Tactical category importance analysis.

Individual goal-scoring analysis in women’s football faces severe class imbalance and limited scouting resources, where classification metrics alone do not capture operational efficiency. We analyzed 2,535 non-goalkeeper player-match observations from the 2023 FIFA Women’s World Cup (736 unique players) with 51 performance features, excluding match-outcome variables to emphasize individual actions. Using nested cross-validation, LightGBM captured 79.4% of goal-scoring observations within the top 20% of ranked observations; an out-of-bag (OOB) bootstrap gains analysis yielded 73.9% capture at Top 20% (lift = 3.69x; 95% CI: 63.9%−84.3%). Permutation and SHAP consensus highlighted tactical availability (Total Offers) and combined technical/physical workload indicators (Passes Attempted, Jogging Distance, Top Speed). This proof-of-concept study shows that ranking-based evaluation improves scouting efficiency using basic match statistics, while thresholds and feature weights require validation in other competitive contexts.

女子足球的个体进球分析面临严重的类别不平衡问题与有限的球探资源困境，仅依靠分类指标无法反映球员的赛场运作效率。本研究分析了2023年国际足联女子世界杯（2023 FIFA Women’s World Cup）中的2535次非守门员球员的单场比赛观测样本，涵盖736名独特球员，共包含51项比赛表现特征，且为突出个体行为，剔除了比赛结果相关变量。本研究采用嵌套交叉验证（nested cross-validation）方法，轻量梯度提升树（LightGBM）在按模型评分排名前20%的观测样本中，成功覆盖了79.4%的进球观测样本；袋外（out-of-bag, OOB）自助增益分析结果显示，其在排名前20%的样本中覆盖比例达73.9%（提升倍数=3.69倍；95%置信区间：63.9%−84.3%）。置换特征重要性与SHAP联合分析显示，战术可得性（Total Offers，总战术机会）以及结合技术与体能的负荷指标（Attempted Passes，尝试传球数；Jogging Distance，慢跑距离；Top Speed，最高速度）为核心特征。本概念验证研究表明，基于排名的评估方法可通过基础比赛统计数据提升球探工作效率，但相关阈值与特征权重仍需在其他竞技赛事场景中进行验证。