428–34.

    Article  PubMed  Google Scholar 

  43. Gabbett TJ, Domrow N. Relationships between training load, injury, and fitness in sub-elite collision sport athletes. J Sports Sci. 2007;25(13):1507–19.

    Article  PubMed  Google Scholar 

  44. Killen NM, Gabbett TJ, Jenkins DG. Training loads and incidence of injury during the preseason in professional rugby league players. J Strength Cond Res. 2010;24(8):2079–84.

    Article  PubMed  Google Scholar 

  45. 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.

    Article  PubMed  Google Scholar 

  46. Gabbett TJ, Jenkins DG. Relationship between training load and injury in professional rugby league players. J Sci Med Sport. 2011;14(3):204–9.

    Article  PubMed  Google Scholar 

  47. Orchard JW, James T, Portus M, et al. Fast bowlers in cricket demonstrate up to 3-to 4-week delay between high workloads and increased risk of injury. Am J Sports Med. 2009;37(6):1186–92.

    Article  PubMed  Google Scholar 

  48. Orchard JW, Blanch P, Paoloni J, et al. Cricket fast bowling workload patterns as risk factors for tendon, muscle, bone and joint injuries. Br J Sports Med. 2015;49:1064–8.

    Article  PubMed  Google Scholar 

  49. Dennis R, Finch CF, Farhart P. Is bowling workload a risk factor for injury to Australian junior cricket fast bowlers? Br J Sports Med. 2005;39(11):843–6.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  50. 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.

    Article  PubMed  Google Scholar 

  51. Lovell G, Galloway HR, Hopkins W, et al. Osteitis pubis and assessment of bone marrow edema at the pubic symphysis with MRI in an elite junior male soccer squad. Clin J Sport Med. 2006;16(2):117–22.

    Article  PubMed  Google Scholar 

  52. Ehrmann FE, Duncan CS, Sindhusake D, et al. GPS and injury prevention in professional soccer. J Strength Cond Res. 2015. (Epub 11 Jul 2015).

  53. Wilson F, Gissane C, Gormley J, et al. A 12-month prospective cohort study of injury in international rowers. Br J Sports Med. 2010;44(3):207–14.

    CAS  Article  PubMed  Google Scholar 

  54. Wheeler K, Kefford T, Mosler A, et al. The volume of goal shooting during training can predict shoulder soreness in elite female water polo players. J Sci Med Sport. 2013;16(3):255–8.

    Article  PubMed  Google Scholar 

  55. Anderson L, Triplett-Mcbride T, Foster C, et al. Impact of training patterns on incidence of illness and injury during a women’s collegiate basketball season. J Strength Cond Res. 2003;17(4):734–8.

    PubMed  Google Scholar 

  56. Brooks JHM, Fuller CW, Kemp SPT, et al. An assessment of training volume in professional rugby union and its impact on the incidence, severity, and nature of match and training injuries. J Sports Sci. 2008;26(8):863–73.

    Article  PubMed  Google Scholar 

  57. Malisoux L, Frisch A, Urhausen A, et al. Monitoring of sport participation and injury risk in young athletes. J Sci Med Sport. 2013;16(6):504–8.

    Article  PubMed  Google Scholar 

  58. Fortington LV, Berry J, Buttifant D, et al. Shorter time to first injury in first year professional football players: a cross-club comparison in the Australian Football League. J Sci Med Sport. 2016;19(1):18–23.

    Article  PubMed  Google Scholar 

  59. Fricker PA, Pyne DB, Saunders PU, et al. Influence of training loads on patterns of illness in elite distance runners. Clin J Sport Med. 2005;15(4):244–50.

    Article  Google Scholar 

  60. Fleisig GS, Andrews JR, Cutter GR, et al. Risk of serious injury for young baseball pitchers: a 10-year prospective study. Am J Sports Med. 2011;39(2):253–7.

    Article  PubMed  Google Scholar 

  61. Olsen SJ, Fleisig GS, Dun S, et al. Risk factors for shoulder and elbow injuries in adolescent baseball pitchers. Am J Sports Med. 2006;34(6):905–12.

    Article  PubMed  Google Scholar 

  62. 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.

    Article  PubMed  Google Scholar 

  63. Gleeson M, Bishop N, Oliveira M, et al. Influence of training load on upper respiratory tract infection incidence and antigen-stimulated cytokine production. Scand J Med Sci Sports. 2013;23(4):451–7.

    CAS  Article  PubMed  Google Scholar 

  64. Opar DA, Williams MD, Timmins RG, et al. The effect of previous hamstring strain injuries on the change in eccentric hamstring strength during preseason training in elite Australian footballers. Am J Sports Med. 2014;43(2):377–84.

    Article  PubMed  Google Scholar 

  65. Bourne MN, Opar DA, Williams MD, et al. Eccentric knee flexor strength and risk of hamstring injuries in rugby union: a prospective study. Am J Sports Med. 2015;43(11):2663–70.

    Article  PubMed  Google Scholar 

  66. Purdam C, Drew MK, Blanch PD, et al. Prescription of training load in relation to loading and unloading phases of training. In: Departments of Physical Therapies, Sports Medicine and Physiology, Purdam C, Drew MK, editors. Bruce: Australian Sports Commission; 2015.

  67. Downs SH, Black N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J Epidemiol Community Health. 1998;52(6):377–84.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  68. Waller AE, Feehan M, Marshall SW, et al. The New Zealand rugby injury and performance project: I. Design and methodology of a prospective follow-up study. Br. J. Sports Med. 1994;28(4):223–228

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  69. Thornton HR, Delaney JA, Duthie GM, et al. Predicting self-reported illness for professional team-sport athletes. Int J Sports Physiol Perform. 2015. [Epub ahead of print].

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Michael K. Drew.

Ethics declarations

Funding

Funding Caroline Finch was supported by a National Health and Medical Research Council (of Australia) Principal Research Fellowship (ID: 1058737). No other sources of funding were used to assist in the preparation of this article. The Australian Centre for Research into Injury in Sport and its Prevention (ACRISP) is one of the International Research Centres for Prevention of Injury and Protection of Athlete Health supported by the International Olympic Committee (IOC).

Conflict of interest

Michael Drew and Caroline Finch declare that they have no conflicts of interest relevant to the content of this systematic review.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Drew, M.K., Finch, C.F. The Relationship Between Training Load and Injury, Illness and Soreness: A Systematic and Literature Review. Sports Med 46, 861–883 (2016). https://doi.org/10.1007/s40279-015-0459-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40279-015-0459-8

Keywords

  • Training Load
  • Internal Load
  • Moderate Evidence
  • Rugby League
  • Rugby Union