Nonlinear Modeling of European Football Scores
Using Support Vector Machines

Übernahme per Copy & Paste
Bibtex-Export
Endnote-Export

[Zeitschriftenartikel]

Markellos, Raphael Nicholas

(357 KByte)

Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):http://nbn-resolving.de/urn:nbn:de:0168-ssoar-242840

Abstract	This paper 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 indicate 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 modeling 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.
Klassifikation	Volkswirtschaftstheorie; Wirtschaftssektoren
Sprache Dokument	Englisch
Publikationsjahr	2008
Seitenangabe	S. 111-118
Zeitschriftentitel	Applied Economics, 40 (2008) 1
DOI	http://dx.doi.org/10.1080/00036840701731546
ISSN	1466-4283
Status	Postprint; begutachtet (peer reviewed)
Lizenz	PEER Licence Agreement (applicable only to documents from PEER project)