The Relationship Between Training Load and Injury in Athletes: A Systematic Review

A Correction to this article is available

This article has been updated

Abstract

Background

The relationship between training load and musculoskeletal injury is a rapidly advancing area of research in need of an updated systematic review.

Objective

This systematic review examined the evidence for the relationship between training load and musculoskeletal injury risk in athlete, military, and first responder (i.e. law enforcement, firefighting, rescue service) populations.

Methods

The CINAHL, EMBASE, MEDLINE, SportDISCUS, and SCOPUS databases were searched using a comprehensive strategy. Studies published prior to July 2017 were included if they prospectively examined the relationship between training load and injury risk. Study quality was assessed using the Newcastle–Ottawa Quality Assessment Scale (NOS) and Oxford Centre for Evidence-Based Medicine levels of evidence. A narrative synthesis of findings was conducted.

Results

A total of 2047 articles were examined for potential inclusion. Forty-six met the inclusion criteria and 11 known to the authors but not found in the search were added, for a total of 57 articles. Overall, 47 studies had at least partially statistically significant results, demonstrating a relationship between training load and injury risk. Included articles were rated as poor (n = 15), fair (n = 6), and good (n = 36) based on NOS score. Articles assessed as ‘good’ were considered level 2b evidence on the Oxford Centre for Evidence-Based Medicine Model, and articles assessed as ‘fair’ or ‘poor’ were considered level 4 evidence.

Conclusions

Our results demonstrate that the existence of a relationship between training load and injury continues to be well supported in the literature and is strongest for subjective internal training load. The directionality of this relationship appears to depend on the type and timeframe of load measured.

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

Fig. 1

Change history

  • 07 April 2020

    ���Cox proportional hazards regression models with frailty found no difference in injured vs. unin-jured players with week-to-week changes of���<���20, 20���60, and���>���60%, controlling for scapular con-trol, isometric rotational and abduction strength, and shoulder range of motion (p value ranges 0.09���0.68)

References

  1. 1.

    Soligard T, Schwellnus M, Alonso JM, Bahr R, Clarsen B, Dijkstra HP, et al. How much is too much? (part 1) International Olympic Committee consensus statement on load in sport and risk of injury. Br J Sports Med. 2016;50(17):1030–41.

    Article  PubMed  Google Scholar 

  2. 2.

    Drew MK, Raysmith BP, Charlton PC. Injuries impair the chance of successful performance by sportspeople: a systematic review. Br J Sports Med. 2017;51(16):1209–14.

    Article  PubMed  Google Scholar 

  3. 3.

    Lisman P, O’Connor FG, Deuster PA, Knapik JJ. Functional movement screen and aerobic fitness predict injuries in military training. Med Sci Sports Exerc. 2013;45(4):636–43.

    Article  PubMed  Google Scholar 

  4. 4.

    Sefton JEM, Lohse KR, McAdam JS. Prediction of injuries and injury types in army basic training, infantry, armor, and cavalry trainees using a common fitness screen. J Athl Train. 2016;51(11):849–57.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Teyhen DS, Shaffer SW, Butler RJ, Goffar SL, Kiesel KB, Rhon DI, et al. Application of athletic movement tests that predict injury risk in a military population: development of normative data. Mil Med. 2016;181(10):1324–34.

    Article  PubMed  Google Scholar 

  6. 6.

    National Research Council. Assessing fitness for military enlistment: physical, medical, and mental health standards. Washington, DC: The National Academies Press; 2006. https://doi.org/10.17226/11511.

    Google Scholar 

  7. 7.

    Bahr R, Holme I. Risk factors for sports injuries—a methodological approach. Br J Sports Med. 2003;37(5):384–92.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. 8.

    Murphy D, Connolly D, Beynnon B. Risk factors for lower extremity injury: a review of the literature. Br J Sports Med. 2003;37(1):13–29.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. 9.

    Hägglund M, Waldén M, Ekstrand J. Previous injury as a risk factor for injury in elite football: a prospective study over two consecutive seasons. Br J Sports Med. 2006;40(9):767–72.

    Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Kucera KL, Marshall SW, Kirkendall DT, Marchak PM, Garrett WE Jr. Injury history as a risk factor for incident injury in youth soccer. Br J Sports Med. 2005;39(7):462.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. 11.

    Kucera KL, Marshall SW, Wolf SH, Padua DA, Cameron KL, Beutler AI. Association of injury history and incident injury in cadet basic military training. Med Sci Sports Exerc. 2016;48(6):1053–61.

