DF Percy
Generic handicapping for paralympic sports
Percy, DF
Authors
Abstract
Class handicapping methods enable different classes of athletes to compete on equal terms. Different sports use a variety of algorithms, which are usually based on historical data and subjective opinions. A recent proposal is to use an interactive shrinkage method for class handicapping, as this is generic across sports and uses data from the current competition only.
This article presents a mathematical justification of the interactive shrinkage method for class handicapping, based on an objective Bayesian analysis of a suitable probability model. It also investigates how this approach performs in the context of paralympic sports, by analysing actual competition data and comparing the results with those from existing schemes. Our findings suggest that this method is robust, convenient and fair. A discussion follows, to explore possible extensions of this procedure.
Citation
Percy, D. (2012). Generic handicapping for paralympic sports. IMA Journal of Management Mathematics, 24(3), 349-361. https://doi.org/10.1093/imaman/dps013
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 29, 2012 |
Publication Date | Jul 25, 2012 |
Deposit Date | Nov 14, 2013 |
Journal | IMA Journal of Management Mathematics |
Print ISSN | 1471-678X |
Publisher | Oxford University Press |
Peer Reviewed | Peer Reviewed |
Volume | 24 |
Issue | 3 |
Pages | 349-361 |
DOI | https://doi.org/10.1093/imaman/dps013 |
Publisher URL | http://dx.doi.org/10.1093/imaman/dps013 |
Related Public URLs | http://imaman.oxfordjournals.org/ |
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search