Attendance data in sports leagues are organized at more than one level and thus are nested data with factors varying by individual games (e.g. single game attendance figure), which are nested within the factors varying by teams (e.g. local population and income level, stadium). Such a nested data structure requires a multilevel modeling approach for an accurate examination of attendance. Also, although the previous application of multilevel modeling to sport attendance research has been limited to the data aggregated and averaged by seasons or by teams, no multilevel modeling of attendance data at the individual game level is available. The uniqueness of the current study is its extension of the multilevel modeling approach by analyzing the audience data at the individual game level. Thus, this study examined the relationship between attendance determinants and single game attendance in a Major League Baseball (MLB) season by using multilevel modeling with 14 game level variables and 12 team level variables. Twelve predictors (e.g. home/visiting team playoff appearances, day of game, season progress, ticket price, stadium capacity, game uncertainty) significantly (p <.05) influenced attendance.