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Ullah S, Gabbett TJ, Finch CF. Statistical modelling for recurrent events: an application to sports injuries. Br J Sports Med. 2014;48(17):1287–93.

    Article  PubMed  Google Scholar 

  13. 13.

    Hootman JM, Dick R, Agel J. Epidemiology of collegiate injuries for 15 sports: summary and recommendations for injury prevention initiatives. J Athl Train. 2007;42(2):311–9.

    PubMed  PubMed Central  Google Scholar 

  14. 14.

    Halson SL. Monitoring training load to understand fatigue in athletes. Sports Med. 2014;44(Suppl 2):S139–47.

    Article  PubMed  Google Scholar 

  15. 15.

    Wallace LK, Slattery KM, Coutts AJ. The ecological validity and application of the session-RPE method for quantifying training loads in swimming. J Strength Cond Res. 2009;23(1):33–8.

    Article  PubMed  Google Scholar 

  16. 16.

    Saw AE, Main LC, Gastin PB. Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review. Br J Sports Med. 2016;50(5):281–91.

    Article  PubMed  Google Scholar 

  17. 17.

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

    PubMed  CAS  Google Scholar 

  18. 18.

    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):708–12.

    Article  PubMed  Google Scholar 

  19. 19.

    Jones CM, Griffiths PC, Mellalieu SD. Training load and fatigue marker associations with injury and illness: a systematic review of longitudinal studies. Sports Med. 2017;47(5):943–74.

    Article  PubMed  Google Scholar 

  20. 20.

    Drew MK, Finch CF. The relationship between training load and injury, illness and soreness: a systematic and literature review. Sports Med. 2016;46(6):861–83.

    Article  PubMed  Google Scholar 

  21. 21.

    Scofield DE, Kardouni JR. The tactical athlete: a product of 21st century strength and conditioning. Strength Cond J. 2015;37(4):2–7.

    Article  Google Scholar 

  22. 22.

    Grier T, Canham-Chervak M, McNulty V, Jones BH. Extreme conditioning programs and injury risk in a US Army brigade combat team. US Army Med Dep J. 2013:36–47.

  23. 23.

    Cameron KL, Driban JB, Svoboda SJ. Osteoarthritis and the tactical athlete: a systematic review. J Athl Train. 2016;51(11):952–61.

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Nindl BC, Jaffin DP, Dretsch MN, Cheuvront SN, Wesensten NJ, Kent ML, et al. Human performance optimization metrics: consensus findings, gaps, and recommendations for future research. J Strength Cond Res. 2015;29:S221–45.

    Article  PubMed  Google Scholar 

  25. 25.

    US Department of the Army. Army Physical Readiness Training, Field Manual 7–22. Washington, DC: Department of the Army; 2012.

    Google Scholar 

  26. 26.

    Sell TC, Abt JP, Crawford K, Lovalekar M, Nagai T, Deluzio JB, et al. Warrior model for human performance and injury prevention: Eagle Tactical Athlete Program (ETAP) part II. J Spec Oper Med. 2010;10(4):22–33.

    PubMed  Google Scholar 

  27. 27.

    Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700.

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    The Cochrane Collaboration. Study design guide for review authors. 2013. http://cccrg.cochrane.org/sites/cccrg.cochrane.org/files/public/uploads/Study_design_guide2013.pdf. Accessed 20 July 2017.

  29. 29.

    Wells G, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. Newcastle-Ottawa quality assessment scale cohort studies. 2014. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp. Accessed 21 Dec 2016.

  30. 30.

    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 Commun Health. 1998;52(6):377–84.

    Article  CAS  Google Scholar 

  31. 31.

    Higgins J, Green S (editors). Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011]. The Cochrane Collaboration, 2011. Available from http://www.handbook.cochrane.org.

  32. 32.

    Hootman JM, Driban JB, Sitler MR, Harris KP, Cattano NM. Reliability and validity of three quality rating instruments for systematic reviews of observational studies. Res Synth Methods. 2011;2(2):110–8.

    Article  PubMed  Google Scholar 

  33. 33.

    Oxford Centre for Evidence-Based Medicine: levels of evidence (March 2009). 2009. http://www.cebm.net/oxford-centre-evidence-based-medicine-levels-evidence-march-2009/. Accessed 22 July 2017.

  34. 34.

    van Tulder M, Furlan A, Bombardier C, Bouter L. Updated method guidelines for systematic reviews in the Cochrane Collaboration back review group. Spine. 2003;28(12):1290–9.

