Ticket Price Comparison of Double-A and Triple-A Affiliate Baseball Leagues

### Abstract

As the economy continues to decline, sport managers realize that discretionary spending is limited. As such, sport managers are giving more consideration to price strategies within their own marketing mix as well as their comparison to other sport teams. The purpose of this study was to conduct a cross-sectional pricing investigation of individual teams by region within a Class-AAA and Class-AA league from the minor league baseball system. Data were obtained for ticket prices and fees from baseball team websites and phone interviews. Multivariate analysis of variance was examined for both Double-A and Triple-A leagues divided into regions. This study found no significant F (1,6) = .09, p = .77 differences for the highest ticket prices, F (1,6) = .09, p = .78, or the lowest ticket prices, and F (1,6) = .07, p = .80 for the groups within the Double-A Affiliate Texas League. However, a significance F (2,13) = 8.08, p = .00 was found in lowest ticket price within the Triple-A Affiliate Pacific Coast League, unlike highest ticket prices and fees which were not measurably different. Most minor league sport managers could consider this advantageous for promoting their entertainment as a good economic value.

**Key Words:** Baseball, Ticket Prices, Minor League

### Introduction

In light of recent economic times, sport organizations are faced with the challenge of maintaining a competitive marketplace while keeping a close eye on the bottom line. At the same time, the economic market watch (9) indicates consumers are becoming more selective with discretionary spending. Since sport consumption is not a fundamental cost of living, sport organizations have had to take a hard look at their strategic placement in the market. Pricing is a fundamental component of the marketing mix (6). Economic strategists have recommended complex formulas to establish pricing structures (2), while many sport organizations are opting for simplicity (6). In fact, Mullin, Hardy, and Sutton (6) said “the core issues in any pricing situation are cost, value, and objectives” (p. 215). In keeping with the simple pricing strategies that are the focus today, many sport franchises have utilized price comparisons as a simple and effective method of determining where a sport organization “fits” in the regional and league markets.

#### Price Comparisons

Determining the best fit in the sport consumer marketplace and how pricing strategies align with peer teams has become an emphasis for sport managers within the minor league baseball industry. As baseball ticket prices increase (1) and pricing strategies become complex (7), baseball consumers may look to alternative discretionary spending investments. Price comparison consumption behaviors have increased exponentially with the convenience of the Internet (5). Websites like Pricerunner, Amazon, and Shop.com have allowed potential consumers to price shop merchandise with several companies at the same time. Sport organizations have not considered price comparisons as a major influence on strategic pricing, due to the uniqueness offered in sport consumption. For example, sporting events occur sometimes great distances apart whereby a potential consumer may traditionally only be willing to travel 30 miles (4) and therefore do not offer a competitive risk to the local sport organization. However, as seen in recent articles (e.g., 3, 8) with a click of a button, price comparisons are made. In today’s tumultuous economy, many sport organizations have elected to market their event as a “value” within the discretionary spending category. This marketing technique is not only being utilized in relation to their direct sport competition, but also with discretionary spending businesses in general (e.g. cinema, concerts, other types of sporting events).

It was hypothesized that there was a significant (p < .05) difference between Texas and Non-Texas regions when comparing ticket pricing (highest price, lowest price, and ticketing fee) for minor league baseball Class-AA Texas League, as well as a significant (p < .05) difference among West, South, and Central regions when comparing ticket pricing (highest price, lowest price, and ticketing fee) for minor league baseball Class-AAA Pacific Coast League. Additionally, it was hypothesized that there was a significant (p < .05) difference between Double-A and Triple-A affiliate leagues when comparing ticket pricing (highest price, lowest price, and ticketing fee). This study examined price comparisons of minor league professional baseball teams segmented by league and region. A selection criterion was based upon geographic region of the minor league baseball teams as well as a comparison between Class-AA and Class-AAA organizations. Tables 1 and 2 represent the teams included in the study organized by league and region.

