Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/286769 
Year of Publication: 
2021
Citation: 
[Journal:] AStA Advances in Statistical Analysis [ISSN:] 1863-818X [Volume:] 107 [Issue:] 1-2 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2021 [Pages:] 9-27
Publisher: 
Springer, Berlin, Heidelberg
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.
Subjects: 
Statistics, general
Statistics for Business, Management, Economics, Finance, Insurance
Probability Theory and Stochastic Processes
Econometrics
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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