Within-player load-wellness monitoring and lower-limb pain in elite female football: A reproducible secondary analysis of the SoccerMon dataset

Routine athlete-monitoring data can test whether within-player changes in training load and wellness precede health problems, but sparse outcomes and incomplete reporting complicate inference. We conducted a reproducible secondary longitudinal analysis of the public SoccerMon dataset, comprising 50 players from two Norwegian elite women’s football teams monitored in 2020–2021. The outcome was onset on day t (the index player-day) of a self-reported lower-limb pain/injury episode after a 7-day episode washout. The primary risk set contained 42 onset-days from 15 players; the complete-case soreness interaction analysis contained 28 onset-days from nine event players. Under retrospective full-period within-player standardization, the focal acute-load x soreness interaction was estimated below 1.0 by Firth logistic regression (odds ratio [OR] 0.63, 95% confidence interval [CI] 0.45–0.97), but uncertainty remained substantial. When within-player standardization was recalculated using only observations available before each day, the interaction attenuated to OR 0.97 (0.73–1.25). These data therefore do not provide stable evidence that within-player load deviations or load x wellness interactions are associated with next-day self-reported lower-limb pain onset. Sparse events, event concentration, missing monitoring data, and team/season imbalance further limit precision. In practice, daily load and wellness signals should be interpreted as contextual longitudinal information rather than as stand-alone next-day risk thresholds.