Analyzing Soccer Data: Can Statistics Accurately Predict Future Results?
dc.contributor.author | Hanan, Muhammed | |
dc.date.accessioned | 2023-08-14T17:53:13Z | |
dc.date.available | 2023-08-14T17:53:13Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12648/12453 | |
dc.description.abstract | This paper looks to see if specific soccer statistics can accurately predict the results of future matches. This research shows what soccer statistics or prediction methods are the most reliable in predicting future soccer matches. The methods used in this research involve using three different models, model one uses home and away statistics, model two uses expected goals, and model three uses machine learning. The research concluded that machine learning is the most accurate in predicting the results of future soccer matches. Along with this, the paper touches on the history and future of soccer analytics, the collection and use of soccer data, and the limitations of statistics. | |
dc.subject | First Reader Athar Abdul-Quader | |
dc.subject | Senior Project | |
dc.subject | Semester Spring 2023 | |
dc.title | Analyzing Soccer Data: Can Statistics Accurately Predict Future Results? | |
dc.type | Senior Project | |
refterms.dateFOA | 2023-08-14T17:53:14Z | |
dc.description.institution | Purchase College SUNY | |
dc.description.department | Mathematics & Computer Science | |
dc.description.degreelevel | Bachelor of Arts | |
dc.description.advisor | Abdul-Quader, Athar | |
dc.date.semester | Spring 2023 | |
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