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Correlation and agreement analysis in sports ranking
Journal of the Korean Data & Information Science Society 2019;30:159-70
Published online January 31, 2019;  https://doi.org/10.7465/jkdi.2019.30.1.159
© 2019 Korean Data and Information Science Society.

Dae Kee Min1 · Seunghee Pyeon2

12Department of Statistics and Information, Duksung Women’s University
Correspondence to: Professor, Department of Statistics and Information, Duksung Women’s University, Seoul, Korea. E-mail : dkmin@duksung.ac.kr
Received December 24, 2018; Revised January 21, 2019; Accepted January 21, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The method of ranking in sports is often determined by the intended use of the data. A point-based approach to using the World Sports Rating Systems (WSRS), as used in as skiing, tennis, or soccer, is used to award points based on performance in a given period of time. In this case, all the points are summed to obtain an average, and then a final rank is determined. Based on WSRS, it is beneficial to qualify to participate in a specific tournament or to have a partner in match play. These rankings, while useful data in the sports betting industry, could be sensitive data in terms of sports marketing. In this paper, we try to compare the correlation and the degree of consistency of the rankings created by various methods in sports and discuss the appropriateness of their use.
Keywords : Bland-Altman plot, concordance, correlation, intraclass correlation, Kendall’s tau.