Prediction of football match results with Machine Learning

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Fátima
Data de Publicação: 2022
Outros Autores: Pinto, Ângelo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/21230
Resumo: Football is one of the most popular sports in the world, so the perception of the game and the prediction of results is of general interest to fans, coaches, media and gamblers. Although predicting football results is a very complex task, the football betting business has grown over time. The unpredictability of football results and the growing betting business justify the development of prediction models to support gamblers. In this article, we develop machine learning methods that take multiple statistics of previous matches and attributes of players from both teams as inputs to predict the outcome of football matches. Several prediction models were tested, with the experimental results showing encouraging performance in terms of the profit margin of football bets.
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spelling Prediction of football match results with Machine LearningData miningSports bettingFeature selectionClassificationFootballFootball is one of the most popular sports in the world, so the perception of the game and the prediction of results is of general interest to fans, coaches, media and gamblers. Although predicting football results is a very complex task, the football betting business has grown over time. The unpredictability of football results and the growing betting business justify the development of prediction models to support gamblers. In this article, we develop machine learning methods that take multiple statistics of previous matches and attributes of players from both teams as inputs to predict the outcome of football matches. Several prediction models were tested, with the experimental results showing encouraging performance in terms of the profit margin of football bets.ElsevierRepositório Científico do Instituto Politécnico do PortoRodrigues, FátimaPinto, Ângelo2022-12-21T12:24:50Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/21230eng10.1016/j.procs.2022.08.057info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T13:16:44Zoai:recipp.ipp.pt:10400.22/21230Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:41:00.904552Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Prediction of football match results with Machine Learning
title Prediction of football match results with Machine Learning
spellingShingle Prediction of football match results with Machine Learning
Rodrigues, Fátima
Data mining
Sports betting
Feature selection
Classification
Football
title_short Prediction of football match results with Machine Learning
title_full Prediction of football match results with Machine Learning
title_fullStr Prediction of football match results with Machine Learning
title_full_unstemmed Prediction of football match results with Machine Learning
title_sort Prediction of football match results with Machine Learning
author Rodrigues, Fátima
author_facet Rodrigues, Fátima
Pinto, Ângelo
author_role author
author2 Pinto, Ângelo
author2_role author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Rodrigues, Fátima
Pinto, Ângelo
dc.subject.por.fl_str_mv Data mining
Sports betting
Feature selection
Classification
Football
topic Data mining
Sports betting
Feature selection
Classification
Football
description Football is one of the most popular sports in the world, so the perception of the game and the prediction of results is of general interest to fans, coaches, media and gamblers. Although predicting football results is a very complex task, the football betting business has grown over time. The unpredictability of football results and the growing betting business justify the development of prediction models to support gamblers. In this article, we develop machine learning methods that take multiple statistics of previous matches and attributes of players from both teams as inputs to predict the outcome of football matches. Several prediction models were tested, with the experimental results showing encouraging performance in terms of the profit margin of football bets.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-21T12:24:50Z
2022
2022-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/21230
url http://hdl.handle.net/10400.22/21230
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.procs.2022.08.057
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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