Slaying the Trolls: Dr. David Berri on Sports Economics and Gender Inequity

[Dr. Shirin Mollah] (0:11 - 1:00)
Welcome to the Sports Economist, the podcast where we dive deep into sports economics. I'm your host, Dr. Shirin Mollah. And today we have Dr. David Berri from Southern Utah University. He has written several books and his most recent is Slaying the Trolls. So this is my sports economics class. I just wanted to introduce Dr. David Berri from Southern Utah and wrote a recent book, Slaying the Trolls. It's about women's sports. And today he's going to be discussing a lot about sports economics. He also has his own textbook in sports economics.

I think it's a great book. He uses some good regressions, some detail on a lot of sports. And I really like his perspective on baseball as well.

Welcome, Dr. Berri.

[Dr. David Berri] (1:00 - 1:41)
Thank you. Thank you for having me. So Slaying the Trolls is my sixth book.

And I do remember a lot of what I said in those six books. So I can talk about almost all. So I have told people that in the past that after you write a lot of things, you start to forget what it is you've said.

I've had people quote me and I didn't know what they were talking about. I was like, where'd you hear that? You, you said that.

Okay. So but yeah, we can talk about whatever you like, wherever you're at in the class or whatever particular area of sports economics you may talk about, we can do.

[Dr. Shirin Mollah] (1:41 - 2:01)
Could you just summarize the book? And then I'm going to be asking a lot about like how you see the changes in women's sports. I also know that you have a Twitter wages for wins.

You do a lot of work on wages. So that is down my field. And I would love to talk about it.

But can you just summarize your book?

[Dr. David Berri] (2:01 - 8:45)
Yeah, let's start with the book. So Slaying the Trolls is a book that I wrote with Neff Walker. She's a management professor at UMass.

And the idea of the book was going back about before COVID, I had been writing at Forbes. And I'd written when I wrote at Forbes, about half my articles were on women's sports, half the articles were on men's sports. And I'd written a lot of articles on women's sports, articles that did not make Forbes or other people in men's sports very happy.

And when I left Forbes, and as I tell students, when we broke up, because the breakup was covered in the Washington Post. So I broke up with Forbes, and I contacted Neff, I said, you know, I have all this material, and you do a lot of work in this space. So why don't we both kind of come together and write a book on women in sports.

And basically the premise is a lot of people say things about women in sports, that I don't think the data is consistent with that. The data is not consistent, the history is not consistent with that. And so we put together a book detailing all the things that we had heard the trolls say, that we think the data contradicts.

So the first probably the big overarching thing is that when you look at discrepancies between women and men's sports, why do men's sports have higher attendance or higher revenue than women's sports? The answer seems pretty obvious. Men have historically discriminated against women.

So, and that goes back all the way to the beginning. So initially, when women's sports is attempted to start back in the late 19th century, men effectively banned women from playing sports. And those bands were in place for quite a long time.

One of the oddest bands is that women were prevented from participating in long distance running. And there's a fairly famous story of the first woman to attempt to run the Boston Marathon, and she literally was tackled by a man to prevent her from doing that. What's odd about that story is that if you think about where women and men compete in sports, the one thing that it seems pretty clear women are better at than men in sports is long distance running.

The longer the distance goes, the more competitive women get. So if you do short distances, men do better. But as the distance gets longer, studies show that women not only get to a point where they're as good as men, if the distance is long enough, women are actually better than men.

And so the story that men told is women shouldn't run long distances, which they made up. But the actual evidence is, well, no, not only should they run long distances, they're better at it than you are. But so there's that long history of banning.

Even when they're not banning sports, men did not fund women's sports. And that's true both at the public level. Men's sports in America received billions of dollars in public subsidies that don't go to women.

If you go to a baseball game or a football game, you are likely sitting in a stadium that was built with taxpayer dollars. And that is not true for women's sports. Women's sports do not get these kinds of subsidies.

Men have chosen the sports coverage, and they have chosen to cover men sports far more than cover women's sports. And when it comes to investment, private investment, men are far more likely to invest in men's sports than they are in women's sports, even if there's no particular return in it. One of the better recent examples of that is, it seems highly unlikely the Saudis are ever going to generate a return from their golf tournament.

