dc.contributor.author | Ötting, Marius | |
dc.contributor.author | Langrock, Roland | |
dc.contributor.author | Maruotti, Antonello | |
dc.date.accessioned | 2022-04-21T13:07:52Z | |
dc.date.available | 2022-04-21T13:07:52Z | |
dc.date.created | 2022-01-12T11:59:29Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 1863-8171 | |
dc.identifier.uri | https://hdl.handle.net/11250/2992055 | |
dc.description.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. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | A copula-based multivariate hidden Markov model for modelling momentum in football | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | Copyright 2021 The Author(s) | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |
dc.identifier.doi | 10.1007/s10182-021-00395-8 | |
dc.identifier.cristin | 1979321 | |
dc.source.journal | AStA Advances in Statistical Analysis | en_US |
dc.identifier.citation | AStA Advances in Statistical Analysis. 2021 | en_US |