When NBA superstars like Steph Curry, Joel Embiid, or Kawhi Leonard are given a planned night off, the impact of their absence isn’t just felt on the floor — it’s a financial issue as well. Whether it’s fans not getting what they believe they paid for, prices on the secondary ticket markets crumbling, or teams dealing with empty seats and depressed TV viewership, the consequences of a planned absence of a major star reverberate across the sport. But just how much is everyone losing when stars sit out — and which stars are creating the biggest holes in NBA pockets? To get to the bottom of one of the biggest financial questions surrounding the NBA, Paul spoke to Scott Kaplan, who presented his paper detailing the economic impact of NBA Superstars at the 2019 Sloan Sports Analytics Conference.
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Paul Michelman: Hello Counterpoints listeners, we have a favor to ask. If you enjoy our program, would you please take two minutes to rate us and, even better, post a review on Apple Podcasts or wherever you get Counterpoints? It makes a huge difference in our discoverability, and we’d actually like to know what you think. On to the show.
Ben Shields: In today’s NBA, it isn’t uncommon for the biggest names in the game to take a planned night off here and there. In fact, it’s become a core component of player management strategy. To keep your most valuable contributors healthy and fresh across an NBA season that can run up to seven months, scheduled R&R for superstars is an accepted practice. It even has a buzzworthy term — load management. But back in 2012, scheduled rest was not yet in vogue, and when San Antonio coach Gregg Popovich decided to sit his “Big Three” of Tim Duncan, Manu Ginóbili, and Tony Parker for a national TV matchup against the Miami Heat, there was serious outrage — not from other players or coaches — but from commissioner David Stern, who levied a quarter-million-dollar fine on the Spurs.
Paul Michelman: And it wasn’t just the mucky-mucks in the NBA league office who felt that Popovich’s stunt demanded financial consideration. Deprived of what they felt they had paid for — that is, the chance to see two of the league’s powerhouse teams go head-to-head at full strength — fans in Miami did what any group of red-blooded Americans would do in their situation. They sued. A Miami lawyer named Larry McGuinness, who had attended the controversial game, filed a class action lawsuit claiming that he and other fans had suffered economic damages. McGuinness noted that it was like going to a Morton’s steak house, paying $63 for a porterhouse, and they bring out cube steak. Though the suit was later dropped, the message they intended to send remains vital to this day. Resting healthy stars in the NBA has ramifications that reach well beyond keeping them fit for the long season. It has serious impact on fan welfare and ultimately on the business of basketball. I’m Paul Michelman.
Ben Shields: I’m Ben Shields. And this is Counterpoints, the sports analytics podcast from MIT Sloan Management Review. In this episode, we’re asking, to rest or not to rest? — as we look at the economic impact of the biggest stars in the NBA sitting in suits rather than sweating in jerseys.
When players like Steph Curry, Joel Embiid, and Kawhi Leonard fall victim to the malady known as load management, the impact of their absence isn’t just felt on the floor — it’s a financial issue as well.
Paul Michelman: Whether it’s fans like Larry McGuinness not getting what they believe they paid for, or prices on the secondary ticket markets crumbling, or teams dealing with empty seats and depressed TV viewership, the consequences of a planned absence of a major star reverberate across the sport.
Ben Shields: But just how much is everyone losing when stars sit out? And which stars are creating the biggest holes in NBA pockets? To get to the bottom of one of the biggest financial questions surrounding the NBA, Paul spoke to Scott Kaplan who presented his paper on the economic impact of NBA superstars at the 2019 Sloan Sports Analytics Conference.
Paul Michelman: Scott, welcome to the podcast.
Scott Kaplan: Thanks for having me.
Paul Michelman: So you’ve taken on as a research interest what’s a pretty hot topic in the NBA — the resting of superstars and its impact on the game. I guess I’d like to begin by understanding what prompted you to look at this.
Scott Kaplan: I think the initial motivation was exactly what you said: There was this higher tendency of teams to rest their superstar players on purpose at certain intervals during the course of the season. And we really wanted to understand what sort of impact this had on fans who were attending the game — in terms of their welfare, their well-being. How much did this hurt the game? Things like that.
