Here is a pdf of my most recent school project: Predicting Day-to-Day Variability in Baseball Attendance to Support Staffing
It details how I used 30 years of attendance data at MLB games to determine what is important in predicting attendance. A lot of businesses surrounding stadiums rely upon accurate forecasts of attendance in order to staff their business appropriately. If the effect of short-term factors (weather, recent performance) dominate, schedulers would do well to wait until the last minute to put out a staff schedule. However, it seems that long-term factors (date/time of game, opponent, performance in past seasons) dominates the attendance regression, giving schedulers the ability to put out schedules well in advance of gameday. A missing short-term regressor in my paper is pitching matchup. If star starting pitchers really bring more fans to the game, that might increase the importance of the short-term factors.