A copula-based multivariate hidden Markov model for modelling momentum in football

Marius Ötting (), Roland Langrock and Antonello Maruotti
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Marius Ötting: Bielefeld University
Roland Langrock: Bielefeld University
Antonello Maruotti: Libera Universita Maria Ss. Assunta

AStA Advances in Statistical Analysis, 2023, vol. 107, issue 1, No 2, 9-27

Abstract: Abstract We investigate the potential occurrence of change points—commonly referred to as “momentum shifts”—in the dynamics of football matches. For that purpose, we model minute-by-minute in-game statistics of Bundesliga matches using hidden Markov models (HMMs). To allow for within-state dependence of the variables, we formulate multivariate state-dependent distributions using copulas. For the Bundesliga data considered, we find that the fitted HMMs comprise states which can be interpreted as a team showing different levels of control over a match. Our modelling framework enables inference related to causes of momentum shifts and team tactics, which is of much interest to managers, bookmakers, and sports fans.

Date: 2023
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DOI: 10.1007/s10182-021-00395-8

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