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June 2018 A Comparison of Truncated and Time-Weighted Plackett–Luce Models for Probabilistic Forecasting of Formula One Results
Daniel A. Henderson, Liam J. Kirrane
Bayesian Anal. 13(2): 335-358 (June 2018). DOI: 10.1214/17-BA1048

Abstract

We compare several variants of the Plackett–Luce model, a commonly-used model for permutations, in terms of their ability to accurately forecast Formula One motor racing results. A Bayesian approach to forecasting is adopted and a Gibbs sampler for sampling from the posterior distributions of the model parameters is described. Prediction of the results from the 2010 to 2013 Formula One seasons highlights clear strengths and weaknesses of the various models. We demonstrate by example that down weighting past results can improve forecasts, and that some of the models we consider are competitive with the forecasts implied by bookmakers odds.

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Daniel A. Henderson. Liam J. Kirrane. "A Comparison of Truncated and Time-Weighted Plackett–Luce Models for Probabilistic Forecasting of Formula One Results." Bayesian Anal. 13 (2) 335 - 358, June 2018. https://doi.org/10.1214/17-BA1048

Information

Published: June 2018
First available in Project Euclid: 28 February 2017

zbMATH: 06989951
MathSciNet: MR3780426
Digital Object Identifier: 10.1214/17-BA1048

Keywords: Bayesian inference , Gibbs sampling , latent variable models , permutations , ranks , sport

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Vol.13 • No. 2 • June 2018
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