Outcome Uncertainty, Fan Travel, and Aggregate Attendance

Abstract

The uncertainty of outcome hypothesis (UOH) informs economists' understanding of consumer decisions to attend sporting events and team revenue generation. We develop a model of fan behavior based on standard expected utility methods which incorporates fan heterogeneity in terms of decisions to travel to away games and strong preferences for wins. The model reflects aggregate attendance outcomes across local and visiting fans, generates predictions consistent with the UOH, and gives rise to concave league‐wide revenue functions. Empirical analysis of game outcomes and attendance at regular season National Basketball association games from 1979 to 2013 supports key predictions of the model. (JEL L83, D12, Z20)

Disaggregated Attendance Demand: Comparing Daily Ticket Purchasers and Season Ticket Holders in K-League 1

“…These findings show that sports fans are affected by the presence of high-performing, conspicuous, and/or distinguished athletic prowess. Matchday characteristics, such as the day of the match (Buraimo & Simmons, 2008; Forrest & Simmons, 2006), the timing of the event (Krumer, 2020), and the geographical distance between competing teams (Humphreys & Miceli, 2020; Wooten, 2018), are commonly used as determinants of sports demand. These studies revealed that weekend matches or post work-hour matches would enjoy increased attendance.…”

Revisiting the Uncertainty of Outcome Hypothesis and the Loss Aversion Hypothesis in the National Basketball Association: Adding a Predicted Game Quality Perspective

“…To capture the curvilinear nature of the effect of predicted outcome uncertainty on attendance, we also included the squared term of PS in the model ( PS 2 ). Although some researchers have applied an additional step to calculate winning probabilities from betting odds (e.g., Kuypers, 2000; Paul et al, 2021; Sung & Mills, 2018), we relied on PS (e.g., Brown & Salaga, 2018; Coates & Humphreys, 2010; Humphreys & Miceli, 2020) for three reasons. First, our study focused on basketball.…”

“…Second, the number of all-star players on the home ( HAS ) and away ( AAS ) teams in the previous season was included. Star players have been found to influence consumer demand in the NBA (Hausman & Leonard, 1997; Humphreys & Miceli, 2020), Bundesliga (Feddersen & Rott, 2011), and MLS (Sung & Mills, 2018). Third, the Euclidian distance between the home and away teams’ cities (Distance) was measured based on Google Maps and included in our model because visiting-team fans’ travel costs affect their interest in attending a game (Humphreys & Miceli, 2020).…”

“…1 When the home team is favored, attendance will be higher than for games with an uncertain outcome because fans want to see the home team win (Humphreys & Miceli, 2020). When the home team is an underdog, attendance will be better than for games with an uncertain outcome because fans hope to see an upset (Humphreys & Miceli, 2020).…”

College football attendance in the long run: The Football Championship Subdivision

“…(e.g.,Falls & Natke, 2014Humphreys & Miceli, 2020). Travel cost for a specific season is measured by the national real per-mile fuel cost of driving a private automobile.…”