A traceable path from wearable data to football decisions.

Study scope

The source paper was prepared for a Wuhan University essay competition using retrospective, anonymised data from three youth squads. It is an applied methods paper, not a peer-reviewed medical or sports-science publication.

The final analysis included 61 players, 39 valid dates and 343 player-days after device binding, session-record review and trajectory-quality checks.

Time windows are part of the measurement.

ATHLOS aligns events, squad lists, devices and selected player windows using China Standard Time and Unix timestamps. Multiple valid intervals can be combined without treating breaks or device-off periods as exposure.

The analysis separates volume, intensity and context: effective duration and total distance describe volume; distance per minute and high-speed structure add intensity; the session type and the player’s own history provide context.

The same number can mean different things in different sessions.

Total distance can change because playing time, selected windows or task structure changed. Distance density and high-speed running add useful detail, but they still require the drill, role and coach observation.

Cross-squad differences in this material support separate internal baselines. They do not establish age norms or justify ranking players across teams.

Useful analysis starts with clear limits.

The workflow supports training review, load planning and longitudinal development. Medical diagnosis, selection decisions and public player ranking require separate professional processes and evidence.