A Statistical approach to predict future members of the Baseball Hall of Fame
The purpose of this study was to construct an accurate statistical model for the members of the baseball hall of fame and use this model to predict future hall of fame members, using a frequentist approach. Using logistic regression, accurate models were determined for each position that can be used to predict if a certain player will make it into the Hall of Fame. Baseball-Reference.com was the major source of data. Once the analysis was complete, nine different models were chosen to determine the probability that a certain player at a given position would make it into the Hall of Fame based on their baseball statistics. Positions were also analyzed by time periods and models were found for each position in each time frame, if one existed. In general, time period models for the various positions were inconclusive, however a model for each position was found overall.
Networked Digital Library of Theses and Dissertations