Multivariate approaches to investigate the home and away behavior of football teams playing football matches

Antonello D’Ambra (), Pietro Amenta () and Antonio Lucadamo ()
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Antonello D’Ambra: University of Campania “Luigi Vanvitelli”
Pietro Amenta: University of Sannio
Antonio Lucadamo: University of Sannio

Computational Statistics, 2025, vol. 40, issue 4, No 6, 1779-1799

Abstract: Abstract Compared to other European competitions, participation in the Uefa Champions League is a real “bargain” for football clubs due to the hefty bonuses awarded based on performance during the group qualification phase. To perform successfully in football depends on several multidimensional factors, and analyzing the main ones remains challenging. In the performance study, little attention has been paid to teams’ behavior when playing at home and away. Our study combines statistical techniques to develop a procedure to examine teams’ performance. Several considerations make the 2022–2023 Serie A league season particularly interesting to analyze with our approach. Except for Napoli, all the teams showed different home-and-away behaviors concerning the results obtained at the season’s end. Ball possession and corners have positively influenced scored points in both home and away games with a different impact. The precision indicator was not an essential variable. The procedure highlighted the negative roles played by offside, as well as yellow and red cards.

Keywords: Multidimensional scaling; External information; Count data models; Lasso; Football (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00180-024-01553-7

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