### Methods

#### Procedures

The data were collected through a variety of methods. Most of the information was collected through individual team websites. Some information was obtained though cold-calling via landline phones, and remaining data were provided through personal interviews. Once the data were collected, they were entered into a Microsoft Excel spreadsheet and reserved for future reference. Collection of data occurred over several months during the 2009 baseball season.

#### Data Analyses

Descriptive statistics, specifically means and standard deviations, were initially reviewed and reported for the Leagues, regions, and individual teams. The data obtained for the purpose of determining the research hypotheses were analyzed using MANOVA statistical methods. The independent variables were regions within the Texas League (Texas and Non-Texas regions) and Pacific Coast League (West, South, and Central regions). The dependent variables were the ticket pricing (highest ticket price, lowest ticket price, and ticketing fee), concession pricing (draft beer and hot dogs), and price for a family of four. Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 17.0.

### Results And Discussion

#### Descriptive Statistics

Descriptive statistics were reported on all the dependent variables for the team, region and league. Table 3 provides the means and standard deviations found for highest ticket price, lowest ticket price, and ticketing fees.

Further examination of the ticket pricing established by the respective franchises indicates that the Triple-A teams (i.e. Pacific Coast League) have the greatest price point means. Specifically, the West region is higher than all other regions examined across all three price point values $22.63, $7.56, and $3.66 respectively. Inversely, the Southern region within the same league offers considerably lower price points for the highest ticket ($12.00) and lowest ticket ($5.50). All regions studied included fees into their ticket prices, particularly when utilizing online purchasing websites. Most regions were consistently adding approximately $2.00 to the overall price of the ticket.

Figures 1 and 2 show graphical comparisons between the highest and lowest ticket prices for the Texas League teams and Pacific Coast League teams respectively. As shown in both the Texas League and the Pacific Coast League price comparisons, there is great variability among teams when comparing the highest ticket prices; however within both leagues all the franchises have a relatively similar low cost for tickets.

The aforementioned price points did not include additional fees traditionally included in ticket prices for sporting events. As an example of how prices fluctuate with fees included in the price, Figures 3 and 4 show the price increase for the highest ticket price per franchise within both the Texas League and Pacific Coast League. Previously noted within Table 3, the West region of the Pacific Coast League had the highest ticket prices and once again that is reflected in Figure 4 as the fees are also the greatest among several West coast baseball franchises.

#### MANOVA Hypotheses Testing

The three hypotheses were tested by applying MANOVA to the data with SPSS software. The first group analyzed was the Texas League regions (Texas and Non-Texas) as the independent variable and the ticket prices (highest, lowest, and fees) as the dependent variables. As indicated in Table 4, there were no significant F (1,6) = .09, p = .77 differences for the highest ticket prices, F (1,6) = .09, p = .78, and the lowest ticket prices, F (1,6) = .07, p = .80, or the ticketing fees between Texas teams and Non-Texas teams within the Double-A Affiliate Texas League baseball.

As shown in Table 5, the same statistical principles were applied to the Pacific Coast League. The three regions, West, South, and Central, were the independent variables and the ticket prices (highest, lowest, and fees) were the dependent variables. There was a significant F (2,13) = 8.08, p = .00 difference in lowest ticket price between Pacific Coast League when divided by region. A Scheffe post hoc analysis revealed that the South region was significantly different from both the West (p = .00) and the Central (p = .04) regions. The South region had the lowest of the low ticket prices with an average of $5.50 as compared to the West which was $7.56 and the Central at $7.25.

Table 6 shows the difference between the Double-A Texas League and the Triple-A Pacific Coast League ANOVA source table. As noted in the Table, there were no significant F (1,22) = 1.91, p = .18 differences for the highest ticket prices, F (1,22) = 4.11, p = .06, the lowest ticket prices, and F (1,22) = .66, p = .42, or the ticketing fees.

