It’s easy to understand why winning teams would draw more fans — a great team features exciting players, entertaining competition, and the expectation of feeling satisfied once the game is over. But are those qualities actually tied to wins and losses? Or can any team with the right combination of potential and promotion draw a large audience, regardless of what happens during the game?
Jessica Gelman, CEO of Kraft Analytics Group and cofounder and cochair of the MIT Sloan Sports Analytics Conference, joins the show to defend the hypothesis: Teams can win at selling tickets without winning on the field.
Ben Shields: In 1962, just five years after the Giants and Dodgers bid farewell to New York and headed to sunny California, the Big Apple was gifted a new major league baseball team — the New York Metropolitans. Ostensibly, the Mets would be the new crosstown and cross-league rivals to those perennial winners, the New York Yankees, just as the Giants and Dodgers had been for decades. The only problem? The Mets couldn’t quite figure out that whole winning thing. Their inaugural season set a modern-day record for futility — 40 wins against 120 losses. As their Hall of Fame manager Casey Stengel said at the time, “Been in this game 100 years, but I see new ways to lose ’em I never knew existed before.” And there wasn’t much light at the end of the tunnel — over the following six seasons, the Mets lost more than 100 games four more times and never finished above ninth place in the 10-team National League.
Paul Michelman: But, while the losses kept piling up, a funny thing was happening for the Mets — the fans kept buying tickets. In fact, the Mets quickly became one of the top draws in the majors, filling seats throughout the ’60s with folks apparently content to cheer on a loser. During the ’64 season, the Mets lost 109 games yet still outdrew the St. Louis Cardinals, who would go on to win the National League pennant, and more remarkably, their dynastic fellow New Yorkers, the AL champion Yankees. The Queens faithful were finally rewarded in 1969, when the Miracle Mets stormed to their first championship. But by then it was clear: Win or lose, New York’s second team could put fans in the stands. I’m Paul Michelman.
Ben Shields: I’m Ben Shields. And you’re listening to Counterpoints, the sports analytics podcast from MIT Sloan Management Review. In this episode: Were the Mets a box office miracle? Or is attendance a lot less connected to winning than we might think?
Ben Shields: In Counterpoints, we look beyond the data in search of what the data reveals…
Paul Michelman: (interjecting): Or supposedly reveals.
Ben Shields: ...about what’s actually happening both on the field and off.
Paul Michelman: In each episode, we put one analytics-based hypothesis to the test and see how well it stands up.
Ben Shields: Today’s hypothesis: Teams can win at selling tickets without winning on the field.
Paul Michelman: It’s easy to understand why winning teams would draw more fans — a great team features exciting players, entertaining competition, and the expectation of feeling satisfied once the game is over. But are those qualities, and especially the idea of a satisfying experience, actually tied to wins and losses? Or can any team with the right combination of potential and promotion draw a large audience, regardless of what happens on the ice, court, and turf?
Ben Shields: Which brings us to Jessica Gelman, the CEO of Kraft Analytics Group, a technology and services company focused on data management, advanced analytics, and strategic consulting in the sports and entertainment space. She’s also the cofounder and cochair of the MIT Sloan Sports Analytics Conference. We invited Jessica to defend the thesis that teams can win at selling tickets without winning on the field.
Ben Shields: Paul and I were just talking about this thesis of “teams can win at selling tickets without winning on the field,” and it’s interesting, you know, when you’re selling Disney World, for instance, every time you go to Disney World, Space Mountain is gonna work the same way, right? Whereas when you are selling sports teams, you can’t really control the performance in the same way. Right? There’s so many different variabilities. So, you have been on the team side for a while now. How do you think about the problem of selling tickets, especially for a product where you can’t really control the performance?
Jessica Gelman: No, it’s a great challenge and question, and I think from my days working with Kraft Sports and Entertainment, and then now with the broader view that we have across multiple leagues and teams and even colleges, it really boils down into a couple of different factors. Obviously, first, there’s just the basics of supply and demand, and that is around what is the demand, which is really what we’re talking about. And that can be so heavily impacted by the price. And pricing is one of the biggest areas [where] organizations or teams can really try and alter expectations for what might be happening. And you see this very commonly even in minor league baseball, where it’s very much experiential. It’s very family-friendly, and you’re going to go and have a very different experience at a minor league baseball game versus a professional game.
