Publicação
Prediction of football match results with Machine Learning
| dc.contributor.author | Rodrigues, Fátima | |
| dc.contributor.author | Pinto, Ângelo | |
| dc.date.accessioned | 2022-12-21T12:24:50Z | |
| dc.date.available | 2022-12-21T12:24:50Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | 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. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1016/j.procs.2022.08.057 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.22/21230 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Elsevier | pt_PT |
| dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S1877050922007955 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.subject | Data mining | pt_PT |
| dc.subject | Sports betting | pt_PT |
| dc.subject | Feature selection | pt_PT |
| dc.subject | Classification | pt_PT |
| dc.subject | Football | pt_PT |
| dc.title | Prediction of football match results with Machine Learning | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 470 | pt_PT |
| oaire.citation.startPage | 463 | pt_PT |
| oaire.citation.title | Procedia Computer Science | pt_PT |
| oaire.citation.volume | 204 | pt_PT |
| person.familyName | Rodrigues | |
| person.givenName | Maria de Fátima Coutinho | |
| person.identifier.orcid | 0000-0003-4950-7593 | |
| person.identifier.scopus-author-id | 7101624989 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | d144c436-b126-4215-aff5-909fc2f87302 | |
| relation.isAuthorOfPublication.latestForDiscovery | d144c436-b126-4215-aff5-909fc2f87302 |