    PubMed  Google Scholar 

  35. 35.

    Ball S, Halaki M, Sharp T, Orr R. Injury patterns, physiological profile, and performance in university rugby union. Int J Sports Physiol Perform. 2017;13(1):1–18.

    Google Scholar 

  36. 36.

    Colby MJ, Dawson B, Heasman J, Rogalski B, Rosenberg M, Lester L, et al. Preseason workload volume and high-risk periods for noncontact injury across multiple Australian football league seasons. J Strength Cond Res. 2017;31(7):1821–9.

    Article  PubMed  Google Scholar 

  37. 37.

    Colby MJ, Dawson B, Peeling P, Heasman J, Rogalski B, Drew MK, et al. Multivariate modelling of subjective and objective monitoring data improve the detection of non-contact injury risk in elite Australian footballers. J Sci Med Sport. 2017;20(12):1068–74.

    Article  PubMed  Google Scholar 

  38. 38.

    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 

  39. 39.

    Kluitenberg B, van der Worp H, Huisstede BM, Hartgens F, Diercks R, Verhagen E, et al. The NLstart2run study: training-related factors associated with running-related injuries in novice runners. J Sci Med Sport. 2016;19(8):642–6.

    Article  PubMed  Google Scholar 

  40. 40.

    Malisoux L, Nielsen RO, Urhausen A, Theisen D. A step towards understanding the mechanisms of running-related injuries. J Sci Med Sport. 2015;18(5):523–8.

    Article  PubMed  Google Scholar 

  41. 41.

    Taunton JE, Ryan MB, Clement DB, McKenzie DC, Lloyd-Smith DR, Zumbo BD. A prospective study of running injuries: the Vancouver Sun Run “in training” clinics. Br J Sports Med. 2003;37(3):239–44.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. 42.

    Dellal A, Lago-Penas 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. Br J Sports Med. 2015;49(6):390–4.

    Article  PubMed  Google Scholar 

  43. 43.

    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 

  44. 44.

    Theisen D, Frisch A, Malisoux L, Urhausen A, Croisier JL, Seil R. Injury risk is different in team and individual youth sport. J Sci Med Sport. 2013;16(3):200–4.

    Article  PubMed  Google Scholar 

  45. 45.

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

    Article  PubMed  CAS  Google Scholar 

  46. 46.

    Weiss KJ, Allen SV, McGuigan MR, Whatman CS. The relationship between training load and injury in men’s professional basketball players. Int J Sports Physiol Perform. 2017;12(9):1–20.

    Article  Google Scholar 

  47. 47.

    Williams S, Trewartha G, Kemp SP, Brooks JH, Fuller CW, Taylor AE, et al. How much rugby is too much? A seven-season prospective cohort study of match exposure and injury risk in professional rugby union players. Sports Med. 2017;47(11):2395–402.

    Article  PubMed  PubMed Central  Google Scholar 

  48. 48.

    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. J Sci Med Sport. 2017;20(3):250–4.

    Article  PubMed  Google Scholar 

  49. 49.

    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? J Sci Med Sport. 2018;21(3):257–62.

    Article  PubMed  Google Scholar 

  50. 50.

    Ekstrand J, Gillquist J, Moller M, Oberg B, Liljedahl SO. Incidence of soccer injuries and their relation to training and team success. Am J Sports Med. 1983;11(2):63–7.

    Article  PubMed  CAS  Google Scholar 

  51. 51.

    Dennis R, Farhart P, Clements M, Ledwidge H. The relationship between fast bowling workload and injury in first-class cricketers: a pilot study. J Sci Med Sport. 2004;7(2):232–6.

    Article  PubMed  CAS  Google Scholar 

  52. 52.

    Colby MJ, Dawson B, Heasman J, Rogalski B, Gabbett TJ. 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 

  53. 53.

    Orchard JW, James T, Portus M, Kountouris A, Dennis R. 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 

  54. 54.

    Orchard JW, Blanch P, Paoloni J, Kountouris A, Sims K, Orchard JJ, et al. Fast bowling match workloads over 5–26 days and risk of injury in the following month. J Sci Med Sport. 2015;18(1):26–30.

    Article  PubMed  Google Scholar 

  55. 55.

    Murray NB, Gabbett TJ, Townshend AD, Blanch P. Calculating acute:chronic workload ratios using exponentially weighted moving averages provides a more sensitive indicator of injury likelihood than rolling averages. Br J Sports Med. 2017;51(9):749–54.

