Using Prediction Market Prices to Differentiate Factors that Influence the Highest and Lowest Priced Tickets in Dynamic Pricing for Major League Baseball

2015 ◽  
Vol 9 (2) ◽  
pp. 43-63
Author(s):  
Rodney Paul ◽  
Andrew Weinbach
Keyword(s):  
Dynamic Pricing ◽  
Major League Baseball ◽  
Prediction Markets ◽  
Market Prices ◽  
Betting Market ◽  
Major League ◽  
Similarities And Differences ◽  
Using Data ◽  
Ticket Prices ◽  
Uncertainty Of Outcome

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.

An Empirical Examination of the Development and Impact of Star Power in Major League Baseball

2016 ◽  
Vol 19 (2) ◽  
pp. 155-187 ◽  
Author(s):  
Michael Lewis ◽  
Yeujun Yoon
Keyword(s):  
Consumer Demand ◽  
Major League Baseball ◽  
Empirical Examination ◽  
Star Power ◽  
Team Success ◽  
Major League ◽  
Using Data ◽  
Ticket Prices ◽  
The Impact ◽  
Additional Variance

We examine the processes by which star power (SP) develops and the impact of SP on both consumer demand and team performance using data from Major League Baseball. First, we examine the dynamics of stardom using data based on player salaries, performance, and award recognition. We find that SP explains additional variance in salaries beyond performance measures. Also, we examine the impact of SP on consumer demand and team success. We find that a team’s stock of SP positively influences consumer demand, even after controlling for various factors ranging from team success to ticket prices.

Explaining Game-to-Game Ticket Sales for Major League Baseball Games Over Time

2011 ◽  
Vol 13 (5) ◽  
pp. 536-553 ◽  
Author(s):  
Elise M. Beckman ◽  
Wenqiang Cai ◽  
Rebecca M. Esrock ◽  
Robert J. Lemke
Keyword(s):  
Major League Baseball ◽  
Ticket Sales ◽  
Home Team ◽  
Major League ◽  
Potential Factors ◽  
Using Data ◽  
Uncertainty Of Outcome ◽  
Over Time

Using data from more than 10,000 games from 1985 through 2009, the authors estimate the effect various factors have on attendance at Major League Baseball (MLB) games. As previously found in the literature, interleague and interleague rivalry contests are associated with higher attendances, but this relationship has been weakening over time. Contrary to some of the literature, the authors find that the likelihood the home team will win the contest is inconsistently estimated over time, lending little support for the uncertainty of outcome hypothesis. Generally the effect on ticket sales from many potential factors has generally been weakening over time.

Behavioral Biases and Sportsbook Pricing in Major League Baseball

2012 ◽  
pp. 301-318 ◽  
Author(s):  
Rodney J. Paul ◽  
Andrew P. Weinbach
Keyword(s):  
Financial Markets ◽  
Market Efficiency ◽  
Major League Baseball ◽  
Prediction Markets ◽  
Large Margin ◽  
The Public ◽  
Sports Gambling ◽  
Betting Market ◽  
Major League ◽  
Alternative Theories

This article discusses the literature that uses sports gambling markets as an analogy to financial markets. It also expands the study of actual sportsbook behavior, comparing the traditional models to the Levitt hypothesis and considering alternative theories, by examining the betting market for Major League Baseball (MLB). The reverse favorite-longshot bias and home/road biases are then explored. It appears that bettors prefer road favorites by a large margin, but this is not captured by the sportsbook odds, which, likely not coincidentally, tend to map closer to actual favorite win percentages. There are no statistically significant returns to betting against the public. The findings that sportsbooks do not set prices to balance the book calls into question the source of some of the earlier findings of market efficiency in sports wagering markets and its underlying support for the forecasting power of prediction markets.

The Impact of Variable Pricing, Dynamic Pricing, and Sponsored Secondary Markets in Major League Baseball

2019 ◽  
Vol 21 (2) ◽  
pp. 115-138 ◽  
Author(s):  
Pascal Courty ◽  
Luke Davey
Keyword(s):  
Dynamic Pricing ◽  
Major League Baseball ◽  
Fixed Effect ◽  
Secondary Markets ◽  
Variable Pricing ◽  
Major League ◽  
Ticket Prices ◽  
Or Team ◽  
The Impact

Toward the end of the 1990s and into the 2000s, Major League Baseball teams moved away from fixed ticket prices, to first setting prices according to expected game demand, and subsequently to dynamically changing prices in response to demand. Teams have also collaborated with secondary ticket marketplaces to sponsor resale. By exploiting a team panel covering seasons 1999-2017, we use fixed effect models to estimate the impact of these pricing innovations on team revenue and team value. Variable pricing increases revenue and team value by 4.2% and 9.5%, respectively. The introduction of dynamic pricing and sponsored secondary markets has no statistically significant effect on revenue or team value.

