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Nonlinear modelling of European football scores using support vector machines

Vlastakis, N and Dotsis, G and Markellos, R (2008) 'Nonlinear modelling of European football scores using support vector machines.' Applied Economics, 40 (1). 111 - 118. ISSN 0003-6846

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Abstract

This article explores the linear and nonlinear forecastability of European football match scores using IX2 and Asian Handicap odds data from the English Premier league. To this end, we compare the performance of a Poisson count regression to that of a nonparametric Support Vector Machine (SVM) model. Our descriptive analysis of the odds and match outcomes indicates that these variables are strongly interrelated in a nonlinear fashion. An interesting finding is that the size of the Asian Handicap appears to be a significant predictor of both home and away team scores. The modelling results show that while the SVM is only marginally superior on the basis of statistical criteria, it manages to produce out-of-sample forecasts with much higher economic significance.

Item Type: Article
Subjects: H Social Sciences > HD Industries. Land use. Labor
Divisions: Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Essex Finance Centre
Depositing User: Clare Chatfield
Date Deposited: 04 Apr 2014 08:49
Last Modified: 30 Jan 2019 16:16
URI: http://repository.essex.ac.uk/id/eprint/7251

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