An empirical Bayes model for time-varying paired comparisons ratings : who is the greatest women’s tennis player?

Baker, RD ORCID: https://orcid.org/0000-0003-3555-3425 and McHale, IG 2017, 'An empirical Bayes model for time-varying paired comparisons ratings : who is the greatest women’s tennis player?' , European Journal of Operational Research, 258 (1) , pp. 328-333.

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Abstract

We present a methodology for fitting a time-varying paired comparisons model using an empirical Bayes approach. The model simultaneously avoids two problems that typically arise with paired comparisons data: first, that extreme values of estimated strengths can occur for competitors appearing in and winning a small number of games, producing absurd rankings, and second, that the time-varying strengths ‘balloon’ over time. The empirical Bayes approach automatically shrinks the strength estimates towards the mean, thus avoiding both issues. We present our model and demonstrate its use in the setting of tennis in search of an answer to the question: who is the greatest women’s player of all time. Our results suggest that Steffi Graf is a strong candidate, but, using confidence intervals on the rankings themselves, others cannot be ruled out.

Item Type:	Article
Schools:	Schools > Salford Business School
Journal or Publication Title:	European Journal of Operational Research
Publisher:	Elsevier
ISSN:	0377-2217
Related URLs:	Publication
Funders:	Non funded research
Depositing User:	Professor Ian G. McHale
Date Deposited:	10 Nov 2016 10:44
Last Modified:	15 Feb 2022 21:24
URI:	https://usir.salford.ac.uk/id/eprint/40728

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