UCLA

Major League Baseball teams play considerably more games per season than the teams in any of the other major professional sports leagues in the United States, providing baseball fans with a large selection of games and frequently resulting in large fluctuations in attendance. In addition to studying the effect of the home and visiting teams' season win percentages on attendance, this paper examines various shorter-term metrics of performance to see which recent performance metric has the most significant impact on a home team’s game-to-game attendance numbers. The number of wins in a team’s previous 10 home games is shown to be statistically significant and the best recent performance metric to estimate attendance; however, the attendance prediction benefits are not practically much better than a simpler model that ignores such recent performance. This paper also discusses how the magnitude of the variation in a team’s attendance numbers can differ from team to team and from season to season and suggests using a team-season standardized attendance response variable to eliminate this difference in variance issue between low average / low variance, high average / high variance, and high average / low variance teams. The models with the team-season standardized response variable consistently outperform models with the traditional attendance response variable.