Kendall correlations and radar charts to include goals for and goals against in soccer rankings

Roy Cerqueti; Raffaele  Mattera; Valerio Ficcadenti

doi:10.1007/s00180-024-01542-w

Kendall correlations and radar charts to include goals for and goals against in soccer rankings

Roy Cerqueti, Raffaele Mattera, Valerio Ficcadenti

Finance, Economics, Accounting and Analytics

University of Rome La Sapienza

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Abstract

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.

Original language	English
Journal	Computational statistics
DOIs	https://doi.org/10.1007/s00180-024-01542-w
Publication status	Published - 17 Sept 2024

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10.1007/s00180-024-01542-w

s00180-024-01542-wFinal published version, 1.58 MBLicence: CC BY 4.0

Cite this

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title = "Kendall correlations and radar charts to include goals for and goals against in soccer rankings",

abstract = "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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AB - 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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