Modelling The Relationships Between Volume, Intensity And Injury-Risk In Professional Rugby League Players

Cummins C, Welch M, Inkster B, Cupples B, Weaving D, Jones B, King D, Murphy A

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 (m min⁻¹), high-speed distance ([m]>20 km h⁻¹), very-high-speed distance ([m]>25 km h⁻¹), acceleration and deceleration efforts (count), and PlayerLoad (Arbitrary Unit: AU). Cumulative two-, three-, and four-weekly loads; Acute
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 analyzed 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: >60 m min⁻¹) demonstrated a positive association with injury risk, whilst high two-weekly loads (high: >82 m min⁻¹) 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 optimize player performance and welfare.

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