Predicting the Outcome of a Football Game: A Comparative Analysis of Single and Ensemble Analytics Methods

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dc.contributor.author Eryarsoy, Enes
dc.contributor.author Delen, Dursun
dc.date.accessioned 2019-01-02T23:49:09Z
dc.date.available 2019-01-02T23:49:09Z
dc.date.issued 2019-01-08
dc.description.abstract As analytical tools and techniques advance, increasingly large numbers of researchers apply these techniques on a variety of different sports. With nearly 4 billion followers, it is estimated that association football, or soccer, is the most popular sports for fans across the world by a large margin. The objective of this study is to develop a model to predict the outcomes of soccer (or association football) games (win-loss-draw), and determine factors that influence game outcomes. We used 10 years of comprehensive game-level data spanning the years 2007-2017 in the Turkish Super League, and tested a variety of classifiers to identify the most promising methods for outcome predictions.
dc.format.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2019.136
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59550
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Data, Text, and Web Mining for Business Analytics
dc.subject Decision Analytics, Mobile Services, and Service Science
dc.subject Association Football, analytics, predictive modeling, soccer
dc.title Predicting the Outcome of a Football Game: A Comparative Analysis of Single and Ensemble Analytics Methods
dc.type Conference Paper
dc.type.dcmi Text
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