Predicting Football Outcomes

Predicting Football Outcomes: with Bayesian Networks

van Dijk, Max (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Delft Institute of Applied Mathematics)

Nane, Tina (mentor)
van Elderen, Emiel (graduation committee)
van Iersel, Leo (graduation committee)

Delft University of Technology

2019-07-11

In this thesis Bayesian Networks are used to predict European football matches between the years 2008 and 2016. The goal of this research is to see how the structures learned by different Bayesian Network learning algorithms influences the predictions. First the data is explored and modified to be used for Bayesian Networks and secondly the theory is explained using examples. Finally the theory is applied on the data and the structures are learned with the help of a bootstrap method and the predictions are validated using 5-fold cross validation. We can conclude that the networks learned by the algorithms and with the help of an expert give a good representation of the underlying relationships, but are not very good in prediction the end result.

Bayesian Networks
Football
Prediction

http://resolver.tudelft.nl/uuid:ceaaf8cf-cc03-48b3-8ef6-679263e26998

Student theses

bachelor thesis

© 2019 Max van Dijk