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English(EN) Credit Attribution in Timestamped Soccer Networks Using Multivariate Hawkes Processes

新指标 xGI 使用 Hawkes 过程量化球员贡献

研究人员开发了一种名为预期进球参与度 (xGI) 的新指标,以更好地量化球员在足球比赛中的贡献。该指标利用多元 Hawkes 过程 (MHPs) 对传球和射门的连续时间序列进行建模,从而可以将功劳分配给进攻序列中的多个传球。与仅归功于进球前最后一次传球的传统统计数据不同,xGI 识别出在创造得分机会方面发挥关键作用的球员,从而提供对进攻参与度和球员表现更全面的看法。 AI

影响 引入了一种新颖的事件序列分析统计方法,可能适用于体育分析以外的其他领域。

排序理由 学术论文,详细介绍了一种新的统计方法和指标。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新指标 xGI 使用 Hawkes 过程量化球员贡献

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学术论文,详细介绍了一种新的统计方法和指标。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Phillip W. Kornberg, Kevin S. Xu ·

    使用多元 Hawkes 过程对带时间戳的足球网络进行信用归因

    arXiv:2610.12775v1 Announce Type: cross Abstract: The two main traditional player statistics used in soccer are goals scored and assists, with an assist credited when a player's pass immediately leads to a teammate scoring. Attributing credit solely to the player who makes the fi…