### Conclusions

As more sport franchises compete in this challenging economic market, the need to maintain a positive public image is imperative. Baseball ticket pricing has increased substantially (1) and complex ticket prices could potentially confuse the consumer (7). As a means of determining the best fit in the sport consumer marketplace and how pricing strategies align with peer teams, leagues are examining ticketing price points. This is a simple marketing approach in line with sport marketing professionals (6). Since the advent of the internet price comparison shopping, consumers are able to make buying decisions with a simple click of a button (3, 8). With that said, sport franchises are more conscious than ever of how their ticket prices compare to their competitors’. This research determined, through mainly website analysis, that most of the ticket prices within Double-A and Triple-A baseball affiliate leagues were similar to competition franchises located within their regions. The only exception was found in the Triple-A Pacific Coast League where the South region had substantially lower low-end ticket prices (more similar to that of the Double-A Texas League). As the consumer becomes savvier with online price comparisons, and as economic discretionary spending continues to decline (9), knowing where a team fits within the market offers a greater promotional advantage. Future research may consider examining the impact of how price comparisons can improve sport franchise marketing potential (e.g. illustrating the “value” of minor league entertainment) and measure spectator attitudes toward region price comparisons.

### Applications In Sport

As the present economy is depressed and the future market is unpredictable, discretionary spending on sport entertainment may continue to decline. As such, sport managers within the minor league structure are determining the best approach to continue financial feasibility. This study revealed a common price point for minor league baseball organizations with similar attributes. Most importantly, however, this study revealed that the lowest ticket price in most minor league venues is still relatively affordable. This offers a unique marketing perspective for the increased demand for discretionary spending and sport management organizations should capitalize on this marketing opportunity.

### Acknowledgments

The authors would like to thank graduate research assistant, Lindsey Eidner, and undergraduate research assistant, Nick Garcia, for their invaluable contributions to data collection and analyses of this research endeavor.

### Tables

#### Table 1

Texas League teams organized by region.

Texas League
Double-A Affiliate
Texas Team Non-Texas Team
Corpus Christi Hooks Arkansas Travelers
Frisco Rough Riders Northwest Arkansas Naturals
Midland Rockhounds Springfield Cardinals
San Antonio Missions Tulsa Drillers

#### Table 2

Pacific Coast League teams organized by region.

Pacific Coast League
Triple-A Affiliate
West South Central
Albuquerque Isotopes Nashville Sounds Oklahoma City Redhawks
Fresno Grizzles Memphis Redbirds Colorado Springs Sky Fox
Las Vegas 51’s New Orleans Zephyrs Iowa Cubs
Portland Beavers Round Rock Express Omaha Royals
Salt Lake City Bees
Reno Aces
Sacramento River Cats
Tacoma Rainers

#### Table 3

Descriptive statistics (mean ± standard deviation) for the baseball teams separated by region.

Ticket Prices*
Highest Lowest Fees**
Texas League 13.13 ± 5.40 6.06 ± 0.56 2.13 ± 1.25
  Texas 12.50 ± 4.51 6.13 ± 0.85 2.00 ± 1.08
  Non-Texas 13.75 ± 6.84 6.00 ± 0.00 2.25 ± 1.55
Pacific Coast League 18.13 ± 9.43 6.97 ± 1.19 2.72 ± 1.86
  West 22.63 ± 10.70 7.56 ± 1.05 3.66 ± 2.26
  South 12.00 ± 4.00 5.50 ± 0.58 2.00 ± 0.82
  Central 15.25 ± 6.85 7.25 ± 0.50 1.58 ± 0.15

* Ticket prices are in US dollars
** Fees were team specific, examples included online convenience charges, facility improvement fees, and taxes

#### Table 4

MANOVA source table for the Texas League by region.

Source of Variation df SS MS F
Highest Tickets Between Groups 1 3.13 3.13 0.09
Within Groups 6 201.25 33.54
Total 7 204.38
Lowest Tickets Between Groups 1 0.03 0.03 0.09
Within Groups 6 2.19 0.37
Total 7 2.22
Fees Between Groups 1 0.13 0.13 0.07
Within Groups 6 10.75 1.79
Total 7 10.88

* p < .05

#### Table 5

MANOVA source table for the Pacific Coast League by region.

