Baio, G;
Blangiardo, M;
(2010)
Bayesian hierarchical model for the prediction of football results.
Journal of Applied Statistics
, 37
(2)
253 - 264.
10.1080/02664760802684177.
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Abstract
The problem of modelling football data has become increasingly popular in the last few years and many different models have been proposed with the aim of estimating the characteristics that bring a team to lose or win a game, or to predict the score of a particular match. We propose a Bayesian hierarchical model to fulfil both these aims and test its predictive strength based on data about the Italian Serie A 1991-1992 championship. To overcome the issue of overshrinkage produced by the Bayesian hierarchical model, we specify a more complex mixture model that results in a better fit to the observed data. We test its performance using an example of the Italian Serie A 2007-2008 championship.
| Type: | Article |
|---|---|
| Title: | Bayesian hierarchical model for the prediction of football results |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/02664760802684177 |
| Publisher version: | http://dx.doi.org/10.1080/02664760802684177 |
| Language: | English |
| Additional information: | This is an electronic version of an article published in 'Baio, G; Blangiardo, M; (2010) Bayesian hierarchical model for the prediction of football results. Journal of Applied Statistics, 37 (2) 253 - 264. 10.1080/02664760802684177'. The Journal of Applied Statistics is available online at: http://www.tandfonline.com/loi/cjas. |
| Keywords: | Bayesian hierarchical models, overshrinkage, football data, bivariate Poisson distribution, Poisson-log normal model |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/16040 |
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