Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/26371
Title: | Modelling the relationships between volume, intensity and injury-risk in professional rugby league players | Contributor(s): | Cummins, Cloe (author)![]() ![]() |
Publication Date: | 2019 | Early Online Version: | 2018-12-18 | DOI: | 10.1016/j.jsams.2018.11.028 | Handle Link: | https://hdl.handle.net/1959.11/26371 | 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. | Publication Type: | Journal Article | Source of Publication: | Journal of Science and Medicine in Sport, v.22, p. 653-660 | Publisher: | Elsevier Australia | Place of Publication: | Australia | ISSN: | 1878-1861 1440-2440 |
Fields of Research (FoR) 2008: | 110699 Human Movement and Sports Science not elsewhere classified 110604 Sports Medicine 110601 Biomechanics |
Fields of Research (FoR) 2020: | 320225 Sports medicine 420701 Biomechanics |
Socio-Economic Objective (SEO) 2008: | 950102 Organised Sports 920409 Injury Control |
Socio-Economic Objective (SEO) 2020: | 200408 Injury prevention and control 130602 Organised sports |
Peer Reviewed: | Yes | HERDC Category Description: | C1 Refereed Article in a Scholarly Journal |
---|---|
Appears in Collections: | Journal Article School of Science and Technology |
Files in This Item:
File | Description | Size | Format |
---|
SCOPUSTM
Citations
25
checked on May 18, 2024
Page view(s)
2,520
checked on May 5, 2024
This item is licensed under a Creative Commons License