Paul Michelman: What do you mean by welfare when it comes to fans?
Scott Kaplan: So in this case, the way we think about welfare is sort of the dollar amount of losses experienced by fans in the context of players not playing. So we can measure this essentially by looking at changes in prices. And the way prices move can tell us a little bit about how fans sort of value or disvalue players resting or not playing. So the data we looked at was twofold. The first set of data we looked at was a very high temporal frequency data on secondary ticket marketplace prices for each game. And the way we broke that down was looking at every single future game, at every single point in time, and determining the listing price for every single ticket listing. That was the first data set. The second data set was looking at the count and timing of injury announcements or rest announcements for players missing games. So we determined the exact timing with which an announcement occurred about a player missing a future game, why that announcement occurred — whether that’s through injury, rest, suspension, or something else — and then we can map that to our secondary ticket marketplace ticket data to see how ticket prices changed in response to that announcement.
Paul Michelman: So what was the correlation you found?
Scott Kaplan: So what we did is we took a very classic applied econometric approach to looking at this question. And what we found is that for the most popular players, once an announcement occurs that they’re going to miss a game, we see prices on the secondary marketplace drop anywhere between as low as 5% to up to 25%, depending on the game and the player.
Paul Michelman: So that’s a pretty broad range. I’m really interested in what drove it up to 25%.
Scott Kaplan: So there are several factors we think that account for the large range. These are factors like whether it’s a home versus an away game, the market size of the home team, and where the game is played. And even something like the popularity of the player, like something like All-Star votes.
Paul Michelman: Can you pinpoint particular players who have a larger effect on depressing the ticket price?
Scott Kaplan: Yeah, absolutely. So our analysis is at the player level, and what we do is we look at all of each player’s missed games, and we estimate an aggregate effect for each player across all of their missed games. So for example, if Steph Curry missed five games, we would be able to find an average effect of Steph Curry’s absence on ticket prices. But we would be able to break that down into Steph Curry’s absence effects for home Warriors’ games and Steph Curry’s absence effects for away Warriors’ games. And what’s interesting about Steph is you find much, much larger effects for away games than for home games. And we think that is super-intuitive because of Steph’s sort of universal impact on the game, and he only visits away stadiums up to two times a year, and fans pay a lot of money to want to see him play in those two times.
Paul Michelman: And are there other players who follow kind of the same pattern as Steph — LeBron, for instance? Durant?
Scott Kaplan: Yeah, great question. So unfortunately, LeBron didn’t miss any games in the last NBA season, so we weren’t able to analyze him. But we do have the data for this year, and he obviously missed a lot of games, so we’ll be able to take a look and get back to you on that. Another interesting thing, for example, is Anthony Davis and Kristaps Porziņģis. They’re sort of the lone superstars on their teams. And what you find is their home game absence effects outweigh their away game absence effects. And we think that’s because when those players sit out, their team becomes much less competitive, and their fans in their home games are going to respond accordingly. But, for example, on the other hand, when Steph sits out, the Warriors are still extremely competitive — they still have, arguably, three other superstars. And so you really aren’t paying for the experience of seeing Steph in that case, and there’s not really a competitiveness or a huge competitiveness impact in that case.
Paul Michelman: So what you have found — it seems to be particularly important to people who are, say, season ticket holders who are reselling their tickets in the secondary marketplace. Those are the ones who are going to be most materially affected, right, by these changes in demand based on planned superstar absences. Is that the limit of your finding? In other words, how much should we really care what happens to a ticket price on StubHub? I guess I’m asking: Are there echo effects from this that we should be concerned about?
