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Objectives To assess the association between workload, subjective wellness, musculoskeletal screening measures and non-contact injury risk in elite Australian footballers. Design Prospective cohort study. Methods Across 4 seasons in 70 players from one club, cumulative weekly workloads (acute; 1 week, chronic; 2-, 3-, 4-week) and acute:chronic workload ratio's (ACWR: 1-week load/average 4-weekly load) for session-Rating of Perceived Exertion (sRPE) and GPS-derived distance and sprint distance were calculated. Wellness, screening and non-contact injury data were also documented. Univariate and multivariate regression models determined injury incidence rate ratios (IRR) while accounting for interaction/moderating effects. Receiver operating characteristics determined model predictive accuracy (area under curve: AUC). Results Very low cumulative chronic (2-, 3-, 4- week) workloads were associated with the greatest injury risk (univariate IRR=1.71–2.16, 95% CI=1.10–4.52) in the subsequent week. In multivariate analysis, the interaction between a low chronic load and a very high distance (adj-IRR=2.60, 95% CI=1.07–6.34) or low sRPE ACWR (adj-IRR=2.52, 95% CI=1.01–6.29) was associated with increased injury risk. Subjectively reporting " yes " ( vs. " no " ) for old lower limb pain and heavy non-football activity in the previous 7 days (multivariate adj-IRR=2.01–2.25, 95% CI=1.02–4.95) and playing experience (>9 years) (multivariate adj-IRR=2.05, 95% CI=1.03–4.06) was also associated with increased injury risk, but screening data were not. Predictive capacity of multivariate models was significantly better than univariate (AUC multivariate =0.70, 95% CI 0.64–0.75; AUC univariate range=0.51–0.60). Conclusions Chronic load is an important moderating factor in the workload–injury relationship. Low chronic loads coupled with low or very high ACWR are associated with increased injury risk.
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Colby et al. (2017) studied this question.
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