Honors Thesis Archive
| Author | Clara Andersen |
|---|---|
| Title | Modeling Major League Baseball Hall of Fame Players |
| Department | Mathematics |
| Advisor | Alyssa Hoofnagle |
| Year | 2022 |
| Honors | Departmental Honors |
| Full Text | View Thesis (1447 KB) |
| Abstract | The purpose of this research project was to investigate what baseball statistics predict whether or not a player is inducted into the Baseball Hall of Fame. I focused on the quantitative factors that influence induction, rather than the qualitative factors, such as sportsmanship or ethics. I collected and cleaned the data from the Lahman’s Database that included all baseball players, managers, executives, and umpires that have been on the Hall of Fame ballot since its establishment in 1936. Only the individuals who were voted on as players were included in the analysis. I used multiple logistic regression methods and created various models to evaluate their ability to predict players’ induction into the Hall of Fame. Based on the players who have already been inducted into the Hall of Fame, I used the models to determine if the stars of the 2006 St. Louis Cardinals should be enshrined based on their career statistics as of today. I chose the 2006 Cardinals because they won the World Series and are considered one of the greatest teams in Cardinals history, so I wanted to see if the players on arguably the best Cardinals team would be enshrined. I broadened the scope and applied the models to players over the age of 35 and those who were on the Hall of Fame ballot from 2019 to 2022 to predict if they will be voted into the Hall of Fame. |
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