So, supply and demand is huge. But what I was kind of referencing there also with minor league baseball is the actual overall experience at the games has been getting magnified meaningfully. I mean, look, I’ve been working in sports for 17 years now, but over the past 17 years, I actually remember several years ago at the Sloan Conference, a conversation between Mark Cuban and Jonathan Kraft where they were talking about Wi-Fi and how it was going to be critical that not only arenas that have, let’s call it 20,000 — [but] stadiums who have anywhere from 65 to 85 or 100,000 — that Wi-Fi was going to be an expectation and that people were going to want to be able to be on their phones having kind of this dual-screen experience that we’re used to today. And that is an expectation, and it’s actually very good now. But there were times where people would just get so frustrated, they couldn’t make a phone call, let alone check what their fantasy scores were. So that experience, along with what is happening on the field, is obviously very important.
One of the big shifts we’ve seen more recently in sports is this enhanced kind of premium experience at games, as well as [in] congregating areas. And I think that is very impactful for millennials, [it’s] a big part of how that part of our demographics likes to engage. And then the last thing, and this is what makes things great about sports, is that you never know what’s going to happen in any given game. There might be great performances, there’s going be an unexpected upset, whatever there might be, people want to be part of that. So the experience of going to a game is very communal. You’re sharing in this experience. You will hear people talk about, “Oh, I was at this game for that.” Now I’m not suggesting that poor performances on the field, or on the court, or in the ice rink aren’t painful, they are. But there are a lot of aspects of going to a game, for sure.
Ben Shields: Right. And you got into so many of these different elements of why fans may buy a ticket for a game. Right? So the price might be right. It’s the great stadium experience. It’s the fact that there’s now premium experiences and this idea of “wow” — being somewhere live with other fans to experience something that you can’t necessarily get at home. Those are all great reasons for fans to attend a game, and what’s interesting about this conversation is that despite all that, we still have to get fans to spend their time and their money, right? To buy a ticket and actually go to the stadium. So when you put your analytics hat on, for instance, and you say, okay, I’m working on the problem of attracting fans to come buy a ticket for a team that may be average or mediocre, right? That may not even have a chance of winning the championship. How do you think about this from an analytic standpoint of say, okay, we know this team’s not going to necessarily be the championship winner for this season, but yet we still got to put people in the stands? How do you approach that problem from an analytic standpoint?
Jessica Gelman: Well, it’s interesting because [of] what we were talking a little bit about — teams that are performing not very well, or they don’t have a great product on the field. But one of the more interesting kind of analytic findings is that one of the drivers of attendance is how people are performing or how teams are performing compared to the expectations that are upon them.
Ben Shields: Ah, that’s interesting.
Jessica Gelman: So, most of the kind of applicable expectations that people can see is really what the Vegas odds are, right? So, for example, the Golden State Warriors have been, I mean, they’re basically the basketball dynasty right now. The expectation is that they’re going to be performing at such a high level. The fans, especially the season ticket members who have the ability to see them play for 40-some-odd games a year, their expectations are so much higher now. So, from an analytic perspective, it is of course the quality of the game, but also the expectations that the fans have for the performance that they’re going to see. So, I think that’s a really big way from a data analytics perspective. Managing expectations is critical. And kind of beating expectations, of course. Another big way that we have been helping organizations think about data analytics to solve this problem is trying to forecast expected attendance. And this can be based on a large variety of different factors, but you see it obviously with dynamic ticket pricing; there’s a big, significant version of this that is happening in the kind of open ticket market today.
Of course as the average fan or even as a team, you might not have direct access to all of that data. That’s certainly changing with some of the efforts that Ticketmaster has taken this past year, working with the NFL and the open district distribution platform. So, there’s a lot more data that’s going to be available. But it’s everything from the time of the game, to the day of the game of the week, the get-in price of getting into the venue, the weather that’s expected, that kind of competitiveness of the game. The caliber of the players — so this is actually one of the more interesting, detailed analytic findings that we’ve had. If you have one of the top-selling jerseys of a player who’s coming into town across the league, that’s actually a pretty heavy predictor of interest in demand. I mean, it’s not rocket science, but it’s important. There’s data that’s out there that can be used to help inform a bunch of the expectations.
