In the last decade, the application of statistical techniques to the sport field significantly increased. One of the most famous sports in the world is the soccer (football), and the present work deals with it, using data referred to the seasons from 2009/2010 to 2015/2016 of the Italian League Serie A extracted from the Kaggle European Soccer database. The players’ overall performance indicators, obtained on the basis of the players’ position or role (forward, midfielder, defender and goalkeeper), are used to predict the result of the matches by applying the Bayesian Networks as well as the Naive Bayes and the Binomial Logistic Regression models, considered as their competitors.
Exploring the Kaggle European Soccer database with Bayesian Networks: the case of the Italian League Serie A
Maurizio Carpita;Silvia Golia
2018-01-01
Abstract
In the last decade, the application of statistical techniques to the sport field significantly increased. One of the most famous sports in the world is the soccer (football), and the present work deals with it, using data referred to the seasons from 2009/2010 to 2015/2016 of the Italian League Serie A extracted from the Kaggle European Soccer database. The players’ overall performance indicators, obtained on the basis of the players’ position or role (forward, midfielder, defender and goalkeeper), are used to predict the result of the matches by applying the Bayesian Networks as well as the Naive Bayes and the Binomial Logistic Regression models, considered as their competitors.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
