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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp012z10wq33p
Title: What Actually Wins Soccer Matches: Prediction of the 2011-2012 Premier League for Fun and Profit
Authors: Snyder, Jeffrey
Advisors: Schapire, Robert
Department: Computer Science
Class Year: 2013
Abstract: Sports analytics is a fascinating problem area in which to apply statistical learning techniques. This thesis brings new data to bear on the problem of predicting the outcome of a soccer match. We use frequency counts of in-game events, sourced from the Manchester City Analytics program, to predict the 380 matches of the 2011-2012 Premier League season. We generate prediction models with multinomial regression and rigorously test them with betting simulations. An extensive review of prior efforts is presented, as well as a novel theoretically optimal betting strategy. We measure performance different feature sets and betting strategies. Accuracy and simulated profit far exceeding those of all earlier efforts are achieved.
Extent: 52 pages
URI: http://arks.princeton.edu/ark:/88435/dsp012z10wq33p
Access Restrictions: Walk-in Access. This thesis can only be viewed on computer terminals at the Mudd Manuscript Library.
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Computer Science, 1988-2016

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