Cargando…

Analysis of a double Poisson model for predicting football results in Euro 2020

First developed in 1982, the double Poisson model, where goals scored by each team are assumed to be Poisson distributed with a mean depending on attacking and defensive strengths, remains a popular choice for predicting football scores, despite the multitude of newer methods that have been develope...

Descripción completa

Detalles Bibliográficos
Autores principales: Penn, Matthew J., Donnelly, Christl A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119507/
https://www.ncbi.nlm.nih.gov/pubmed/35588428
http://dx.doi.org/10.1371/journal.pone.0268511
_version_ 1784710716363636736
author Penn, Matthew J.
Donnelly, Christl A.
author_facet Penn, Matthew J.
Donnelly, Christl A.
author_sort Penn, Matthew J.
collection PubMed
description First developed in 1982, the double Poisson model, where goals scored by each team are assumed to be Poisson distributed with a mean depending on attacking and defensive strengths, remains a popular choice for predicting football scores, despite the multitude of newer methods that have been developed. This paper examines the pre-tournament predictions made using this model for the Euro 2020 football tournament. These predictions won the Royal Statistical Society’s prediction competition, demonstrating that even this simple model can produce high-quality results. Moreover, the paper also presents a range of novel analytic results which exactly quantify the conditions for the existence and uniqueness of the solution to the equations for the model parameters. After deriving these results, it provides a novel examination of a potential problem with the model—the over-weighting of the results of weaker teams—and illustrates the effectiveness of ignoring results against the weakest opposition. It also compares the predictions with the actual results of Euro 2020, showing that they were extremely accurate in predicting the number of goals scored. Finally, it considers the choice of start date for the dataset, and illustrates that the choice made by the authors (which was to start the dataset just after the previous major international tournament) was close to optimal, at least in this case. The findings of this study give a better understanding of the mathematical behaviour of the double Poisson model and provide evidence for its effectiveness as a match prediction tool.
format Online
Article
Text
id pubmed-9119507
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-91195072022-05-20 Analysis of a double Poisson model for predicting football results in Euro 2020 Penn, Matthew J. Donnelly, Christl A. PLoS One Research Article First developed in 1982, the double Poisson model, where goals scored by each team are assumed to be Poisson distributed with a mean depending on attacking and defensive strengths, remains a popular choice for predicting football scores, despite the multitude of newer methods that have been developed. This paper examines the pre-tournament predictions made using this model for the Euro 2020 football tournament. These predictions won the Royal Statistical Society’s prediction competition, demonstrating that even this simple model can produce high-quality results. Moreover, the paper also presents a range of novel analytic results which exactly quantify the conditions for the existence and uniqueness of the solution to the equations for the model parameters. After deriving these results, it provides a novel examination of a potential problem with the model—the over-weighting of the results of weaker teams—and illustrates the effectiveness of ignoring results against the weakest opposition. It also compares the predictions with the actual results of Euro 2020, showing that they were extremely accurate in predicting the number of goals scored. Finally, it considers the choice of start date for the dataset, and illustrates that the choice made by the authors (which was to start the dataset just after the previous major international tournament) was close to optimal, at least in this case. The findings of this study give a better understanding of the mathematical behaviour of the double Poisson model and provide evidence for its effectiveness as a match prediction tool. Public Library of Science 2022-05-19 /pmc/articles/PMC9119507/ /pubmed/35588428 http://dx.doi.org/10.1371/journal.pone.0268511 Text en © 2022 Penn, Donnelly https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Penn, Matthew J.
Donnelly, Christl A.
Analysis of a double Poisson model for predicting football results in Euro 2020
title Analysis of a double Poisson model for predicting football results in Euro 2020
title_full Analysis of a double Poisson model for predicting football results in Euro 2020
title_fullStr Analysis of a double Poisson model for predicting football results in Euro 2020
title_full_unstemmed Analysis of a double Poisson model for predicting football results in Euro 2020
title_short Analysis of a double Poisson model for predicting football results in Euro 2020
title_sort analysis of a double poisson model for predicting football results in euro 2020
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119507/
https://www.ncbi.nlm.nih.gov/pubmed/35588428
http://dx.doi.org/10.1371/journal.pone.0268511
work_keys_str_mv AT pennmatthewj analysisofadoublepoissonmodelforpredictingfootballresultsineuro2020
AT donnellychristla analysisofadoublepoissonmodelforpredictingfootballresultsineuro2020