How is artificial intelligence being used to monitor performance within women's football

Player tracking and movement analysis in women’s football

Optical systems e.g., TRACAB and wearable GPS devices e.g., Catapult collect highfrequency location and motion data for each player: positio

Tactical and opponent analysis

Machine learning models process match video and event data to extract formations, passing networks and pressing patterns, then cluster and c

Injury risk prediction and load management

AI systems integrate multiple data streams — external workload GPS distance, accelerations, internal load heart rate, perceived exertion, bi

Performance enhancement and skill development

Computer vision and poseestimation tools use video and machinelearning models to track players’ body positions, joint angles and movement tr

Recruitment and Talent ID — Predictive Models in Women’s Football

Predictive models analyze large datasets from youth and lowerleague matches e.g., tracking, event, physical and demographic data to estimate

Match preparation and set‑piece optimization

AI systems analyze large amounts of historical match data passes, shots, player locations, outcomes to simulate many possible in‑game scenar

Broadcast Analytics and Fan-Facing Metrics in Women’s Football

AI processes tracking and event data from matches to produce advanced statistics e.g., expected goals, pressing intensity, packing and clear