Source of Variation df SS MS F
Highest Tickets Between Groups 2 345.13 172.56 2.27
Within Groups 13 990.13 76.16
Total 15 1335.25
Lowest Tickets Between Groups 2 11.77 5.88 8.08±
Within Groups 13 9.47 0.73
Total 15 21.23
Fees Between Groups 2 14.33 7.17 2.46
Within Groups 13 37.81 2.91
Total 15 52.14

* p < .05

#### Table 6

MANOVA source table for the Double-A Texas League compared to the Triple-A Pacific Coast League.

Source of Variation df SS MS F
Highest Tickets Between Groups 1 133.33 133.33 1.91
Within Groups 22 1539.63 69.98
Total 23 1672.96
Lowest Tickets Between Groups 1 4.38 4.38 4.11
Within Groups 22 23.45 1.07
Total 23 27.83
Fees Between Groups 1 1.90 1.90 0.66
Within Groups 22 63.02 2.86
Total 23 64.92

* p < .05

### Figures

#### Figure 1

Texas League individual franchise highest and lowest ticket prices.

![figure 1](/files/volume-14/437/figure-1.jpg “figure 1”)

#### Figure 2

Pacific Coast League individual franchise highest and lowest ticket prices.

![figure 2](/files/volume-14/437/figure-1.jpg “figure 2”)

#### Figure 3

Texas League highest ticket price with franchise-specific fees included.

![figure 3](/files/volume-14/437/figure-1.jpg “figure 3”)

#### Figure 4

Pacific Coast League highest ticket price with franchise-specific fees included.

![figure 4](/files/volume-14/437/figure-1.jpg “figure 4”)

### References

1. Alexander, D.L. (2001). Major league baseball: Monopoly pricing and profit-maximizing behavior. Jounal of Sports Economics, 2, 341-355.
2. French, C.W. (2002). Jack Treynor’s ‘Toward a theory of market value of risky assets’. Social Science Research Network. Retrieved April 09, 2010, from <http://papers.ssrn.com/so13/papers.cfm>.
3. Henderson, Dan. (2007, December 13). Online or offline, price comparison tools help consumers shop smart. The Free Library. (2007). Retrieved April 09, 2010, from <http://www.thefreelibrary.com/Online or Offline, Price Comparison Tools Help Consumers Shop Smart-a01073766340>.
4. Jallai, T. (2008). Development of fan loyalty questionnaire for a Double-A minor league baseball affiliate (Master thesis, Texas A&M University-Kingsville, 2008).
5. Lake, C. (2006). Shopping comparison engines market worth £120m-£140m in 2005, says E-consultancy. UK & Global News Distribution. Retrieved April 09, 2010, from <http://www.ukprwire.com/Detailed/Computer_Internet_Shopping_Comparison_Engines_market_worth>.
6. Mullin, B.J., Hardy, S., & Sutton, W.A. (2007). Pricing Strategies. In Human Kinetics (3rd), Sport Marketing (pp. 213-230). Champaign, IL: Human Kinetics.
7. Rascher, D.A., McEvoy, C.D., Magel, M.S., & Brown, M.T. (2007). Variable ticket pricing in major league baseball. Journal of Sport Management, 21, 407-437.
8. Simonds, M. (2009, April 29). Online price comparisons: Easing off your shopping experience. Articlesbase. (2009). Retrieved April 09, 2010, from <http://articlesbase.com/shopping-articles/online-price-comparison-easing-off-your-shopping-experience>.
9. U.S. Bureau of Labor Statistics. (2008). The consumer expenditure survey: Thirty years as a continuous survey.

### Corresponding Author

Liette B. Ocker, Ph.D.
Department of Kinesiology
Texas A&M University – Corpus Christi
6300 Ocean Drive, Unit 5820
Corpus Christi, TX 78412-5820
O (361) 825-2670 F (361) 825-3708
<Liette.Ocker@tamucc.edu>