Ticket Masters: Researchers Want Analytics to Move From the Field to the Box Office

As stadiums and arenas reopen, struggling teams are losing revenue by not introducing data-driven pricing for ticket sales.

Advanced stats like WAR and WOWY have changed how coaches and managers evaluate the talent on their teams. 

Now, a researcher at the University of Colorado Boulder’s Leeds School of Business wants the owners of those teams to use the same mathematical perspective and sophistication to think about the value of the seats in their stadiums. 

“There’s all this hype in sports about analytics and data-driven pricing, but what these teams are doing is just not sophisticated enough,” said Övünç Yilmaz, an assistant professor of operations at Leeds. 

Using data from a major Division I college football team, Yilmaz and his co-authors determined that, through price optimization techniques and re-imagined seat and game categories, a team could increase gate revenue by 11.9 percent. The resulting paper was one of three finalists in the biennial Production and Operations Management Society’s Applied Research Challenge.

Seeing sunlight and scores

How does it work? Say the Buffaloes are kicking off against a conference opponent for a mid-October matinée. Most college football tickets are sold well in advance, so in addition to things like distance from the field, Yilmaz’s model considers things like how long a section will be baked in direct sunlight, how easy it is to see the video board from your seat and how popular a draw the opponent will be. 

“Now, let’s consider a night game in November—it’s cold, it’s dark, maybe the opponent isn’t very good,” he said. “That needs to be part of your consideration when you’re pricing your single-game tickets. And, can you see the video board? That’s important to customers.” 

Variable pricing is easier for things like seats on a plane or rooms in a hotel—the best seats and rooms are easy to identify. Fan preference in a stadium isn’t so cut and dried.

“For a single game, as a desirable section gets fuller, you see customers choosing less-expensive sections as opposed to, say, a corner seat with poor sightlines in a good section,” Yilmaz said. “To really optimize pricing, you would set individual seat prices, as opposed to sections and rows. In fact, we already see this playing out on the resale market.” 

Forbes has estimated that ticket reselling for sports, concerts and shows is a $15.2 billion market—money that doesn’t go to the teams or performers. Teams and athletics departments that optimize their prices would do a better job of capturing some of this revenue themselves. 

It would also be a better experience for fans, who are the ones squeezed out by scalpers for in-demand events. 

“Our research showed that some of the seat categories for the less-desirable games are overpriced,” Yilmaz said. “The goal should be to bring more people in by lowering the bar for entry, as opposed to charging higher prices and selling fewer seats. Data-driven optimization might help the team keep the revenue for those seats, as opposed to value disappearing on the secondary market.” 

COVID-driven challenges

The researchers’ insights on the varied decision-making processes of customers amid changing seat inventory adds to the literature of operations management, and it does so in a way that excited Yilmaz, a big sports fan, to see the project through. 

“There’s more interest right now in event revenue management, because of COVID,” he said. “Even in our work, when we were gathering data, we had no idea a pandemic was around the corner. But it makes this work even more interesting now.” 

That’s because, for pro and college teams, the inability to fill stadiums during lockdown created an economic crunch that may leave them open to rethinking how they price their seats. 

“In normal times, it’s hard to get teams to think about changing their pricing strategies,” Yilmaz said. “With how much these teams suffered during the pandemic, it’s a good time for teams to revisit those strategies.” 

In fact, in one of the most rewarding developments for Yilmaz, the college team that supplied its data to the researchers is figuring out how to deploy them at the box office. 

“Our hope is that the school will fully implement these ideas—and because the football team is so successful, maybe athletics departments elsewhere will start to adopt them, too,” he said. “It’s very validating to see this work get consideration in the real world.”

This research was published in August in Manufacturing & Service Operations Management. Yilmaz’s co-authors included Hayri Arslan, of the University of Texas at San Antonio; Rob Easley, of the University of Notre Dame; and Ruxian Wang, of Johns Hopkins University.

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