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Objective: This study aimed to: (a) identify the association between external-workloads and injury-risk in the subsequent week; and (b) understand the effectiveness of workload variables in establishing injury-risk.
Design: Retrospective cohort study.
Methods: Workload and injury data (soft-tissue) were collected from forty-eight professional male rugby league players. Load variables included duration (min), total distance (m), relative distance (mmin), high speed distance ([m]>20kmh), very-high speed distance ([m]>25kmh), acceleration and deceleration efforts (count) and PlayerLoad (Arbitrary Unit: AU). Cumulative two-, three- and four-weekly loads; Acute:Chronic Workload Ratio (ACWR); Mean-Standard Deviation Workload Ratio (MSWR) and strain values were calculated and divided into three equally-sized bins (low, moderate and high). Generalised Estimating Equations analysed relationships between workload variables and injury probability in the subsequent week.
Results: Injury-risk increased alongside increases in the ACWR for duration, total distance and PlayerLoad. Conversely, injury-risk decreased (Area Under Curve: 0.569-0.585) with increases in the four-weekly duration, total distance, accelerations, decelerations and PlayerLoad. For relative distance, high four-weekly workloads (high: >60mmin) demonstrated a positive association with injury-risk, whilst high two-weekly loads (high: >82 mmin) were negatively associated.
Conclusions: A range of external workload metrics and summary statistics demonstrate either positive or negative associations with injury-risk status. Such findings provide the framework for the development of decision-support systems in which external workload metrics (e.g. total or high speed distance) can be uniquely and routinely monitored across a range of summary statistics (i.e. cumulative weekly loads and ACWR) in order to optimise player performance and welfare.
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http://dx.doi.org/10.1016/j.jsams.2018.11.028 | DOI Listing |
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