And then the last thing I guess I would say, that I think is really important from an analytics perspective, [is] we talk a lot about the operational data, the inventory — that’s ticketing and pricing and expected attendances. But really, it’s knowing the customer — this concept of serving your customers after games and understanding what their experiences are and just consistently testing new experiential things at the game. We’re seeing changes every single year by all of the leagues. Major League Baseball right now is very hot and heavy on the length of the game and trying to address that. I mean the NFL has obviously had that this year too, with the overtime being reduced from 15 minutes to 10 minutes. So, lots of talking to customers, hearing what their experiences are, what are the pain points that they have, and then actually taking action to fix those. So, getting all of those trends and [that] information together to make decisions about what is going to be most impactful and what needs to be addressed first is obviously a very important form of analytics as well.
Ben Shields: These are all very important points as we think about solving this problem. And you know, I hadn’t even thought about this notion of gathering data about fan expectations. I think that’s fascinating, and the fact that you’re able to pull together some interesting data around forecasting, expected attendance, and of course knowing the customer. These are all really critical new additions to the decision-making tool set. When you think back at your work at the Kraft Analytics Group right now at KAGR, is there a specific example that you are particularly proud of where you have helped one of your clients to use a more analytical approach to increase ticket sales for a variable product, like a sports team?
Jessica Gelman: One of the more interesting ones is actually Mississippi State. That’s one of our college clients. Dak Prescott played there. After he graduated — they’d had a huge surge, increase in their tickets, during his time at Mississippi State, and he’s obviously now the starting quarterback for the Cowboys — but there wasn’t a lot of deep analysis into how they were doing the pricing and where they had adjusted their pricing.
So, one of the big efforts that we did was kind of twofold. One, we created a data visualization that’s enabled them to very easily see a map of their stadium and where attendance was high, where it was low, by games where they had people who are high donors and where they were sitting in the venue. So they could see where maybe some people were maybe in the wrong location. But the key thing is that they had this information, but it wasn’t brought up to them or displayed to them in a way that was easy to consume and digest, nor was it easy to consume and digest for the more senior folks within the organization. And what they ended up doing once they had this information that we worked with them on putting together, through the KAGR platform that they leverage, is they actually ended up changing ticket prices in 80% of the stadium. There was almost an equal number of tickets that they increased as well as decreased. So that’s a very smart, that’s not always about this — they’re trying to find where the most value is, based on where the seats are and adding amenities for some of the better seats. And that impact is that the renewal increased significantly. And they also generated, I think, at least a million dollars in incremental revenues as a result of that, because they better priced their tickets and the experiences for the people who are consuming them.
So, you know, having the students in the right location, having the donors, the longstanding donors who had been season ticket members for a long time, putting them into the better seats, concepts like that. Again, making data easy to consume and to see kind of where there might be trends that might be hard to see if you don’t have that visually laid out in the right way.
Ben Shields: Yeah, that’s a great example and underscores what you were saying earlier about knowing the customer. There’s some real gains there if you better understand who’s actually in your stadium. Now, Jessica, we wouldn’t call this Counterpoints if we didn’t play a little devil’s advocate. So, I’m going to hit you with a few devil’s advocate type questions because you know, there is that conventional wisdom in sports which is to say, well, the main thing in selling tickets is you got to have a winning team. So, let me just throw a few Counterpoints to you here and kinda get your take on them. So, the first is — is this true by sport? Can you really win at selling tickets without winning on the field in all sports? You know, maybe the NFL is different from Major League Baseball because there’s scarcity in the NFL with 16 games versus Major League Baseball has so much more inventory. So, does this approach vary by sport?
Jessica Gelman: I mean, I don’t think it does, personally. What you will see [is] games vary. Your Sunday 1 o’clock game in baseball for example, versus a Saturday 7 p.m. game. That Sunday 1 o’clock might be more appealing for families. So, you might have a different type of promotion — a bobblehead or take your kids on the field kind of pregame. What you’ll see is there’s this customization of the experience to really reach different fan bases. That’s not to say that, for example, a Red Sox/Yankees game isn’t going to be in very high demand and those tickets are going to sell at a higher price. But again, if you are managing whatever the performance might be, and really all organizations and all teams have down years, there are a lot of challenges that many organizations are dealing with in respect to that.
