Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/177699
Authors: 
Gorgi, P.
Koopman, Siem Jan
Lit, R.
Year of Publication: 
2018
Series/Report no.: 
Tinbergen Institute Discussion Paper TI 2018-009/III
Abstract: 
We propose a basic high-dimensional dynamic model for tennis match results with time varying player-specific abilities for different court surface types. Our statistical model can be treated in a likelihood-based analysis and is capable of handling high-dimensional datasets while the number of parameters remains small. In particular, we analyze 17 years of tennis matches for a panel of over 500 players, which leads to more than 2000 dynamic strength levels. We find that time varying player-specific abilities for different court surfaces are of key importance for analyzing tennis matches. We further consider several other extensions including player-specific explanatory variables and the accountance of specific configurations for Grand Slam tournaments. The estimation results can be used to construct rankings of players for different court surface types. We finally show that our proposed model can also be effective in forecasting. We provide evidence that our model significantly outperforms existing models in the forecasting of tennis match results.
Subjects: 
Sports statistics
Score-driven time series models
Rankings
Forecasting
JEL: 
C32
C53
Document Type: 
Working Paper
Social Media Mentions:

Files in This Item:
File
Size
747.12 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.