Physical Sciences and Mathematics Commons^™

Top Of The Order: Modeling The Optimal Locations Of Minor League Baseball Teams, W. Coleman Conley

Undergraduate Economic Review

Over the last twenty-five years, minor league baseball franchises have defined firm mobility. Revisiting the work of Michael C. Davis (2006), I construct a logistic regression model to predict which cities house minor league baseball teams. Six variables are tested for inclusion in the model, including population, income level, the number of major-league professional sports teams in a city, five-year population change, and distance from the closest professional team. Based on the model's predicted probabilities, cities are ranked in order of highest probability of having a team at each of the different levels from Class A to Class AAA.

Success In Professional Baseball: The Value Of Above Average Position Players, Heath Detweiler

Senior Honors Theses

In professional baseball, efficient spending is the key to success. Because modern player contracts are so costly, front offices must seek out the most valuable players. In addition, to reach the playoffs, teams need offensively above average players at some positions. Together, these facts lead to an interesting question of whether or not defensive position impacts the value of offensively above average players. To answer this question, reliable metrics of offensive ability must be employed and appropriately analyzed.

Through an analysis involving on-base percentage, park-adjusted linear weights, and weighted on-base average over the course of the 2010 through 2013 Major …