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

Artikel

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: AStA Advances in Statistical Analysis ; ISSN: 1863-818X ; Volume: 107 ; Year: 2021 ; Issue: 1-2 ; Pages: 9-27 ; Berlin, Heidelberg: Springer

Classification and Topics

• Classification: Mathematik
• Subject: Statistics, general ; Statistics for Business, Management, Economics, Finance, Insurance ; Probability Theory and Stochastic Processes ; Econometrics

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Ötting, Marius ; Langrock, Roland ; Maruotti, Antonello
• Event: Veröffentlichung
• (who): Springer
• (where): Berlin, Heidelberg
• (when): 2021

Further information

• DOI: doi:10.1007/s10182-021-00395-8
• Last update: 10.03.2025, 11:42 AM CET