Scott Kaplan: You’re right, and I think season ticket holders are… the most exposed to these events happening, because they own a huge asset, they own all the games, for example, a certain team’s home games — and they can be super affected by injuries or rests by that team. I think what’s really interesting about this estimate is we really consider this a lower bound in the sense that a lot of people may not even respond on the secondary marketplace, but still might experience some sort of economic loss. And you might think that might be because the transaction costs of adjusting their ticket on the secondary marketplace are too high in terms of taking the time to go on there and do that. The fact that we even see effects for some of these players indicates that even from the group of people that is responding, you can see the average effects being substantial and economically meaningful. So that’s really important to know. The other thing, sort of going more directly to your question, is we don’t even look at TV ratings, for example. So TV ratings are going to be also negatively impacted by a superstar not playing. I mean, just speaking as a Lakers fan, I can tell you I haven’t tuned into a single game since they sat LeBron for the rest of the season this year. So I imagine that’s the case for several people, even the more lay NBA fan.
Paul Michelman: So Scott, the data you have so far is really focused on fan welfare, right, on ticket prices. Let’s talk more specifically about why other stakeholders in the league and maybe other leagues should care. So let’s look at this from the team perspective. If the seats are still being filled, and they’re still selling out the games, is the team affected by what’s happening in the secondary marketplace? Why does the team care?
Scott Kaplan: The team is not affected by what happens in the secondary marketplace. But the team might want to consider alternative pricing strategies based on these players not playing. It may not matter for a team who sells out every game like the Warriors, but it could matter for a small-market team that really depends on revenue generated by an away team coming in, for example. The team effects depend a lot on what teams we’re talking about. Now, I think each team definitely cares about TV deals and TV revenues. So, for example, if you’re the 76ers and you’re signing a TV deal, but you know that Joel Embiid is almost guaranteed to miss at least 10 to 15 games a year, that might impact the extent to which you can generate revenue from that deal — that local TV deal.
Paul Michelman: And so if I’m the local TV owner, how do I use this information?
Scott Kaplan: You can use this information twofold. One, is you can have a better idea of the propensity of a certain superstar player to sit out. So this can tell you sort of on average how many games we expect these different players to sit out, which might affect TV ratings for those specific games. And the other thing is, in looking at these price impacts, we can sort of gauge the relative importance of each player. So, for example, if I’m a TV local owner for the 76ers [and] I want to know Joel Embiid’s impact, I can compare sort of the average magnitude of his impact using this price analysis compared to a potentially less-important player, maybe an Al Horford for the Boston Celtics.
Paul Michelman: And are you incorporating that into your negotiations?
Scott Kaplan: I think that’s a step down the line. You know, as we get more confident and more refined in this analysis, that can really inform a lot of these negotiations, because we can really get a better idea of the marginal impact of each of these players. And I guarantee you when you can look at trades, you can look at things like that. And that has huge impacts when big players are traded to different markets, especially for smaller markets when maybe, let’s say, Zion Williamson’s being drafted. That’s going to have a huge impact for the market that takes him in, in terms of their TV revenues. So these types of things, to the extent that we can accurately measure the magnitude of a player’s importance in terms of welfare for fans and for the team’s well-being, we can hopefully incorporate those things into negotiations about both TV deals and into how teams set ticket prices.
Paul Michelman: Yeah, when you think about it downstream a bit. And I realize that you know you don’t have the kind of full set of data that you might want. But you could imagine in TV negotiations a whole new type of performance clause, right, where the amount that the rights holder is paying is based on the appearances of certain key players. That could be negotiated ahead of time. But maybe more realistically, it’s embedded that if Joel Embiid misses more than X games, the rights drop by X percent.
Scott Kaplan: Yeah, that’s a really good point. And I think what’s really cool about this analysis is we really try and get at the exact impact of each of these players. And we are able to do that confidently because at least injury occurrences, and some other absence occurrences like a suspension, are plausibly random. So they’re not confounded necessarily with other impacts that might affect prices. And by getting at an accurate causal impact of a superstar absence, we can do exactly what you said. We can apply it to negotiations, we can apply it to team decision-making, we can apply it to how much we should fine teams for resting players — because we’ve sort of really got at and identified these exact effects.
Paul Michelman: What if teams were to take a longer-term planning approach and announce a schedule for when key players are going to sit? Would that exacerbate the problem? Ameliorate the problem? Not affect it at all?