scholarly journals The Effect Of Promotions On Attendance At Major League Baseball Games

2011 ◽  
Vol 24 (3) ◽  
Author(s):  
Anthony G. Barilla ◽  
Kathleen Gruben ◽  
William Levernier
Keyword(s):  
Regression Model ◽  
Multivariate Regression ◽  
Major League Baseball ◽  
Sporting Events ◽  
Multivariate Regression Model ◽  
Major League ◽  
Specific Factors ◽  
Using Data ◽  
Game Attendance

The determinants of attendance at professional sporting events come from a variety of team- specific, game-specific, and stadium-specific factors. Using data from the 2,431 major league baseball games played during the 2005 season, this study employs a multivariate regression model to determine the effect that the previously mentioned factors have on game attendance. The focus of the study is on the effect that promotions, such as product giveaways, have on attendance. The findings of this study indicate that having a promotion at a game increases attendance by about 1,532 fans. The findings also indicate that both the timing of a promotion and the type of promotion is important. Specifically, promotions held on weekends have a much smaller impact on attendance than promotions held during the week, with promotions held on Friday or Sunday having a particularly small effect. In terms of the type of promotion, this study finds that bobblehead giveaways have by far the largest impact on attendance and that several types of giveaways actually have no effect on attendance.

scholarly journals Variable Ticket Pricing in Major League Baseball

2007 ◽  
Vol 21 (3) ◽  
pp. 407-437 ◽  
Author(s):  
Daniel A. Rascher ◽  
Chad D. McEvoy ◽  
Mark S. Nagel ◽  
Matthew T. Brown
Keyword(s):  
San Francisco ◽  
Major League Baseball ◽  
Sport Organizations ◽  
Ticket Pricing ◽  
Price Increases ◽  
Special Events ◽  
Variable Pricing ◽  
Major League ◽  
Sport Teams ◽  
Ticket Prices

Sport teams historically have been reluctant to change ticket prices during the season. Recently, however, numerous sport organizations have implemented variable ticket pricing in an effort to maximize revenues. In Major League Baseball variable pricing results in ticket price increases or decreases depending on factors such as quality of the opponent, day of the week, month of the year, and for special events such as opening day, Memorial Day, and Independence Day. Using censored regression and elasticity analysis, this article demonstrates that variable pricing would have yielded approximately $590,000 per year in additional ticket revenue for each major league team in 1996, ceteris paribus. Accounting for capacity constraints, this amounts to only about a 2.8% increase above what occurs when prices are not varied. For the 1996 season, the largest revenue gain would have been the Cleveland Indians, who would have generated an extra $1.4 million in revenue. The largest percentage revenue gain would have been the San Francisco Giants. The Giants would have seen an estimated 6.7% increase in revenue had they used optimal variable pricing.

Short-Run Demand and Uncertainty of Outcome in Major League Baseball

2010 ◽  
Vol 37 (3) ◽  
pp. 197-214 ◽  
Author(s):  
Scott Tainsky ◽  
Jason A. Winfree
Keyword(s):  
Major League Baseball ◽  
Major League ◽  
Short Run ◽  
Uncertainty Of Outcome

scholarly journals A study of efficiency in New Zealand election prediction markers

2021 ◽  
Author(s):  
◽  
Tram P. Cao
Keyword(s):  
Unit Root Test ◽  
Prediction Markets ◽  
Opinion Poll ◽  
Market Pricing ◽  
Market Prices ◽  
Arbitrage Opportunities ◽  
Election Prediction ◽  
Using Data ◽  
Abnormal Profits ◽  
Poll Data

<p>The development of prediction markets has naturally given rise to studies of their efficiency. Most studies of efficiency in prediction markets have focused on the speed with which they incorporate information. A necessary (but not sufficient) condition of efficiency is that arbitrage opportunities must non-existent or transitory in nature so that the systematic generation of abnormal profits is not possible. Using data from New Zealand’s first prediction market, iPredict, I examine the potential for arbitrage in the contracts for the party vote for the 2011 General Election. Relative to the risk-free interest rate, the returns from arbitrage are generally low, consistent with an efficient market. Regression analysis requires that the data not be subject to the possibility of spurious regressions - something that is not addressed in the literature. After confirming the non-stationarity of the price level and the stationarity of the price changes by the unit root test, I use the iPredict data in conjunction with opinion poll data to test whether the polls impact on market pricing behaviour. Using a number of different model types, I find that the opinion poll data has a very limited impact on market prices, suggesting that the information contained in the poll is largely already incorporated into market prices.</p>

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