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Analysis of football prediction methods

Nowadays football betting is becoming more and more popular around the world.
In the last few years several works have been done and improved in order to develop models able to predict the outcome of football matches. In our analysis we study the Dixon-Coles model for the full-time scores and then we focus our attention on the difference of goals, since it seems to be more advantageous than modelling the scores themselves. We develop two basic models for the difference of goals based on the discrete Normal distribution that gives us interesting results as compared to the Skellam distribution. Furthermore we study the Dixon-Robinson model for the goal times and we investigate the possible clustering of goal times data. Using self-exciting point processes, we found that the scoring rate in a football match tends to be higher during the minutes straight after a goal has been scored. Our general results want to be a solid starting point for more sophisticated analyses.

Mostra/Nascondi contenuto.
1. Introduction Football is one of the most popular sports in the world. Every day people watch matches all over the world. Consequently betting on the outcome of football matches is having a considerable interest by football supporters and simple betting fans. Every week a huge number of bookmakers offers an infinite amount of odds on the various results of a match. Bets can be placed on the final outcome, but also on the exact score, on the halfnulltime and fullnulltime results, on the margin of victory and so on. Furthermore, also thanks to the global diffusion of internet, in the last few years the sonullcalled “innullrunning betting” is getting more and more common among the betters since people can place a bet while they are following the match in progress. Unlike in the other types of betting, such as in horsenullracing, the odds are given around one week before the football matches are played. In this way we could make a detailed comparison of bookmakers' odds and identify who offers the most profitable odds for each match. That is why a statistical model able to accurately predict the probabilities of the outcome of football matches has the potential to create the basis for an optimal betting strategy. Various proposals have been made for modelling the outcome of football matches. For a good betting strategy, however, probabilities must be estimated on a teamnullspecific basis, so that the probabilities of the various match outcomes between two specific teams on a particular date can be calculated. The first complete model able to allow for the different team effects and also for the fluctuating performance of individual teams was made by Dixon and Coles (1997). The goals scored by the home and the away teams have different Poisson distributions and a sort of dependence between them is introduced. 8

Tesi di Laurea Magistrale

Facoltà: Scienze Statistiche

Autore: William Brojanigo Contatta »

Composta da 180 pagine.


Questa tesi ha raggiunto 749 click dal 13/01/2012.


Consultata integralmente 9 volte.

Disponibile in PDF, la consultazione è esclusivamente in formato digitale.