Relationships Among PlayerLoad, High-Intensity Intermittent Running Ability, and Injury Risk in Professional Rugby League Players

in International Journal of Sports Physiology and Performance
Restricted access

Purchase article

USD  $24.95

Student 1 year subscription

USD  $107.00

1 year subscription

USD  $142.00

Student 2 year subscription

USD  $203.00

2 year subscription

USD  $265.00

Purpose: To examine relationships among physical performance, workload, and injury risk in professional rugby league players. Methods: Maximal-effort (n = 112) and submaximal (n = 1084) running performances of 45 players were recorded from 1 club over 2 consecutive seasons. Poorer and better submaximal running performance was determined by higher and lower exercise heart rates, respectively. Exponentially weighted moving averages and daily rolling averages were used to assess microtechnology-derived acute and chronic field-based workloads. The associations among within-individual submaximal running performance, workload, and noncontact lower-limb injury were then investigated. Results: The injury risk associated with poorer submaximal performance was “likely” greater than stable (relative risk = 1.8; 90% confidence interval, 0.9–3.7) and better submaximal performance (relative risk = 2.0; 90% confidence interval, 0.9–4.4). Compared with greater submaximal performance, poorer performance was associated with lower chronic workloads (effect size [d] = 0.82 [0.13], large) and higher acute:chronic workload ratios (d = 0.49 [0.14], small). Chronic workload demonstrated a “nearly perfect” positive relationship with maximal-effort running performance (exponentially weighted moving average, R2 = .91 [.15]; rolling average, R2 = .91 [.14]). At acute:chronic workload ratios >1.9, no differences in injury risk were found between rolling average and exponentially weighted moving average methods (relative risk = 1.1; 90% confidence interval, 0.3–3.8; unclear). Conclusions: Reductions in submaximal running performance are related with low chronic workloads, high acute:chronic workload ratios, and increased injury risk. These findings demonstrate that a submaximal running assessment can be used to provide information on physical performance and injury risk in professional rugby league players.

Hulin and Jenkins are with the School of Human Movement and Nutrition Sciences, University of Queensland, Brisbane, QLD, Australia. Hulin and Pickworth are with Football Dept, St George Illawarra Dragons Rugby League Football Club, Wollongong, NSW, Australia. Gabbett is with Gabbett Performance Solutions, Brisbane, QLD, Australia, and the Inst for Resilient Regions, University of Southern Queensland, Ipswich, QLD, Australia. Johnston is with the School of Behavioural and Health Sciences, Australian Catholic University, Brisbane, QLD, Australia.

Hulin (billyhulin@hotmail.com) is corresponding author.
  • 1.

    Eirale C, Tol JL, Farooq A, et al. Low injury rate strongly correlates with team success in Qatari professional football. Br J Sports Med. 2013;47:807–808. PubMed ID: 22904292 doi:10.1136/bjsports-2012-091040

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2.

    Hickey J, Shield AJ, Williams MD, et al. The financial cost of hamstring strain injuries in the Australian Football League. Br J Sports Med. 2014;48(8):729–730. doi:10.1136/bjsports-2013-092884

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Gabbett TJ. Debunking the myths about training load, injury and performance: empirical evidence, hot topics and recommendations for practitioners [published online ahead of print October 26, 2018]. Br J Sports Med. doi:10.1136/bjsports-2018-099784

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Gabbett TJ, Ullah S, Finch C. Identifying risk factors for contact injury in professional rugby league players—application of a frailty model for recurrent injury. J Sci Med Sport. 2012;15:496–504. PubMed ID: 22748762 doi:10.1016/j.jsams.2012.03.017

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5.

    Johnston RD, Gabbett TJ, Jenkins DG, et al. Influence of physical qualities on post-match fatigue in rugby league players. J Sci Med Sport 2015;18:209–213. PubMed ID: 24594214 doi:10.1016/j.jsams.2014.01.009

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Bangsbo J, Iaia FM, Krustrup P. The Yo-Yo Intermittent Recovery Test: a useful tool for evaluation of physical performance in intermittent sports. Sports Med. 2008;38(1):37–51. PubMed ID: 18081366 doi:10.2165/00007256-200838010-00004

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    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;48:708–712. PubMed ID: 23962877 doi:10.1136/bjsports-2013-092524

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    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;50:231–236. PubMed ID: 26511006 doi:10.1136/bjsports-2015-094817

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9.

    Hulin BT, Gabbett TJ, Caputi P, et al. Low chronic workload and the acute:chronic workload ratio are more predictive of injury than between-match recovery time: a two-season prospective cohort study in elite rugby league players. Br J Sports Med. 2016;50:1008–1012. PubMed ID: 26851288 doi:10.1136/bjsports-2015-095364

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Boyd LJ, Ball K, Aughey RJ. The reliability of MinimaxX accelerometers for measuring physical activity in Australian football. Int J Sports Physiol Perform. 2011;6:311–321. PubMed ID: 21911857 doi:10.1123/ijspp.6.3.311

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Barreira P, Robinson MA, Drust B, et al. Mechanical player load™ using trunk-mounted accelerometry in football: is it a reliable, task- and player-specific observation? J Sports Sci. 2017;35:1674–1681. PubMed ID: 27598850 doi:10.1080/02640414.2016.1229015

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Hulin BT, Gabbett TJ, Johnston RD, et al. Sub-maximal heart rate is associated with changes in high-intensity intermittent running ability in professional rugby league players. Sci Med Football. 2019;3:50–56. doi:10.1080/24733938.2018.1475748

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Veugelers KR, Naughton GA, Duncan CS, Burgess DJ, Graham SR. Validity and reliability of a submaximal intermittent running test in elite Australian football players. J Strength Cond Res. 2016;30(12):3347–3353. PubMed ID: 27870695 doi:10.1519/JSC.0000000000001441

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Williams S, West S, Cross MJ, et al. Better way to determine the acute:chronic workload ratio? Br J Sports Med. 2017;51:209–210. PubMed ID: 27650255 doi:10.1136/bjsports-2016-096589

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Menaspà P. Are rolling averages a good way to assess training load for injury prevention? Br J Sports Med. 2017;51:618–619.

