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http://hdl.handle.net/11375/20695
Title: | WASP: An Algorithm for Ranking College Football Teams |
Authors: | Earl, Jonathan |
Advisor: | McNicholas, Paul |
Department: | Mathematics and Statistics |
Keywords: | Ranking;Football;Statistics;Principal Component Analysis |
Publication Date: | 2016 |
Abstract: | Arrow's Impossibility Theorem outlines the flaws that effect any voting system that attempts to order a set of objects. For its entire history, American college football has been determining its champion based on a voting system. Much of the literature has dealt with why the voting system used is problematic, but there does not appear to be a large collection of work done to create a better, mathematical process. More generally, the inadequacies of ranking in football are a manifestation of the problem of ranking a set of objects. Herein, principal component analysis is used as a tool to provide a solution for the problem, in the context of American college football. To show its value, rankings based on principal component analysis are compared against the rankings used in American college football. |
URI: | http://hdl.handle.net/11375/20695 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Earl_Jonathan_A_201610_MSc.pdf | 637.29 kB | Adobe PDF | View/Open |
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