PARX model for football matches predictions

Angelini, Giovanni ; De Angelis, Luca (2016) PARX model for football matches predictions. Bologna, IT: Dipartimento di Scienze Statistiche "Paolo Fortunati", Alma Mater Studiorum Università di Bologna, p. 25. DOI 10.6092/unibo/amsacta/5408. In: Quaderni di Dipartimento. Serie Ricerche (2). ISSN 1973-9346.
Full text available as:
[img]
Preview
Text(pdf)
License: Creative Commons Attribution Non-commercial No Derivatives

Download (516kB) | Preview

Abstract

We propose an innovative approach to model and predict the outcome of football matches based on the Poisson Autoregression with eXogenous covariates (PARX) model recently proposed by Agosto, Cavaliere, Kristensen and Rahbek (2016). We show that this methodology is particularly suited to model the goals distribution of a football team and provides a good forecast performance that can be exploited to develop a profitable betting strategy. The betting strategy is based on the idea that the odds proposed by the market do not reflect the true probability of the match because they may incorporate also the betting volumes or strategic price settings in order to exploit bettors’ biases. The out-of-sample performance of the PARX model is better than the reference approach by Dixon and Coles (1997). We also evaluate our approach in a simple betting strategy which is applied to the English football Premier League data for the 2013/2014 and 2014/2015 seasons. The results show that the return from the betting strategy is larger than 35% in all the cases considered and may even exceed 100% if we consider an alternative strategy based on a predetermined threshold which allows to exploit the inefficiency of the betting market.

Abstract
Document type
Monograph (Working Paper)
Creators
CreatorsAffiliationORCID
Angelini, GiovanniUniversità di Bologna0000-0003-3000-9885
De Angelis, LucaUniversità di Bologna0000-0003-3222-2620
Keywords
Sports forecasting, Density forecasts, Count data, Poisson autoregression, Bet- ting market. Previsioni sportive, Previsioni di densità, Dati di conteggio, Autoregressione di Poisson, Mercato delle scommesse.
Subjects
ISSN
1973-9346
DOI
Deposit date
12 Sep 2016 06:50
Last modified
08 May 2017 13:24
URI

Other metadata

Downloads

Downloads

Staff only: View the document

^