Investigating trade-offs made by American football linebackers using tracking data

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS

Journal of Quantitative Analysis in Sports Pub Date : 2023-07-21 DOI:10.1515/jqas-2022-0091

Eric Eager, Tej Seth

引用次数: 0

Abstract

Abstract In recent years, the game of football has made a shift towards being more quantitative. With the advent of charting and tracking data, player evaluation is able to be studied from several different angles. In this paper, we build and refine two novel metrics: Bite Distance Under Expected (BDUE) and Ground Covered Over Expected (GCOE) for the evaluation of linebackers in the National Football League (NFL). Here, we show that these metrics are heavily correlated with each other, which demonstrates the trade-off linebackers have to make between being aggressive against the run and being effective when the opposing offense is using play-action. We also show that these metrics are more stable than those in the public space. Finally, we show how these metrics measure deception by opposing offenses.

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利用追踪数据调查美式橄榄球中后卫的取舍

摘要近年来，足球运动向着量化方向发展。随着图表和追踪数据的出现，玩家评估可以从多个不同的角度进行研究。在本文中，我们建立并完善了两个新的指标:咬距低于预期(BDUE)和地面覆盖超过预期(GCOE)，用于评估国家橄榄球联盟(NFL)的线卫。在这里，我们展示了这些指标彼此之间的高度相关性，这表明了线卫必须在对抗跑动的侵略性和当对方进攻使用动作时的有效性之间做出权衡。我们还表明，这些指标比公共空间的指标更稳定。最后，我们展示了这些指标是如何通过反对冒犯来衡量欺骗的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Quantitative Analysis in Sports SOCIAL SCIENCES, MATHEMATICAL METHODS-

CiteScore

2.00

自引率

12.50%

发文量

期刊介绍： The Journal of Quantitative Analysis in Sports (JQAS), an official journal of the American Statistical Association, publishes timely, high-quality peer-reviewed research on the quantitative aspects of professional and amateur sports, including collegiate and Olympic competition. The scope of application reflects the increasing demand for novel methods to analyze and understand data in the growing field of sports analytics. Articles come from a wide variety of sports and diverse perspectives, and address topics such as game outcome models, measurement and evaluation of player performance, tournament structure, analysis of rules and adjudication, within-game strategy, analysis of sporting technologies, and player and team ranking methods. JQAS seeks to publish manuscripts that demonstrate original ways of approaching problems, develop cutting edge methods, and apply innovative thinking to solve difficult challenges in sports contexts. JQAS brings together researchers from various disciplines, including statistics, operations research, machine learning, scientific computing, econometrics, and sports management.