Scott Kaplan: I think what it does is it reduces the uncertainty involved in purchasing a ticket. So if I’m a consumer and I want to make sure I go to a game where LeBron’s playing, then I might be willing to pay some sort of extra premium to know that he’s going to play that game. Now on the other hand, what that allows is some sort of price discrimination scheme from the team standpoint. There might be consumers who can’t afford to go to a game when Steph Curry and Kevin Durant and Klay Thompson are playing, but they might be able to pay a slightly lower price to go to a game where, for example, Kevin Durant decides to sit down. So I think that by reducing the uncertainty involved in the purchase process and the team sort of knows exactly when to expect players to be out, how that might impact their TV deals, how that might impact how many tickets they’re going to sell — these are all sort of factors that I think both parties would appreciate in terms of invoking certainty into the situation.
Paul Michelman: How about from the player’s perspective — could your research have any effect on player contracts?
Scott Kaplan: I think what’s really nice about this is you might be able to design different sort of incentive structures — similar to what you mentioned about the TV deal. You might be able to design similar incentive structures for players [that would] essentially reward players for their popularity. So because of the way contract structures are set up in the NBA today, there’s sort of a max salary that a player can hit and then there are certain additional incentives in reward to their actual performance, whether it’s all NBA or other awards like Defensive Player of the Year or MVP. But in this case, you might be able to reward a player, for example, for the number of All-Star votes that they generate. And we think that’s a pretty good correlator to how popular a player is and how much they might drive ticket prices. What’s also really interesting, I think, about this analysis and the NBA in particular is there’s so many games in the NBA that each marginal game rarely has a huge effect on a team’s outcome in terms of their place in the standings. So a lot of times for an individual game, if I get to go to one or two games a year, I really want to make sure that I’m going to see the players that I want to see play, because that’s really at that point what’s driving the value of attending that game. So in this case, we think that contract incentives can play a huge part in what we think is rewarding players for their popularity and for branding themselves in a way that fans relate to. Steph Curry is the principal example of a player that I think that fans relate to, that there’s huge demand to go see — probably of his brand, both on and off the court.
Paul Michelman: Scott, you talk about a player being rewarded for his popularity. Could a player’s popularity also become a burden? If Steph Curry is that valuable in terms of attractiveness on the road, might a team kind of load his contract with incentives that really penalize him for not playing?
Scott Kaplan: Oftentimes, at least from my understanding, it’s not the player’s decision to rest and certainly not the player’s decision to sit out due to injury. So I think this actually resonates at a team level, and whether that’s the general manager or the coach making these decisions about when to rest players, when to play players — I think you would have to look much more closely at the specific situation of how the structure of a player playing versus not playing is generated and who’s making those decisions, before you decide how to incentivize them to play or not play.
Paul Michelman: I’m also wondering from the team perspective, and again, let’s stay with Golden State because they’ve got this roster of stars that allows home teams when Golden State is visiting to charge a premium for the tickets — which I experienced going to a Golden State game in Boston this year. I don’t know enough about how the NBA does revenue sharing or if they do [it] at all, but I am assuming that visiting teams don’t participate in the revenue generated by the home team. Could your research actually lead to the league revisiting revenue sharing, particularly for visiting teams that have really attractive stars?
Scott Kaplan: My understanding of revenue sharing in the NBA is it’s a half-half split, and this might’ve been updated in the most recent CBA. But from my understanding, there’s a 50% revenue sharing that sort of is pooled among all teams in the league based on the revenues from the year, and then each team gets to keep sort of the other 50% of the revenues they generate. So I think, for sure, in answering your question, that there’s potential implications for how the league decides to share revenues, whether that’s basically allowing small-market teams to take more advantage of these visiting players when they play, because so many of their other games are not going to generate huge amounts of revenue. But that’s sort of a question that’s beyond the scope, I think, of the research that we generate here in terms of informing decisions or policy at the league level.
Paul Michelman: I’m also wondering, kind of on that same theme, whether or not Golden State ought to be traveling with their own merch booths. You know, I can’t imagine that the Celtics would agree to put Steph jerseys in the store when Golden State’s visiting, but they’re probably missing a huge revenue opportunity.
