Abstract
In this article an approach for the analysis and prediction of soccer match results is proposed. It is based on a regularized Poisson regression model that includes various potentially influential covariates describing the national teams' success in previous FIFA World Cups. Additionally, similar to Bradley-Terry-Luce models, differences of team-specific effects of the competing teams are included. It is discussed that within the generalized linear model (GLM) framework the team-specific effects can either be incorporated in the form of fixed or random effects. In order to achieve variable selection and shrinkage, we use tailored Lasso approaches. Based on the three preceding FIFA World Cups, two competing models for the prediction of the FIFA World Cup 2014 are fitted and investigated.
Item Type: | Paper |
---|---|
Keywords: | Football, FIFA World Cup 2014, Sports tournaments, Generalized linear model, Lasso, Variable selection |
Faculties: | Mathematics, Computer Science and Statistics > Statistics > Technical Reports |
Subjects: | 500 Science > 510 Mathematics |
URN: | urn:nbn:de:bvb:19-epub-21072-4 |
Language: | English |
Item ID: | 21072 |
Date Deposited: | 02. Jul 2014, 16:16 |
Last Modified: | 04. Nov 2020, 13:01 |