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Activity Number: 435 - SPEED: Sports to Fire: Fascinating Applications of Statistics
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 3:05 PM to 3:50 PM
Sponsor: Section on Statistics in Sports
Abstract #332636
Title: To Bet or Not to Bet - the Modified Kelly Criteria
Author(s): Dani Chu* and Yifan Wu and Tim Swartz
Companies: SFU Sports Analytics Club and Simon Fraser University and Simon Fraser University
Keywords: Bayes Estimation; Kelly Criterion; Minimax Estimation; Loss Functions; Sports Gambling

Our research considers an extension of the Kelly criterion used in sports wagering. By recognizing that the probability p of placing a correct wager is unknown, modified Kelly criteria are obtained that take the uncertainty into account. Estimators are proposed that are developed from a decision theoretic framework. We observe that the resultant betting fractions can differ markedly based on the choice of loss function. In the cases that we study, the modified Kelly fractions are smaller than original Kelly.

Authors who are presenting talks have a * after their name.

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