Journal of Issues in Intercollegiate Athletics Journal of Issues in Intercollegiate Athletics

Volume 14 Article 8

2021

An Examination of Secondary Ticket Market Pricing Trends and An Examination of Secondary Ticket Market Pricing Trends and

Determinants at the NCAA Football Bowl Subdivision Level Determinants at the NCAA Football Bowl Subdivision Level

Stephen L. Shapiro

University of South Carolina

Austin Schulte

University of North Carolina – Chapel Hill

Shapiro, Stephen L.; Schulte, Austin; Popp, Nels; and Bates, Brad (2021) "An Examination of Secondary

Ticket Market Pricing Trends and Determinants at the NCAA Football Bowl Subdivision Level,"

Journal of

Issues in Intercollegiate Athletics

: Vol. 14, Article 8.

Available at: https://scholarcommons.sc.edu/jiia/vol14/iss1/8

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© 2021 College Sport Research Institute

Several factors influence the price college athletics administrators set for football tickets, but

nearly all pricing decisions are established prior to the season commencing. The secondary

ticket market allows college athletics administrators to observe real-time consumer valuation for

tickets. The purpose of the current study was two-fold: (a) to examine how secondary ticket

market prices fluctuate at different time periods leading up to game day and (b) to examine the

relationship between several key demand variables and “Get In” price (GIP) during those

the variance in GIP at each point in time. As game day grew closer, overall GIP diminished in a

linear fashion at each data collection. Several explanatory variables were significant in each

model and are interpreted in the discussion.

Secondary Ticket Market Pricing

icket sales have long been a major source of revenue for collegiate athletics

departments. College football, in particular, generates significant revenue from ticket sales. The

top 25 college football programs generated annual revenues of over $2.7 Billion in 2018, and

27% ($729 million) of that revenue is a result of football ticket sales (Smith, 2019). Berkowitz

(2020) suggested the total football ticket revenue for all of Power 5 schools exceeded $1 billion

in 2019, while sport economist Patrick Rishe estimated Power 5 schools would have generated

an average of $18.6 million in football ticket sales in 2020 had the coronavirus pandemic not

struck (Schlabach & Lavigne, 2020). According to the NCAA Finances of Intercollegiate

Athletics Database, 17.5% of all revenue (generated and institutional support in FY 2019) came

approaches to create additional revenue (Shapiro & Drayer, 2012). From a college football

perspective, it has never been more important for athletic departments to accurately price their

catalog of events to produce revenue.

Traditionally, the predominant method for establishing ticket prices to live sporting

events has been to raise prices incrementally over time by some arbitrary percentage or flat rate

(Howard & Crompton, 2004). However, more recent scholarship has highlighted the positive

impact of demand based pricing, including variable ticket pricing (Rascher, McEvoy, Nagel, &

Brown, 2007), dynamic ticket pricing (Shapiro & Drayer, 2012, 2014), and other forms of

discriminant pricing (Courty, 2003) that have been used in professional sport. These pricing

strategies are largely in response to the secondary ticket market, which highlights inefficiencies

& Drayer, 2015; Diehl, Drayer, & Maxcy, 2016; Shapiro & Drayer, 2014). The majority of the

strategic pricing research has been conducted within the context of professional sport. Our

understanding of ticket pricing within the realm of college sport, and the inefficiencies in a dual-

market environment such as college football, is limited.

Although some athletic departments are using demand-based pricing strategies for

college football, these strategies are not consistent across all programs, further highlighting the

need to investigate ticket prices across markets. College sport, and football in particular, presents

some unique challenges with regards to ticket pricing. These challenges include the vast number

of teams, competing in various divisions and conferences, each with differing policies and

guidelines. Additionally, the revenue disparity is dramatic. In 2017-2018, there was a disparity of

Shapiro, Schulte, Popp & Bates

& McManus, 2019). Finally, stadium capacity and demand for football tickets varies

considerably with the largest college football stadiums seating over 100,000 fans and regularly

selling out, while other programs have stadiums that hold fewer than 15,000 fans with no

sellouts.

