Predicting Football Match Results Using a Poisson Regression Model

Currently, several techniques based on probabilities and statistics, along with the rapid advancements in computational power, have deepened our understanding of a football match result, giving us the capability to estimate future matches’ results based on past performances. The ability to estimate the number of goals scored by each team in a football match has revolutionized the perspective of a match result for both betting market professionals and fans alike. The Poisson distribution has been widely used in a number of studies to model the number of goals a team is likely to score in a football match. Therefore, the match result can be estimated using a double Poisson regression model—one for each participating team. In this study, we propose an algorithm, which, by using Poisson distributions along with football teams’ historical performance, is able to predict future football matches’ results. This algorithm has been developed based on the Premier League’s—England’s top-flight football championship—results from the 2022–2023 season.

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Publication Details

Journal
Applied Sciences
Published
2024-08-16
DOI
https://doi.org/10.3390/app14167230
Citations
5
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
5.65
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article

Predicting Football Match Results Using a Poisson Regression Model

Georgios Feretzakis, Dimitrios Karapiperis, Vassilios S. Verykios, Konstantinos Loukas
5 citations
Applied Sciences
Sports Analytics and Performance
5.65
article

Predicting Football Match Results Using a Poisson Regression Model

Georgios Feretzakis, Dimitrios Karapiperis, Vassilios S. Verykios, Konstantinos Loukas
article en
5 citations

Abstract

Currently, several techniques based on probabilities and statistics, along with the rapid advancements in computational power, have deepened our understanding of a football match result, giving us the capability to estimate future matches’ results based on past performances. The ability to estimate the number of goals scored by each team in a football match has revolutionized the perspective of a match result for both betting market professionals and fans alike. The Poisson distribution has been widely used in a number of studies to model the number of goals a team is likely to score in a football match. Therefore, the match result can be estimated using a double Poisson regression model—one for each participating team. In this study, we propose an algorithm, which, by using Poisson distributions along with football teams’ historical performance, is able to predict future football matches’ results. This algorithm has been developed based on the Premier League’s—England’s top-flight football championship—results from the 2022–2023 season.

Applied SciencesVol. 14(16)
International Hellenic University (GR), Hellenic Open University (GR)
Openalex Percentile: Top 4%
Sports Analytics and Performance
5.65
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Predicting Football Match Results Using a Poisson Regression Model — Georgios Feretzakis, Dimitrios Karapiperis, et al. · Applied Sciences (2024) | TGRS Research Map | TGRS