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Abstract Details
Activity Number:
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319
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Type:
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Invited
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Date/Time:
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Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract - #300020 |
Title:
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Hierarchical Bayesian Modeling of Hitting Performance in Baseball
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Author(s):
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Shane Jensen*+ and Blakeley McShane and Abraham Wyner
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Companies:
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The Wharton School and The Wharton School and The Wharton School
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Address:
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, , ,
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Keywords:
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baseball ;
hidden Markov model ;
hierarchical Bayes
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Abstract:
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We have developed a sophisticated statistical model for predicting the hitting performance of Major League baseball players. The Bayesian paradigm provides a principled method for balancing past performance with crucial covariates, such as player age and position. We share information across time and across players by using mixture distributions to control shrinkage for improved accuracy. We compare the performance of our model to current sabermetric methods on a held-out season (2006), and discuss both successes and limitations.
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Authors who are presenting talks have a * after their name.
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