Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/59550

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

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Title:Predicting the Outcome of a Football Game: A Comparative Analysis of Single and Ensemble Analytics Methods
Authors:Eryarsoy, Enes
Delen, Dursun
Keywords:Data, Text, and Web Mining for Business Analytics
Decision Analytics, Mobile Services, and Service Science
Association Football, analytics, predictive modeling, soccer
Date Issued:08 Jan 2019
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.
Pages/Duration:9 pages
URI:http://hdl.handle.net/10125/59550
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.136
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Data, Text, and Web Mining for Business Analytics


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