ArticlePloS one2025
Position-specific workload and performance analysis in professional rugby union: Insights from global positioning system data and principal component analysis.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
Quantifying workload and performance is a systematic approach employed by practitioners to enhance their understanding of the training process as a whole. This study aims to utilize data collected from global positioning system (GPS) and video analysis to assess the movement patterns and key performance indicators (KPIs) of players across various positions during both training and match play. Additionally, it seeks to simplify workload analysis by using principal component analysis (PCA) for dimensionality reduction. Over three seasons, data were collected from 63 professional rugby union players, divided into six positional groups: front row, second row, back row, scrum-half, inside backs, and outside backs. The results showed significant positional differences in movement characteristics (p < 0.05, effect size = 0.02-0.59) and KPIs (p < 0.05, effect size = 0.04-0.77). Scrum-halves demonstrated the highest workload in medium and low-intensity activities, while outside backs excelled in high-intensity metrics, and front row forwards consistently had the lowest workload. Regarding KPIs, forwards recorded the most tackles, the highest count of arrivals at offensive and defensive rucks, while scrum-halves accounted for the most kicks, passes, and receipts. In the analysis of training and match workload, PCA extracted two principal components, explaining 73.9% and 79.1% of the variance, respectively. Overall, backs exhibited a higher training workload compared to the forwards, with scrum-halves having the highest total workload during matches. This study demonstrates significant positional differences in key movement variables, providing critical insights into the demands placed on players in different positions.
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