nflWAR: a reproducible method for offensive player evaluation in football
nflWAR: a reproducible method for offensive player evaluation in football
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nflWAR：一种可重复的足球进攻球员评估方法
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Maksim Horowitz
中科院分区：
文献类型：
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作者：
Ronald Yurko;Samuel L. Ventura;Maksim Horowitz
摘要 美式足球中现有的球员评估方法严重依赖专有数据，通常不可重复，落后于其他主要运动项目，并且无法解释比赛结果。我们提出了四项对足球统计研究的贡献来解决这些问题。首先，我们开发 R 包 nflscrapR，以便轻松访问来自国家橄榄球联盟 (NFL) 的公开实时数据。其次，我们引入了一种新颖的多项式逻辑回归方法来估计每场比赛的预期得分。第三，我们使用预期分数作为广义加性模型的输入来估计每次比赛的获胜概率。第四，我们介绍 nflWAR 框架，使用多级模型来隔离个人进攻技能球员在胜率高于替换（WAR）方面的贡献。我们通过专门为橄榄球设计的重采样方法评估 WAR 的不确定性，并提供 2017 年 NFL 赛季的结果。如果研究人员拥有指定每次比赛期间场上球员的数据，我们将讨论如何扩展我们的可重现 WAR 框架来估计任何位置球员的 WAR。最后，我们讨论这项工作对 NFL 球队的潜在影响。
Abstract Existing methods for player evaluation in American football rely heavily on proprietary data, are often not reproducible, lag behind those of other major sports, and are not interpretable in terms of game outcomes. We present four contributions to the study of football statistics to address these issues. First, we develop the R package nflscrapR to provide easy access to publicly available play-by-play data from the National Football League (NFL). Second, we introduce a novel multinomial logistic regression approach for estimating the expected points for each play. Third, we use the expected points as input into a generalized additive model for estimating the win probability for each play. Fourth, we introduce our nflWAR framework, using multilevel models to isolate the contributions of individual offensive skill players in terms of their wins above replacement (WAR). We assess the uncertainty in WAR through a resampling approach specifically designed for football, and we present results for the 2017 NFL season. We discuss how our reproducible WAR framework can be extended to estimate WAR for players at any position if researchers have data specifying the players on the field during each play. Finally, we discuss the potential implications of this work for NFL teams.
让我们疯狂的方法。
DOI：
10.1261/rna.049684.115
发表时间：
2015
期刊：
RNA (New York, N.Y.)
影响因子：
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作者：
Jacobson,Allan
通讯作者：
Jacobson,Allan