Modelling football data

Abstract

The main goal of this dissertation is to investigate the Bayesian modelling performance for football data. An extensive study of Markov processes and the Bayesian statistical approach is carried out. In particular, special reference is made to the radical Markov Chain Monte Carlo sampling technique. Using real data from the Italian serie A championship, a Bayesian modelling application (as according to the rationale of professors Gianluca Baio and Martha A. Blangiardo) is considered and confronted with the performance of a comparable generalised linear model.