    Article  PubMed  Google Scholar 

  56. 56.

    Hulin BT, Gabbett TJ, Lawson DW, Caputi P, Sampson JA. 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.

    Article  PubMed  Google Scholar 

  57. 57.

    Rogalski B, Dawson B, Heasman J, Gabbett TJ. Training and game loads and injury risk in elite Australian footballers. J Sci Med Sport. 2013;16(6):499–503.

    Article  PubMed  Google Scholar 

  58. 58.

    Brink MS, Visscher C, Arends S, Zwerver J, Post WJ, Lemmink KA. 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 

  59. 59.

    Murray NB, Gabbett TJ, Chamari K. Effect of different between-match recovery times on the activity profiles and injury rates of National Rugby League players. J Strength Cond Res. 2014;28(12):3476–83.

    Article  PubMed  Google Scholar 

  60. 60.

    Murray NB, Gabbett TJ, Townshend AD. Relationship between pre-season training load and in-season availability in elite Australian football players. Int J Sports Physiol Perform. 2017;12(6):749–55.

    Article  PubMed  Google Scholar 

  61. 61.

    Harrison PW, Johnston RD. The relationship between training load, fitness and injury over an Australian rules football preseason. J Strength Cond Res. 2017;31(10):2686–93.

    Article  PubMed  Google Scholar 

  62. 62.

    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):561–5.

    Article  PubMed  Google Scholar 

  63. 63.

    Malone S, Roe M, Doran DA, Gabbett TJ, Collins KD. Protection against spikes in workload with aerobic fitness and playing experience: the role of the acute:chronic workload ratio on injury risk in elite Gaelic football. Int J Sports Physiol Perform. 2017;12(3):393–401.

    Article  PubMed  Google Scholar 

  64. 64.

    Stares J, Dawson B, Peeling P, Heasman J, Rogalski B, Drew M, et al. Identifying high risk loading conditions for in-season injury in elite Australian football players. J Sci Med Sport. 2018;21(1):46–51.

    Article  PubMed  Google Scholar 

  65. 65.

    Moller M, Nielsen RO, Attermann J, Wedderkopp N, Lind M, Sorensen H, et al. Handball load and shoulder injury rate: a 31-week cohort study of 679 elite youth handball players. Br J Sports Med. 2017;51(4):231–7.

    Article  PubMed  CAS  Google Scholar 

  66. 66.

    Carey DL, Blanch P, Ong KL, Crossley KM, Crow J, Morris ME. Training loads and injury risk in Australian football-differing acute:chronic workload ratios influence match injury risk. Br J Sports Med. 2017;51(16):1215–20.

    Article  PubMed  Google Scholar 

  67. 67.

    Bowen L, Gross AS, Gimpel M, Li FX. Accumulated workloads and the acute: chronic workload ratio relate to injury risk in elite youth football players. Br J Sports Med. 2017;51(5):452–9.

    Article  PubMed  Google Scholar 

  68. 68.

    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 

  69. 69.

    Jacobsson J, Timpka T, Kowalski J, Nilsson S, Ekberg J, Dahlstrom O, et al. Injury patterns in Swedish elite athletics: annual incidence, injury types and risk factors. Br J Sports Med. 2013;47(15):941–52.

    Article  PubMed  Google Scholar 

  70. 70.

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

    PubMed  CAS  Google Scholar 

  71. 71.

    Owen AL, Forsyth JJ, del Wong P, Dellal A, Connelly SP, Chamari K. Heart rate-based training intensity and its impact on injury incidence among elite-level professional soccer players. J Strength Cond Res. 2015;29(6):1705–12.

    Article  PubMed  Google Scholar 

  72. 72.

    Wyss T, Roos L, Hofstetter MC, Frey F, Mader U. Impact of training patterns on injury incidences in 12 Swiss Army basic military training schools. Mil Med. 2014;179(1):49–55.

    Article  PubMed  Google Scholar 

  73. 73.

    Viswanathan M, Ansari MT, Berkman ND, Chang S, Hartling L, McPheeters M, et al. Assessing the risk of bias of individual studies in systematic reviews of health care interventions. In: AHRQ methods for effective health care. Methods guide for effectiveness and comparative effectiveness reviews. Rockville: Agency for Healthcare Research and Quality; 2008.

  74. 74.

    Dupont G, Nedelec M, McCall A, McCormack D, Berthoin S, Wisloff U. Effect of 2 soccer matches in a week on physical performance and injury rate. Am J Sports Med. 2010;38(9):1752–8.

