@article{ref1,
title="Modelling the relationships between volume, intensity and injury-risk in professional rugby league players",
journal="Journal of science and medicine in sport",
year="2019",
author="Cummins, Cloe and Welch, Mitchell and Inkster, Brendan and Cupples, Balin and Weaving, Dan and Jones, Ben and King, Doug and Murphy, Aron",
volume="22",
number="6",
pages="653-660",
abstract="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. <br><br>DESIGN: Retrospective cohort study. <br><br>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<sup>-1</sup>), high speed distance ([m]>20kmh<sup>-1</sup>), very-high speed distance ([m]>25kmh<sup>-1</sup>), 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. <br><br>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<sup>-1</sup>) demonstrated a positive association with injury-risk, whilst high two-weekly loads (high: >82 mmin<sup>-1</sup>) were negatively associated. <br><br>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.<br><br>Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.<p /> <p>Language: en</p>",
language="en",
issn="1440-2440",
doi="10.1016/j.jsams.2018.11.028",
url="http://dx.doi.org/10.1016/j.jsams.2018.11.028"
}