Using Prediction Market Prices to Differentiate Factors that Influence the Highest and Lowest Priced Tickets in Dynamic Pricing for Major League Baseball
The use of prediction markets is extended to explain differences in preferences of fans that purchase different price levels of tickets under dynamic pricing for Major League Baseball. Using data from eleven teams, this research investigates similarities and differences in variables that affect ticket prices for the highest-priced and lowest-priced tickets. Key contrasts between the groups are found to stem from distinct preferences for uncertainty of outcome, measured by betting market odds, and team quality. It is also shown that differences between the groups are attributable to sensitivity to factors such as key opponents, weekend games, opening day, and temperature.