Evaluating defensive performance in soccer remains challenging, as effective defending is often expressed not through visible on-ball actions such as interceptions and tackles, but through preventing dangerous opportunities before they arise. Existing approaches have largely focused on valuing on-ball actions, leaving much of defenders' true impact unmeasured. To address this gap, we propose DEFCON (DEFensive CONtribution evaluator), a comprehensive framework that quantifies player-level defensive contributions for every attacking situation in soccer. Leveraging Graph Attention Networks, DEFCON estimates the success probability and expected value of each attacking option, along with each defender's responsibility for stopping it. These components yield an Expected Possession Value (EPV) for the attacking team before and after each action, and DEFCON assigns positive or negative credits to defenders according to whether they reduced or increased the opponent's EPV. Trained on 2023-24 and evaluated on 2024-25 Eredivisie event and tracking data, DEFCON's aggregated player credits exhibit strong positive correlations with market valuations. Finally, we showcase several practical applications, including in-game timelines of defensive contributions, spatial analyses across pitch zones, and pairwise summaries of attacker-defender interactions.

翻译：评估足球中的防守表现仍然具有挑战性，因为有效的防守往往并非通过抢断和铲球等可见的控球动作体现，而是通过在危险机会出现之前予以阻止。现有方法主要侧重于评估控球动作的价值，导致防守球员的真实影响在很大程度上未被衡量。为填补这一空白，我们提出了DEFCON（防守贡献评估器），这是一个量化足球中每次进攻情境下球员层面防守贡献的综合框架。利用图注意力网络，DEFCON估计每个进攻选项的成功概率和期望价值，以及每位防守球员阻止该选项的责任。这些组成部分分别得出进攻方在每次动作前后的期望控球价值，DEFCON根据防守球员是否降低或增加了对手的期望控球价值，为其分配正向或负向贡献值。基于2023-24赛季数据训练并在2024-25赛季荷甲赛事与追踪数据上评估，DEFCON聚合的球员贡献值与市场估值呈现强正相关性。最后，我们展示了若干实际应用，包括防守贡献的比赛时间线分析、球场区域的空间分析以及攻防球员互动的成对总结。