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Abstract Details
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Activity Number:
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107
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Type:
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Invited
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Date/Time:
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Monday, August 1, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #300455 |
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Title:
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Can Robust Quantile Regression Improve Valuation of Baseball Players?
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Author(s):
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Jonathan Lane*+ and David W. Scott
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Companies:
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Rice University and Rice University
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Address:
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, Houston, TX, ,
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Keywords:
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Quantile Regression ;
Robust Estimation ;
Baseball ;
Player Valuation
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Abstract:
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In Major League Baseball, teams spend large amounts of time, effort, and money to determine the value of individual players. In recent years, statistical analysis has been used, in addition to traditional scouting methods, to perform this valuation. By using statistical analysis, teams can estimate the value of a player's past performance, as well as predict the value that the player will produce in subsequent years. Here, we examine the effects of using robust quantile regression, particularly using L2 estimation, to perform these prediction and compare them to currently used prediction methods.
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