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标题：恢复潜伏期衍生数据集与分析代码——SoccerMon队列（2020–2021年） 描述： 本仓库包含与下述学术论文相关的衍生数据集与分析脚本： 席尔瓦AA.《精英女子足球运动员受伤前的恢复潜伏期轨迹》，《国际运动生理学与运动表现杂志》，2025年【已投稿】。 所有衍生变量均源自公开可得的SoccerMon数据集（SoccerMon，Midoglu等，2022；doi:10.5281/zenodo.10033832），该数据集涵盖2020–2021年两个完整竞技赛季中，挪威两家顶级联赛（Toppserien）俱乐部的50名精英女子足球运动员的纵向监测数据。 本仓库仅收录作者衍生得到的变量，原始SoccerMon数据集不予重新分发，相关数据可从上述原始Zenodo仓库获取。 衍生变量包括：恢复潜伏期（Recovery Latency，RL）——指个体在经历高负荷训练事件（个人单日训练负荷≥第75百分位数）后，恢复至7日滚动基线水平≥95%所需的天数；动态适应能力（Dynamic Adaptive Capacity，DAC）斜率——每名运动员的恢复潜伏期随连续训练事件变化的线性斜率；为挪威卑尔根（约北纬60°）计算的天文光照时长；以及从临床记录中衍生得到的受伤临近预警标记。 文件说明： soccermon_rl_derived.csv——涵盖49名运动员的3616条事件级观测样本； compute_rl.py——用于恢复潜伏期与动态适应能力计算的完整Python流程脚本，支持命令行接口与敏感性分析网格搜索。 关键词：恢复监测；运动员监测；损伤预测；女子足球；恢复潜伏期；动态适应能力；训练负荷；光照时长；SoccerMon