Date of Award

6-2025

Degree Name

MS in Statistics

Department/Program

Statistics

College

College of Science and Mathematics

Advisor

Kelly N. Bodwin

Advisor Department

Statistics

Advisor College

College of Science and Mathematics

Abstract

This study investigates “bandwagon” behavior among Major League Baseball (MLB) fans by analyzing Google search interest data from 2004 to 2019. Drawing on publicly available information from Google Trends, the analysis explores how fluctuations in search activity align with team performance during both the regular season and postseason. Hierarchical linear models are used to estimate expected levels of fan interest based on team performance and market characteristics. Deviations from these expectations during the regular season are interpreted as evidence of bandwagon or anti-bandwagon behavior. A drop-off in interest following playoff elimination is also examined to capture shifts in fan attention within the postseason window. To address scaling limitations inherent in Google Trends, a rescaling and normalization method is developed, enabling consistent comparisons across teams and time periods. This approach includes both monthly data in the regular season and daily data in the postseason, with particular attention paid to the heightened volatility and spikes in postseason interest. The findings reveal substantial variability in fan engagement, with certain teams demonstrating pronounced regular season and postseason bandwagon effects. This research offers a novel framework for quantifying fan loyalty using digital search data.

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