Recovery Latency Trajectories Before Injury in Elite Women's Football

Para o Zenodo, a descrição que aparece na página do depósito deve ser assim: Title: Recovery Latency Derived Dataset and Analysis Code — SoccerMon Cohort (2020–2021) Description: This repository contains the derived dataset and analysis scripts associated with the manuscript: Silva AA. Recovery Latency Trajectories Before Injury in Elite Women's Football. International Journal of Sports Physiology and Performance. 2025 [Submitted]. All derived variables were computed from the publicly available SoccerMon dataset (Midoglu et al., 2022; doi:10.5281/zenodo.10033832), which contains longitudinal monitoring data from 50 elite women's football players across two Norwegian top-flight clubs (Toppserien) over two complete competitive seasons (2020–2021). This repository contains only variables derived by the authors. Raw SoccerMon data are not redistributed — they are available at the original Zenodo repository above. Derived variables include: Recovery Latency (RL) — time in days for individual readiness to return to ≥95% of a 7-day rolling baseline following a high-load training event (≥75th percentile individual daily load); Dynamic Adaptive Capacity (DAC) slope — linear slope of RL over sequential events per athlete; astronomical photoperiod computed for Bergen, Norway (~60°N); and injury proximity flags derived from clinical records. Files: soccermon_rl_derived.csv — 3,616 event-level observations across 49 athletes; compute_rl.py — full Python pipeline for RL and DAC computation with CLI interface and sensitivity analysis grid. Keywords: recovery monitoring; athlete monitoring; injury prediction; women's football; Recovery Latency; Dynamic Adaptive Capacity; training load; photoperiod; SoccerMon