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Exploring the Kaggle European Soccer database with Bayesian Networks: the case of the Italian League Serie A
Last modified: 2018-05-17
Abstract
In the last decade, the application of statistical techniques to the sport field significantly increased. One of the most famous sports is the football and the present work deals with it. The data used come from the Kaggle European Soccer database. Players' performance indicators and their aggregation on the basis of the players' position or role (forward, midfielder, defender and goalkeeper) joined to the result of the match, are the variables taken into account. The statistical tool applied to these variables to predict the final result of a match is the Bayesian networks. Seasons from 2009/2010 to 2015/2016 and the Italian League Serie A constitute the data over which the statistical tool is trained.
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