Scott Kaplan: Right. And you totally see tons of people in the stands wearing Steph jerseys, so they’re getting them from somewhere.
Paul Michelman: Yeah, they do. Scott, let’s talk for a minute about potential implications for other sports. Baseball comes to mind, where planned player absences are quite common, and you imagine managers actually scheduling days off for players sometime in advance. So imagine the Red Sox are visiting a city in interleague play, where they only come once every six years and fans know that Mookie Betts isn’t going to play. What might your research suggest about the implications there?
Scott Kaplan: Yeah, I think on a broad, very high level, we would expect that if this player generates sufficient popularity and has high value for their team, you would expect that their impact would reflect in ticket prices to some extent. Now, we can’t say too much about the magnitude by which that might affect ticket prices. I know baseball ticket prices, on average, are a little bit lower than NBA ticket prices. So I think the dollar value is probably going to be slightly lower. And given that there’s several more games in the MLB season, you might have some more substitutability across games and see that player play. I think what’s really interesting with baseball is how the trade deadline and player movement might affect ticket prices for the remainder of a season. So, for example, if a team is deciding that they’re out of the playoff race, and they have a really good player, and they want to trade that player because they can get value for that player now and some other team can get value for that player in their playoff run, you might actually see ticket prices drop for the remainder of the season in response to that player move. So that’s something that I think baseball franchises would be very interested in considering. And in the case of football where there’s only eight home games, you would very likely to see your response to ticket prices, especially if your star player (which in this case is probably your quarterback) gets injured or decides not to play. In that case, what you might expect is the team’s competitiveness immediately goes down due to that injury or that decision not to play. So that might be reflected much more heavily in ticket prices because of the level of ticket prices in football games, which are much higher than baseball and even potentially higher than basketball, but also because the competitiveness of the team and their playoff chances goes down drastically.
Paul Michelman: Scott, so to wrap up, let’s loop back to your original thesis about the impact of superstar absences on fan welfare. How do we think about mitigating that?
Scott Kaplan: Yeah, so I think there’s several ways that we can think about moving forward and using this analysis to hopefully help fans. I think this analysis informs policies at the league level for how star players should be rested, what should be the incentives or disincentives for resting star players, and how might the fee structure depend on certain situations. I think also from a more private-sector-solution standpoint, there’s a new startup called Fansure that presented at the MIT Sloan Sports Analytics Conference that is designed to basically provide an insurance system for fans when they purchase tickets to alleviate the losses incurred by a player not playing. So put more simply, the company essentially insures your ticket for a small price, and if the player doesn’t play that you wanted to see play, whether it’s LeBron or Steph or whoever, then you get a full refund on your ticket and still get to go to the game. Clearly fans, through our analysis, are willing to pay some economically meaningful premium to watch their star players play, or there’s a dispremium for having them not play. It may be something that we can facilitate where fans decide to purchase insurance systems for players not playing and essentially mitigate the risk that they face in going to a game and having their favorite player not play that game.
Paul Michelman: And what’s next in your research, Scott?
Scott Kaplan: So I think with this research, we want to include the most recent regular NBA season (which has just come to an end) and look at these players’ impacts during this season and see if they differ. The next several steps, just from a methodological standpoint, are to try a couple of different ways to tease out the effects we’re interested in — there’s a couple of other methodologies that we think might give us some interesting results that sort of backup what we found already. And I think what will be cool is to include some data on TV ratings, because that’s sort of the second piece of this story in terms of fans. I mean there’s fans that go to the game, and we can observe those fans’ willingness to pay, and losses and welfare, by looking at the secondary marketplace. But there’s so many other fans who don’t go to the game that watch these players on TV and may or may not tune into games when these top players aren’t playing. So by getting data on TV viewership for games and then comparing games where these star players play to when these star players don’t play, we can get a better idea of the full picture of the losses generated by these players sitting out or not playing.
Paul Michelman: Great. Scott Kaplan, thank you very much.
Scott Kaplan: Thanks a lot for having me. I really appreciate it.
Ben Shields: This has been Counterpoints, the sports analytics podcast from MIT Sloan Management Review.
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