Theses and Dissertations

Student sections at college sporting events are an integral part of the collegiate experience. They provide a heightened atmosphere and passion that professional teams can not always attract. They are an exciting social event for students to be a part of a larger community. The student section also represents a new potential market base for athletic departments. If students don't go to games, they have less of an emotional attachment when it comes to giving back to their alma mater in their peak earning years. (Dodd, 2022). Therefore, it is vital to understand the factors that influence a student’s intention to return to future games and, in recent years, the decline in student attendance. There are many variables that contribute to student attendance, so a study was developed to attempt to predict a student’s intention to return to future Arizona State University basketball games. There are multiple factors that are considered when determining the attendance such as the demographics of the student or their level of fandom. In addition, other factors such as social media use can influence a student’s intention to return. A statistical analysis was performed to determine which of these factors are most important in order to build a model to predict intention to return. An exploratory factor analysis will be used to determine which variables of the survey are correlated and measure similar factors. Then regression techniques will help analyze each independent variable to determine their importance and relevance. Through these techniques, it was found that satisfaction of stadium factors, sport club participation, on-campus housing, athlete’s social media, and total attendance positively impact attendance while importance of stadium factors, interest in fan loyalty programs, and employment status negatively impact attendance. The following report will include details of the analysis. The model that was developed will help universities narrow the potential variables that impact student attendance to assist in future research.

This thesis aims to develop a new way to value players for all teams in the MLB, despite the financial disparity. Displayed in the rest of this paper, is a player valuation model created around each team's salary level, focusing on the player’s offensive output. The model functions in a way that values players by their ability to help their team score runs and win games by setting parameters for salary expectations based on player performance. This allows for small market MLB teams, like the Cleveland Guardians, to build a roster of players around their specific salary limit, specifically to score the maximum runs and win games. On the contrary, the model also works for big market teams, like the Los Angeles Dodger, allowing them to project their larger salary limit to players and build their ideal roster as well.