ArticlePloS one2026
Efficient talent identification in women's football: A ranking-based approach for goal scoring analysis.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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.
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