This contribution provides an empirical analysis on player position on the field throughout a football match. To identify potential phases of the game, a Bayesian mixture of experts model is defined where the relationship between the location of a player and their teammates is specified using a mixture via a flexible formulation of the component weights, which are modelled as smooth functions of concomitant covariates. The analysis shows that player positions can be decomposed into phases of play that are related to the other teammates’ locations on the field.

Berrettini, M., Galimberti, G., Brendan Murphy, T., Ranciati, S. (2025). Modelling Football Players’ Field Position via Mixtures of Gaussians with Flexible Weights. Cham : Springer Nature [10.1007/978-3-031-84702-8_3].

Modelling Football Players’ Field Position via Mixtures of Gaussians with Flexible Weights

Marco Berrettini
;
Giuliano Galimberti;Saverio Ranciati
2025

Abstract

This contribution provides an empirical analysis on player position on the field throughout a football match. To identify potential phases of the game, a Bayesian mixture of experts model is defined where the relationship between the location of a player and their teammates is specified using a mixture via a flexible formulation of the component weights, which are modelled as smooth functions of concomitant covariates. The analysis shows that player positions can be decomposed into phases of play that are related to the other teammates’ locations on the field.
2025
Statistical Models and Learning Methods for Complex Data
17
24
Berrettini, M., Galimberti, G., Brendan Murphy, T., Ranciati, S. (2025). Modelling Football Players’ Field Position via Mixtures of Gaussians with Flexible Weights. Cham : Springer Nature [10.1007/978-3-031-84702-8_3].
Berrettini, Marco; Galimberti, Giuliano; Brendan Murphy, Thomas; Ranciati, Saverio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1033150
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