Abstract
ABSTRACT Player movement metrics in football such as speed and distance are typically analysed as aggregates, sometimes outside of any specific tactical or match context. This research adds context to a player’s movement over the course of a match by analysing movement profiles s and bringing together tools from the sport science and sports analytics literature. Position-specific distributions of player movement metrics: speed, acceleration and tortuosity were compared across phases of play and in-game win probability using 25 Hz optical player tracking data from all 52 matches at the 2019 FIFA Women’s World Cup. Comparing the distributions using the Kolmogorov–Smirnov test and Wasserstein distances, differences were identified in these movement profiles across, in and out of possession phases, with small negligible overall positional trends across in-game win probabilities. In-game win probabilities are used in tandem with phases to present a player specific case study. The results demonstrate how sports analytics metrics can be used to contextualise a subset of movement metrics from sport science and provide a framework for analysis of further movement metrics and sports analytics modelling approaches.
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