Citation

Cummins C, Welch M, Inkster B, Cupples B, Weaving D, Jones B, King D, Murphy A. J. Sci. Med. Sport 2019; 22(6): 653-660.

Affiliation

School of Science and Technology, University of New England, Australia.

Copyright

(Copyright © 2019, Sports Medicine Australia, Publisher Elsevier Publishing)

DOI

10.1016/j.jsams.2018.11.028

PMID

30651223

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.

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^-1), high speed distance ([m]>20kmh^-1), very-high speed distance ([m]>25kmh^-1), 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^-1) demonstrated a positive association with injury-risk, whilst high two-weekly loads (high: >82 mmin^-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 optimise player performance and welfare.

Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Language: en

Keywords

Injury prevention; Microtechnology; Team sport; Training load