Modelling the relationships between volume, intensity and injury-risk in professional rugby league players

Chloe Cummins, Mitchell Welch, Brendan Inkster, Balin Cupples, Daniel Weaving, Ben Jones, Doug King, Aron Murphy

Research output: Contribution to journalArticle (journal)peer-review

27 Citations (Scopus)
3 Downloads (Pure)

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 (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: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: >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 optimise player performance and welfare.

Original languageEnglish
Pages (from-to)653-660
Number of pages8
JournalJournal of Science and Medicine in Sport
Volume22
Issue number6
Early online date18 Dec 2018
DOIs
Publication statusPublished - 30 Jun 2019

Keywords

  • Injury prevention
  • Microtechnology
  • Team sport
  • Training load

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