Improvement of prediction of noncontact injury in elite australian footballers with repeated exposure to established high-risk workload scenarios

Marcus J. Colby, Brian Dawson, Peter Peeling, Jarryd Heasman, Brent Rogalski, Michael K. Drew, Jordan Stares

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Objectives: To assess the effect of multiple high-risk-scenario (HRS) exposures on noncontact injury prediction in elite Australian footballers. Design: Retrospective cohort study. Methods: Sessional workload data (session rating of perceived exertion, global positioning system-derived distance, sprint distance, and maximum velocity) from 1 club (N = 60 players) over 3 seasons were collated; several established HRSs were also defined. Accumulated HRS sessional exposures were calculated retrospectively (previous 1-8 wk). Noncontact injury data were documented. Univariate and multivariate Poisson regression models determined injury incidence rate ratios (IRRs) while accounting for moderating effects (preseason workload volume and playing experience). Model performance was evaluated using receiver operating characteristics (area under curve). Results: Very low (0-8 sessions: IRR = 5.76; 95% confidence interval [CI], 1.69-19.66) and very high (>15 sessions: IRR = 4.70; 95% CI, 1.49-14.87) exposures to >85% of an individual's maximal velocity over the previous 8 wk were associated with greater injury risk compared with moderate exposures (11-12 sessions) and displayed the best model performance (area under curve = 0.64). A single session corresponding to a very low chronic load condition over the previous week for all workload variables was associated with increased injury risk, with sprint distance (IRR = 3.25; 95% CI, 1.95-5.40) providing the most accurate prediction model (area under curve = 0.63). Conclusions: Minimal exposure to high-velocity efforts (maximum speed exposure and sprint volume) was associated with the greatest injury risk. Being underloaded may be a mediator for noncontact injury in elite Australian football. Preseason workload and playing experience were not moderators of this effect.

Original languageEnglish
Pages (from-to)1130-1135
Number of pages6
JournalInternational Journal of Sports Physiology and Performance
Volume13
Issue number9
DOIs
Publication statusPublished - 2018

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Workload
Wounds and Injuries
Area Under Curve
Incidence
Confidence Intervals
Geographic Information Systems
Football
ROC Curve
Cohort Studies
Retrospective Studies

Cite this

Colby, Marcus J. ; Dawson, Brian ; Peeling, Peter ; Heasman, Jarryd ; Rogalski, Brent ; Drew, Michael K. ; Stares, Jordan. / Improvement of prediction of noncontact injury in elite australian footballers with repeated exposure to established high-risk workload scenarios. In: International Journal of Sports Physiology and Performance. 2018 ; Vol. 13, No. 9. pp. 1130-1135.
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abstract = "Objectives: To assess the effect of multiple high-risk-scenario (HRS) exposures on noncontact injury prediction in elite Australian footballers. Design: Retrospective cohort study. Methods: Sessional workload data (session rating of perceived exertion, global positioning system-derived distance, sprint distance, and maximum velocity) from 1 club (N = 60 players) over 3 seasons were collated; several established HRSs were also defined. Accumulated HRS sessional exposures were calculated retrospectively (previous 1-8 wk). Noncontact injury data were documented. Univariate and multivariate Poisson regression models determined injury incidence rate ratios (IRRs) while accounting for moderating effects (preseason workload volume and playing experience). Model performance was evaluated using receiver operating characteristics (area under curve). Results: Very low (0-8 sessions: IRR = 5.76; 95{\%} confidence interval [CI], 1.69-19.66) and very high (>15 sessions: IRR = 4.70; 95{\%} CI, 1.49-14.87) exposures to >85{\%} of an individual's maximal velocity over the previous 8 wk were associated with greater injury risk compared with moderate exposures (11-12 sessions) and displayed the best model performance (area under curve = 0.64). A single session corresponding to a very low chronic load condition over the previous week for all workload variables was associated with increased injury risk, with sprint distance (IRR = 3.25; 95{\%} CI, 1.95-5.40) providing the most accurate prediction model (area under curve = 0.63). Conclusions: Minimal exposure to high-velocity efforts (maximum speed exposure and sprint volume) was associated with the greatest injury risk. Being underloaded may be a mediator for noncontact injury in elite Australian football. Preseason workload and playing experience were not moderators of this effect.",
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Improvement of prediction of noncontact injury in elite australian footballers with repeated exposure to established high-risk workload scenarios. / Colby, Marcus J.; Dawson, Brian; Peeling, Peter; Heasman, Jarryd; Rogalski, Brent; Drew, Michael K.; Stares, Jordan.

In: International Journal of Sports Physiology and Performance, Vol. 13, No. 9, 2018, p. 1130-1135.

Research output: Contribution to journalArticle

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AU - Drew, Michael K.

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