肯德尔相关性和雷达图,在足球排名中纳入进球数和失球数

IF 1 4区 数学 Q3 STATISTICS & PROBABILITY Computational Statistics Pub Date : 2024-09-17 DOI:10.1007/s00180-024-01542-w
Roy Cerqueti, Raffaele Mattera, Valerio Ficcadenti
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引用次数: 0

摘要

本文探讨了体育比赛中运动队和运动员排名方式这一具有挑战性的主题。我们从足球这一典型案例出发,通过基于肯德尔相关性和雷达图的计算统计方法,提出了一种在官方全国锦标赛中对球队进行排名的新方法。具体而言,我们考虑了单场比赛中球队的进球数和失球数,将其作为除通常的胜平负三分法之外的另一种分数分配来源。我们的方法克服了目前采用的评分规则中的一些偏差。我们在 1930-2023 年期间举行的意大利甲级联赛冠军赛的相关案例中对这一方法建议进行了测试。
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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Kendall correlations and radar charts to include goals for and goals against in soccer rankings

This paper deals with the challenging themes of the way sporting teams and athletes are ranked in sports competitions. Starting from the paradigmatic case of soccer, we advance a new method for ranking teams in the official national championships through computational statistics methods based on Kendall correlations and radar charts. In detail, we consider the goals for and against the teams in the individual matches as a further source of score assignment beyond the usual win-tie-lose trichotomy. Our approach overcomes some biases in the scoring rules that are currently employed. The methodological proposal is tested over the relevant case of the Italian “Serie A” championships played during 1930–2023.

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来源期刊
Computational Statistics
Computational Statistics 数学-统计学与概率论
CiteScore
2.90
自引率
0.00%
发文量
122
审稿时长
>12 weeks
期刊介绍: Computational Statistics (CompStat) is an international journal which promotes the publication of applications and methodological research in the field of Computational Statistics. The focus of papers in CompStat is on the contribution to and influence of computing on statistics and vice versa. The journal provides a forum for computer scientists, mathematicians, and statisticians in a variety of fields of statistics such as biometrics, econometrics, data analysis, graphics, simulation, algorithms, knowledge based systems, and Bayesian computing. CompStat publishes hardware, software plus package reports.
期刊最新文献
Bayes estimation of ratio of scale-like parameters for inverse Gaussian distributions and applications to classification Multivariate approaches to investigate the home and away behavior of football teams playing football matches Kendall correlations and radar charts to include goals for and goals against in soccer rankings Bayesian adaptive lasso quantile regression with non-ignorable missing responses Statistical visualisation of tidy and geospatial data in R via kernel smoothing methods in the eks package
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