Training Load Monitoring, Injury and Illness in a High-Performance Women’s Rugby Team

Project: Research

Project Details


There is evidence of a relationship between training load (TL), injury, and illness, particularly when considering individual workload changes. TL changes can be viewed as differences in week-to-week variation, and acute chronic workload ratio (ACWR). Targeted TL monitoring can assist with identifying if an athlete is coping with training, and/or is at risk of overtraining which may lead to poor performance, injury, and/or illness. An important consideration of these relationships is the method of calculation used to estimate ACWR.

Traditional ACWR calculations are ‘mathematically coupled’, as the most recent week is included in estimates of both the acute and chronic workloads [1, 2]. Different acute and chronic time windows, exponentially weighted moving averages and week-to-week changes have been proposed in the literature to monitor progressions in training load. Each of these calculations will result in different numbers for a given work-load sequence. Notable ‘thresholds’ will also differ depending on how an ACWR is calculated [1].

Study overview:
The aim of this study is to compare the different ACWR methods of calculation, in order to identify the optimal ACWR calculation as it relates to missed training days due to injury and illness in a high-performance women’s rugby team. Data will be captured from the Brumbies Women’s team across the course of one season.

1. Windt J, Gabbett TJ. Is it all for naught? What does mathematical coupling mean for acute: chronic workload ratios? : BMJ Publishing Group Ltd and British Association of Sport and Exercise Medicine; 2019.
2. Menaspa P. Are rolling averages a good way to assess training load for injury prevention? Br J Sports Med. 2017;51(7):618-9. doi:10.1136/bjsports-2016-096131.

Effective start/end date17/02/2030/11/20


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.