So, this overall experience is a big part of it. And really, pricing plays into it significantly. I would say it’s less the tickets selling than the attendance at the game, which is the bigger concern that organizations are dealing with. Because what organizations do or what teams do is that they have a certain number of tickets that they’re trying to sell as season tickets, to basically minimize the risk. The season ticket members are paying an up-front fee versus the individual games that are being sold — they’re more dynamic or variably priced. So, you might have season ticket members who may choose not to attend that Sunday 1 o’clock game. And then if they’re trying to sell their tickets, or they have friends who they share their tickets with, they might be expecting too much for them, or they might not be able to get quote “the face value” of that ticket, but again they have other tickets that are maybe higher-premium games that are still the same as that Sunday 1 o’clock game in terms of what they paid. If you’re a season ticket member and you have the tickets that you’re selling for a game that might be less desirable, your expectation might be to get that ticket, get whatever the quote “average price” of the tickets that you bought for the season. So, if you have 10 games and you paid $1,000 for them, each ticket in your mind is $100, and a game that’s on New Year’s Eve at 8 o’clock is maybe less valuable than a fall 1 o’clock game.
Ben Shields: Yes, it gets back to this notion of, you know, that not every game is equal, and it could be more valuable to certain fans than when it was originally sold as part of the overall season ticket package. All right, now here’s one for the Chicago Cubs fans out there. Is there any merit in trying to develop a lovable losers strategy? You know, you think about, hey, if you can build a decent business without necessarily relying on winning, I mean, should we just be focused on lovable losers as a strategy? Is there any merit in that, Jessica?
Jessica Gelman: I think there is. It’s actually an interesting discussion, and I think it’s something that’s very prevalent in the NBA in particular. I mean this is obviously an issue that the league has been working on, but there’s this ranking. So, you’re either good and winning and not getting a high draft pick, or you’re bad and getting a very high draft pick. And if you are kind of in this middle no-man’s-land, you’re just going to be an average team. So, there are teams that are fine having that experience, potentially, and then they get lucky with a late-round draft pick or something like that. Look, we see it across all of business where this concept of discounted shopping has worked very well. I think that people, kind of the initial comment that I made at the outset about the expectations for that team, that’s really the driver of the fandom. And if you have a team that’s consistently, you know, winning 70% of their games, that’s pretty good. But if it’s a team that’s consistently losing, like the LA Clippers are kind of known as a lovable loser. I don’t actually know if you can use the Cubs anymore since they won the World Series.
Ben Shields: Fair point.
Jessica Gelman: But I think there is merit in that. You know, it’s a real challenge for fandom. I mean the Cleveland Browns, they’re starting to show some life this year, and that was a very rich and loyal fan base. And you’re starting to see that support come back to that team, and you’re seeing it, by the way, in jersey sales. That’s one of the ways that you see the fandom really starting to resonate.
Ben Shields: Well, one of the big takeaways for this conversation for me is less about measuring winning, so to speak, in terms of wins and losses, but more about measuring the expectations of the fan base. I mean, I think that’s such a fascinating approach to this problem. You know, anytime we do this podcast we want to take a look at some future research questions. So, if you were to think about the data that you would need to more effectively develop solutions to help teams win at selling tickets regardless of their record or fan expectations, what kind of data do you think is necessary and how would you go about capturing it?
Jessica Gelman: Well, the most important thing in the way that I’ve grown up within the business is around really understanding the customer and how they’re engaging with the product or the business. And so we haven’t solved on knowing everyone and what they’re watching behaviors are, but direct to consumer, which is clearly a huge driver of what’s happening with Amazon Prime and the Thursday night broadcast. Facebook just did a big deal maybe with the Premier League? But that’s going to enable teams and leagues to get a much better understanding of not only what people are watching, but how long they’re watching, maybe if they are rewinding; how else they might be engaging with stats. That is something very interesting. I would say, personally, I’m a multiscreen watcher, so I definitely am watching on a TV and also on my phone looking at the stats. And so I think even being able to connect those would be very significant — the web activity that’s going on while you’re engaging in watching.