A handful of studies have either examined managerial theory associated with pricing

strategy or secondary price markups in postseason play within college athletics (Morehead,

Shapiro, Madden, Reams, & McEvoy, 2017; Rishe, Mondello, & Boyle, 2014; Rishe, Reese, &

Boyle, 2015; Rishe, Sanders, Reese, & Mondello, 2016). Price disparities in the primary and

environment.

The following research questions were developed to guide this investigation:

RQ 1: How does resale “get-in” ticket price change over time periods from the

Associated Press Poll release to the day before the game?

RQ 2: What variables predict Power 5 resale “get-in” price at various time periods

leading up to game day?

Secondary Ticket Market Pricing

Revenue management (Kimes, 1989), allows for price discrimination in real-time. In

industries where demand fluctuates daily and the product is perishable, revenue management

provides the opportunity to adjust prices based on instant changes in demand (Kimes 1989;

Shapiro, Schulte, Popp & Bates

year’s price increase, impacted seasonal changes in average ticket prices. Rishe and Mondello

(2004) conducted a subsequent examination across the four major sports leagues in the U.S. The

findings were generally consistent with previous literature, as price was influenced past prices

and team performance, along with playing in a new facility and fan income. Additionally, by

extending this work beyond the NFL, the authors found population size played a role in all other

major professional sport leagues.

These seminal ticket price determinant studies were conducted prior to the wide

implementation of demand-based pricing strategies, such as VTP and DTP. Subsequently,

nature of demand and is the most accurate representation of consumers’ willingness to pay for a

particular event. The prices can change drastically for a variety of reasons such as team success,

injuries, opponent success, weather, and coaching changes, amongst other factors.

Drayer and Shapiro (2009) provided an early assessment of factors affecting ticket resale

prices, which include factors that change over time and provide a better reflection of consumer

ticket value. Their study on NFL playoff ticket prices highlighted some factors consistent with

previous research in the primary market, including team performance, population, and income.

However, new variables not considered in primary market models were also found to be

significant, including total number of transactions, time, day of the game, playoff round, and face

Secondary Ticket Market Pricing

foundational studies providing direction within this context. Patrick Rishe and colleagues

conducted multiple studies examining resale markups for postseason Division I college football

and basketball games. Rishe (2014) examined NCAA Final Four tickets on the secondary market

and found tickets were priced in the inelastic portion of the demand curve. Additionally, specific

sessions (i.e., Semifinals instead of an all session pass) had significantly higher markups and seat

et al., (2016) expanded the college football postseason investigation by examining 55 different

bowl games. They found consistent results regarding seat quality and university proximity to

bowl game site, but interestingly not all bowl games were priced in the inelastic range of

demand. This is most likely due to the large number of bowl games with a wide range of

competitiveness and quality of opponents. In another study examining factors affecting what

ticket buyers were willing to spend on the secondary market for tickets to attend a major college

basketball tournament (Popp et al., 2018), the time in advance of when tickets were purchased

and the number of regular season games attended both had a negative relationship with the

amount paid per ticket, while age and income level of the ticket buyer, as well as seat location

Shapiro, Schulte, Popp & Bates

promotions or deals. Universities sell single game tickets to the public, typically throughout the

summer before the season, once they have exhausted season-ticket sales. Single game tickets can

also become available (and sold) when an unsold portion of tickets allotted to the visiting team

are returned. This typically occurs close to game day.

The secondary market price consisted of the StubHub “get-in” price (GIP) for each

individual game, which was the lowest priced ticket on the resale platform at the time of data

collection. GIP was collected on StubHub at four different time periods: (a) during the pre-

season Associated Press (AP) Poll release, (b) two weeks prior to game day, (c) one week prior

Time/environmental variables included: (a) time-related variables (i.e., month, day, and time of

game), (b) proximity of opponent, and (c) weather-related variables (temperature and

precipitation). Game-related factors included (a) whether the game was nationally televised, (b)

conference affiliation for both teams, (c) whether the game was a conference or division

matchup, and (d) betting related factors (betting line and total points). Performance factors

included (a) current and previous year winning percentage for both teams in a matchup, (b) poll

rankings for each team at the time of ticket price observation (using the Massey Rating