    Article  PubMed  Google Scholar 

  75. 75.

    Vilamitjana J, Lentini N, Masabeu E. The influence of match frequency on the risk of injury in professional soccer. Int J Sport Med. 2013;14(3):139–47.

    Google Scholar 

  76. 76.

    Korkia PK, Tunstall-Pedoe DS, Maffulli N. An epidemiological investigation of training and injury patterns in British triathletes. Br J Sports Med. 1994;28(3):191–6.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. 77.

    Bayne H, Elliott B, Campbell A, Alderson J. Lumbar load in adolescent fast bowlers: a prospective injury study. J Sci Med Sport. 2016;19(2):117–22.

    Article  PubMed  Google Scholar 

  78. 78.

    Gabbett TJ. The training-injury prevention paradox: should athletes be training smarter and harder? Br J Sports Med. 2016;50(5):273–80.

    Article  PubMed  PubMed Central  Google Scholar 

  79. 79.

    Hamalainen O, Vanharanta H, Bloigu R. + Gz-related neck pain: a follow-up study. Aviat Space Environ Med. 1994;65(1):16–8.

    PubMed  CAS  Google Scholar 

  80. 80.

    Polanin JR, Tanner-Smith EE, Hennessy EA. Estimating the difference between published and unpublished effect sizes: a meta-review. Rev Educ Res. 2016;86(1):207–36.

    Article  Google Scholar 

  81. 81.

    Vecchi S, Belleudi V, Amato L, Davoli M, Perucci CA. Does direction of results of abstracts submitted to scientific conferences on drug addiction predict full publication? BMC Med Res Methodol. 2009;9:23.

    Article  PubMed  PubMed Central  Google Scholar 

  82. 82.

    Anderson L, Triplett-McBride T, Foster C, Doberstein S, Brice G. 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 

  83. 83.

    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.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  84. 84.

    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 

  85. 85.

    Brooks JH, Fuller CW, Kemp SP, Reddin DB. 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 

  86. 86.

    Gianoudis J, Webster KE, Cook J. Volume of physical activity and injury occurrence in young basketball players. J Sports Sci Med. 2008;7(1):139–43.

    PubMed  PubMed Central  Google Scholar 

  87. 87.

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

    Article  PubMed  CAS  Google Scholar 

  88. 88.

    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 

  89. 89.

    Newlands C, Reid D, Parmar P. The prevalence, incidence and severity of low back pain among international-level rowers. Br J Sports Med. 2015;49(14):951–6.

    Article  PubMed  Google Scholar 

  90. 90.

    Krutsch W, Zeman F, Zellner J, Pfeifer C, Nerlich M, Angele P. Increase in ACL and PCL injuries after implementation of a new professional football league. Knee Surg Sports Traumatol Arthrosc. 2016;24(7):2271–9.

    Article  PubMed  Google Scholar 

  91. 91.

    Orr R, Cheng HL. Incidence and characteristics of injuries in elite Australian junior rugby league players. J Sci Med Sport. 2016;19(3):212–7.

    Article  PubMed  Google Scholar 

  92. 92.

    Thornton HR, Delaney JA, Duthie GM, Dascombe BJ. Importance of various training load measures on injury incidence of professional rugby league athletes. Int J Sports Physiol Perform. 2017;12(6):819–24.

    Article  PubMed  Google Scholar 

  93. 93.

    van der Worp MP, de Wijer A, van Cingel R, Verbeek AL, Nijhuis-van der Sanden MW, Staal JB. The 5- or 10-km Marikenloop run: a prospective study of the etiology of running-related injuries in women. J Orthop Sports Phys Ther. 2016;46(6):462–70.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge and thank Ms. Rachael Posey and Ms. Chana Kraus Friedberg for their help in developing and executing the search strategy.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Timothy G. Eckard.

Ethics declarations

Funding

Timothy Eckard is supported by a Promotional of Doctoral Studies scholarship from the (US) Foundation for Physical Therapy. No other sources of funding were used to assist in the preparation of this article.

Conflicts of Interest

Timothy Eckard, Darin Padua, Darren Hearn and Barnett Frank declare that they have no conflicts of interest relevant to the content of this review.

Electronic Supplementary Material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Eckard, T.G., Padua, D.A., Hearn, D.W. et al. The Relationship Between Training Load and Injury in Athletes: A Systematic Review. Sports Med 48, 1929–1961 (2018). https://doi.org/10.1007/s40279-018-0951-z

Download citation