纪念卡尔-莫里斯在体育分析方面的贡献

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS

Journal of Quantitative Analysis in Sports Pub Date : 2024-01-05 DOI:10.1515/jqas-2023-0092

Jim Albert

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引用次数: 0

摘要

卡尔-莫里斯（Carl Morris）1938-2023 年，因其在贝叶斯多参数推理和预测方面的开创性研究而闻名于世。莫里斯还因其在体育领域的统计思想和方法论的发展而闻名。本文概述了莫里斯在体育领域的贡献。其中包括莫里斯年轻时的体育经历、莫里斯利用体育数据做出的一些最著名贡献的摘要、他对学生工作的影响以及莫里斯对统计与体育相互作用的一些思考。

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Contributions of Carl Morris in sports analytics, a memorium

Carl Morris 1938–2023 was well-known for his pioneering research in Bayesian multiparameter inference and prediction. Morris was also known for his development of statistical thinking and methodology in sports. This paper provides an overview of Morris’ contributions in sports. This includes Morris’ experience in sports as a youth, summaries of some of Morris’ best-known contributions using sports data, his influence working with students, and some of Morris’ thinking about the interplay of statistics and sports.

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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.