Composite Ranking), (c) whether either team in a given matchup went to a bowl game in the

previous year, and (d) recruiting rankings for each team in a matchup. Finally, home market

Secondary Ticket Market Pricing

Shapiro, Schulte, Popp & Bates

resale prices at this time period. Nine factors were found to be significant in this model. All nine

of these variables were significant at one point or another in previous models. The final model

includes ticket price and proximity, which have been relatively consistent throughout the

regression models, both home and away performance variables, month, whether the game was

nationally televised, venue capacity, and weather (see Table 5). Resale GIP dropped by $12.32

for every ten-percentage increase in precipitation chance, much more in line with expectations

that college football fans would pay less to watch games in unfavorable conditions. Also, for

every dollar increase in primary market price, resale GIP only increases by $.50, which is the

season commencing, with only a handful delaying the release of late-season single game ticket

prices until weeks before the actual game is played. Tracking GIP pricing on the secondary ticket

market enables researchers and administrators to evaluate secondary market ticket pricing trends

and determine what factors may influence market price fluctuations over time.

(Drayer & Shapiro, 2009; Shapiro & Drayer, 2012, 2014), the NHL (Dwyer, Drayer, & Shapiro,

Secondary Ticket Market Pricing

ticket inventory available on the secondary market may have benefits. Theoretically, a wider

variety of fans may find ticket prices to be attractive on the secondary market, but the department

itself is not forced to devalue its own product by trying to match secondary ticket market prices.

However, for administrators wanting to maximize revenue, declining secondary market GIP is

problematic as it conditions ticket buyers to wait as long as possible in order to obtain the

greatest discount on tickets, and to look for those discounts solely on the secondary market. As a

result, departments may need to combat the availability of more affordable tickets on the

secondary market by tactics such as: (a) increasing the value of tickets purchased on the primary

price, a few trends emerged from the regression models. First, as game day drew nearer, the

combination of the variables examined in the models explained less of the variance. Few prior

ticket pricing studies have examined the impact of so many traditional demand variables on

dynamic ticket price at multiple times leading up to a game. It was expected the further out from

kickoff--and thus the greater uncertainty regarding team performance and weather conditions--

the more difficult it would be to determine which factors would impact price variability. In

actuality, the opposite was true. Each subsequent model in the study explained less of the

variance in GIP, indicating unaccounted for explanatory variables (such as number of tickets

available or intrinsic motivations) may be more influential on secondary market ticket price,

Shapiro, Schulte, Popp & Bates

different picture. The higher the predicted likelihood of precipitation for a game a week before it

was played resulted in higher GIP. A day before the game, however, a more logical relationship

was revealed, as higher likelihood of precipitation had a negative relationship with GIP, a result

similar to those found in prior college football attendance studies (Falls & Natke, 2016; Price &

Sen, 2003). Perhaps when season ticket holders who frequently attend games look at the

extended forecast, they are more likely to make a decision to sell their tickets for that game, but

believe other buyers will be willing to pay premium prices. As game day draws nearer and

precipitation is still likely, perhaps ticket sellers realize it will be challenging to sell their tickets

as a game draws near. This findings is consistent with Shapiro and Drayer (2012), who suggest

fixed primary market prices create arbitrage opportunities through pricing inefficiencies. Resale

ticket prices have the ability to fluctuate based on game, time, market, and environmental related

factors highlighted in this study, where primary market prices are static.

Interestingly, the results from the current study showed primary market prices were

higher than resale GIP at all time periods, which is contrary to what Shapiro and Drayer (2012)

found in Major League Baseball. This contradiction was not surprising, as Morehead et al.

(2017), suggested multiple factors make college sport ticket pricing different from professional

sport, including a wider array of stakeholders, organizational structure differences, and cultural

Secondary Ticket Market Pricing

observation of longitudinal trends and could enable researchers to utilize the current regression

models to predict the overpricing or underpricing of future game tickets. The data can also be

used to supplement other research in the college football literature, perhaps not related to ticket

price itself. Overall, the study lays a framework for additional future research into college

football prices on the primary and secondary market while also still capturing significance and

comparison over four distinct time periods.

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