首次将xT和VAEP应用于手球，量化进攻传球价值。
H-VAEP and H-xT: Valuing Offensive On-the-Ball Actions in Handball by Estimating Probabilities
- 基于手球场地特点设计分区网格，提升评分稳定性。
- 模型在5个赛季数据上验证，玩家评分更精准区分贡献。
- 适合俱乐部战术分析与球员评估，代码开源可复用。
传统手球球员评估依赖基础统计数据或经验指标，无法体现多队员配合的进攻链条价值。尽管足球领域已采用预期威胁（xT）和动作价值估计（VAEP）等事件级评分框架，但这些方法尚未适配手球。本文首次系统性地将xT与VAEP引入手球分析，使用德国手球联赛五年追踪事件数据进行建模。我们提出手球专用的H-xT，采用符合手球特点的场地分区结构，仿真表明其比标准矩形网格更具鲁棒性；同时优化了手球版H-VAEP，通过调整特征空间与上下文长度，有效减少球队身份泄露问题。评估结果显示，H-VAEP生成的球员评分具有高度稳定性、区分度与直观性，能准确反映进攻组织贡献。最后，我们开源完整代码库，支持职业俱乐部部署应用。
原文摘要 · Abstract (English)
Traditional player evaluation in professional handball relies on basic box-score metrics or heuristic indices, which fail to credit the multi-player build-up chain. While football (soccer) analytics has adopted Expected Threat (xT) and Valuing Actions by Estimating Probabilities (VAEP), these event-based action valuation frameworks have not yet been adapted to handball. In this paper, we present the first comprehensive adaptation and evaluation of xT and VAEP for handball, utilizing five seasons of tracking-derived event data from the Handball Bundesliga. We develop Handball-xT (H-xT) using a handball-native court zoning layout, demonstrating via simulations that it is systematically more robust than standard rectangular grids. We optimize Handball-VAEP (H-VAEP) by tailoring its feature space and selecting the context length to limit team-identity leakage. Our evaluation shows that H-VAEP yields exceptionally stable, discriminative, and intuitive player ratings that highlight build-up play. Finally, we release our complete code repository to help professional clubs deploy these models.
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