Things like the favorite player, I mean you can make assumptions based on jersey sales, but you know, one of the challenges is that there are so few player jerseys that are actually made. You might have to customize them today, and only some get the publicity. So, I think knowing favorite players, in more than just what jerseys were purchased, would be very helpful.
The last thing I guess I would say would be, well no, there’s two more things. But family history — the connection to the team: I think [about] people who have grown up with the experiences of watching sports with their families and stuff like that. I grew up outside of Chicago, and I didn’t have the chance to go to a lot of sporting events when I was a kid, but I remember seeing the Bears during the Super Bowl shuffle year in 1985/86. I remember going to a Bulls game, you know in the late ’80s, and I only went to one of each of those, but they were very memorable experiences for me with my family. And I think that family connection is really meaningful and significant. But the last thing that I would say is, from a technology perspective, is [that] really understanding the customer’s pain point when they’re coming to the game — that is something that I think will be very challenging. Was it the parking experience? Was it the gate experience? Was it the food or the quality of the food? Whatever the experience was, what was the biggest thing where they were challenged, where the organization can be better.
Paul Michelman: All right, Ben, what’s your verdict? Are you buying what Jessica’s selling?
Ben Shields: The short answer is yes, Paul. I buy it. The methodology works. We heard a number of different examples from Jessica, and we can point to many other examples throughout the industry. I do want to make a couple other additional points here to add into our discussion. Number one is, there is a growing body of research about what makes a fan a fan. And those elements include family connections, if your parents were a fan of a certain team, you might become a fan of a certain team — through thick and thin. Place connections, the connection to your hometown or where you live. Even a vicarious experience connection. The fact that you want to be the player that you’re watching from the stands. So there’s a whole literature around what makes a fan a fan, and that suggests in the fan psychology that it’s not just about the performance of the team, but there are other psychological factors that drive fandom.
Second key point that I wanted to add into this discussion here is that the industry has almost redefined the notion of winning. You know, in the early days of the NFL, the early days of the NBA, the early days of Major League Baseball, only a few teams even had a chance at winning the championship every year. The playoffs were a little bit smaller in terms of teams that were allowed to make the playoffs. Now, part of that is because the leagues were a little bit smaller, but over time as the leagues have grown, they’ve also let more teams into the playoffs. So the NBA has 30 teams, Paul. Sixteen of those teams make the playoffs. And that gives each one of those teams a little bit more material to use to sell to their fans that say, hmm, we’re making progress, we’ve got a competitive product on the field or on the court, come buy a ticket to see us play.
Paul Michelman: So, what I found most persuasive in Jessica’s argument was this idea of performance relative to expectations being one of the key drivers in sales. Right? And if you think about it, that’s not unique to ticket sales. The way we view life is always relative to our expectations. And our level of satisfaction or happiness is often determined by an outcome versus what we expected it to be. So, if you’re talking about a team that is a perennial loser, a modest increase in performance could have a meaningful effect on ticket sales, or perhaps you’ve just redefined what a satisfying experience even is. Going to a Cubs game, when I was a college student in Chicago, was never about winning. It was all about the party at the game, right? And the Cubs never had a problem selling tickets, as you discussed during the interview with Jessica.
And I think that that also seems to be in play with the story about the Mets, which opened the program. Fans were happy to have a team back in New York. They were happy to be out there in the stands, and they didn’t need winning to give them satisfaction. That said, I’m not quite as all in as you are. I want to see more examples across more sports and in particular across more geographies. I completely buy in that teams can put fans in the stands without winning, but how pervasive is that? Under what circumstances might that be too great a challenge to overcome? Sometimes you almost have to prove a negative to prove the positive. So I’m a believer, but I’m not 100% a believer. To wildly misquote Stephen Colbert, “I’m believer-ish.”
Ben Shields: This has been Counterpoints, the sports analytics podcast from MIT Sloan Management Review.
Paul Michelman: You can find us on iTunes, Google Play, and wherever fine podcasts are streamed. And please take a moment to post a review. We really want to hear your feedback.
Ben Shields: We’ll be posting new episodes every two weeks.
Paul Michelman: Counterpoints is produced by Mary Dooe. Our theme music was composed by Matt Reed. Our coordinating producer is Mackenzie Wise. Our crack researcher is Jake Menashi.