  • 16.

    Murray NB, Gabbett TJ, Townshend AD, et al. 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;51:749–754. PubMed ID: 28003238 doi:10.1136/bjsports-2016-097152

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Esmaeili A, Hopkins WG, Stewart AM, Elias GP, Lazarus BH, Aughey RJ. The individual and combined effects of multiple factors on the risk of soft tissue non-contact injuries in elite team sport athletes. Front Physiol. 2018;9:1280. PubMed ID: 30333756 doi:10.3389/fphys.2018.01280

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    McCall A, Dupont G, Ekstrand J. Internal workload and non-contact injury: a one-season study of five teams from the UEFA Elite Club Injury Study. Br J Sports Med. 2018;52(23):1517–1522. PubMed ID: 29626055 doi:10.1136/bjsports-2017-098473

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Hulin BT, Gabbett TJ, Johnston RD, et al. PlayerLoad variables: sensitive to changes in direction and not related to collision workloads in rugby league match play. Int J Sports Physiol Perform. 2018;13(9):1136–1142. PubMed ID: 29543076 doi:10.1123/ijspp.2017-0557

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Malone S, Roe M, Doran DA, et al. 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;12:393–401. PubMed ID: 27400233 doi:10.1123/ijspp.2016-0090

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Batterham AM, Hopkins WG. Making meaningful inferences about magnitudes. Int J Sports Physiol Perform. 2006;1:50–57. PubMed ID: 19114737 doi:10.1123/ijspp.1.1.50

  • 22.

    Hopkins WG, Marshall SW, Batterham AM, et al. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41:3–13. PubMed ID: 19092709 doi:10.1249/MSS.0b013e31818cb278

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Wahl P, Güldner M, Mester J. Effects and sustainability of a 13-day high-intensity shock microcycle in soccer. J Sports Sci Med. 2014;13:259–265. PubMed ID: 24790477

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Bosquet L, Montpetit J, Arvisais D, et al. Effects of tapering on performance: a meta-analysis. Med Sci Sports Exerc. 2007;39:1358–1365. PubMed ID: 17762369 doi:10.1249/mss.0b013e31806010e0

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    Banister E, Calvert T, Savage M, et al. A systems model of training for athletic performance. Aust J Sport Med. 1975;7:57–61.

  • 26.

    Wyss T, Roos L, Hofstetter MC, et al. Impact of training patterns on injury incidences in 12 Swiss Army basic military training schools. Mil Med. 2014;179:49–55. PubMed ID: 24402985 doi:10.7205/MILMED-D-13-00289

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Scott TJ, Dascombe BJ, Delaney JA, et al. Running momentum: a new method to quantify prolonged high-intensity intermittent running performance in collision sports. Sci Med Football. 2017;1:244–250. doi:10.1080/24733938.2017.1331044

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28.

    Aughey R, Elias GP, Esmaeili A, et al. Does the recent internal load and strain on players affect match outcome in elite Australian football? J Sci Med Sport. 2016;19:182–186. PubMed ID: 25804423 doi:10.1016/j.jsams.2015.02.005

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Carey DL, Crossley KM, Whiteley R, et al. Modelling training loads and injuries: the dangers of discretization. Med Sci Sports Exerc. 2018;50(11):2267–2276. PubMed ID: 29933352 doi:10.1249/MSS.0000000000001685

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 30.

    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):1215–1220. PubMed ID: 27789430 doi:10.1136/bjsports-2016-096309

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Duhig S, Shield AJ, Opar D, et al. Effect of high-speed running on hamstring strain injury risk. Br J Sports Med. 2016;50(24):1536–1540. PubMed ID: 27288515 doi:10.1136/bjsports-2015-095679

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Timmins RG, Bourne MN, Shield AJ, et al. Short biceps femoris fascicles and eccentric knee flexor weakness increase the risk of hamstring injury in elite football (soccer): a prospective cohort study. Br J Sports Med. 2016;50(24):1524–1535. PubMed ID: 26675089 doi:10.1136/bjsports-2015-095362

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33.

    Gabbett TJ, Jenkins DG. Relationship between training load and injury in professional rugby league players. J Sci Med Sport. 2011;14(3):204–209. PubMed ID: 21256078 doi:10.1016/j.jsams.2010.12.002

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34.

    Bahr R, Holme I. Risk factors for sports injuries—a methodological approach. Br J Sports Med. 2003;37:384–392. PubMed ID: 14514527 doi:10.1136/bjsm.37.5.384

  • 35.

    Nielsen RO, Bertelsen ML, Ramskov D, et al. Time-to-event analysis for sports injury research part 2: time-varying outcomes. Br J Sports Med. 2019;53(1):70–78. PubMed ID: 30413427 doi:10.1136/bjsports-2018-100000

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 20 20 20
Full Text Views 1 1 1
PDF Downloads 1 1 1