That is not likely to happen. As I told reporters in talking about this, if you put together the best golfers in the world and they're at a tournament called the Masters and there's a sports jacket at the end of the damn thing, that's something that people will watch. If you take those exact same golfers and you stick them on a golf course someplace and you film them playing golf, now you're just watching a bunch of guys play golf.

That doesn't mean anything. Nobody cares. It's the Masters that matters.

You won something that matters. It's the same thing in every sport. There are tournaments like Wimbledon that have a lot of great tennis players out there.

Nobody watches them. It's not Wimbledon. It's just people playing tennis now.

So the venue matters, the history matters, and all that history is biased towards men. So that's the big story. We also talk about other things about men and women's sports.

I think one of the more interesting ones is there is a tendency, and I just said this about women beating men in long-distance running, there's a tendency men have in arguing that women sports is not as interesting as men's sports because men are better. Men don't evaluate men that way. If that were true, middleweight boxers would never have any fans.

Nobody should watch a middleweight boxing match or a lightweight boxing match if what they're interested in is absolute quality. Nobody should watch a college football game if they're interested in absolute quality. There is no college football team that could beat the New York Jets in a football game.

New York Jets are all professionals. They're bad professionals, but they're professionals. College football team, every college football team doesn't just have bad professionals.

They have no professionals. A lot of those players are never going to play professionally. They're not that good.

So if Alabama plays the Jets, they lose. But people watch Alabama play football more than they'll watch the Jets play because it's relative competition that matters, not absolute. And that's why women's sports are just as compelling as men's sports because it only matters whether you're best in class or not.

That's why last year the NCAA Women's Championship drew more fans than the NCAA Men's Championship. Does it make a difference whether Caitlin Clark was better than the men that played the next night? Her matches were more compelling.

That's why people were tuning in. So there's just this long list of myths that men have created for why women's sports lags behind men. And I think if you study and understand how demand works and how the economics of this would work and how the history of this works, you would say, okay, well, that's not really how any of that actually goes down.

The men are not getting this right. The story is just, you discriminate it. That's why we get this outcome.

So that's the book in a four or five minute nutshell.

[Dr. Shirin Mollah] (8:45 - 9:06)
Thank you. I do have a question because you brought up Caitlin Clark. And I think a lot of my class is doing like a superstar effect.

But how do you think that Caitlin Clark is going to be affecting WNBA? Not just, okay, so we have one year, but in terms of economics in the future, how do you think?

[Dr. David Berri] (9:06 - 17:17)
Well, okay. I've written about superstar effects. I think sports are different than other entertainment options.

I tell students this, sports are not a circus. And so I'm going to answer the Caitlin Clark effect by talking about first, the Larry Bird effect, and the Magic Johnson effect. Because I think people have said that.

They said Caitlin Clark and Angel Reese are to the WNBA what Larry Bird and Magic Johnson were to the NBA. And the story they tell is that the NBA was struggling in the 1970s. And then Larry Bird, Magic Johnson came along and they saved the NBA.

And the only problem with that story is the data doesn't say that in the slightest, that there's no data that says that at all. The story of Larry Bird, Magic Johnson is this. The NBA in the 1970s saw their attendance go from about 7,000 fans to about 10,000 fans per game.

It also saw that African Americans increasingly were playing the game to a point where now they were 70, 80% of the athletes. And not only were they playing it, the African Americans started fundamentally changing the way they played. So when Oscar Robertson played, he didn't dunk the ball.

He could dunk the ball, but he was told not to. So he did. He was told in the early 60s, we don't dunk the ball in the NBA because we're not the Harlem Globetrotters.

We are professional basketball players. We play like professionals. And then African Americans, especially coming out of the ABA, going to the NBA in the late 70s, and they're dunking the ball all the time.

And a lot of the white sports writers don't like this. They don't like how they're changing this. And even though the attendance data says, hey, the fans are okay with this, attendance has gone up.

They start writing stories. The NBA is in trouble. The NBA is not making money.

The NBA is not doing well. There's too many NBA players who do drugs. And it's really bad.

And it was a lot of stories that were very racially tinged and how they're writing it. We get to the 80s and what you see in the attendance data is this. Larry Bird and Magic Johnson show up.

Overall attendance goes up 100 fans per game. That's it. That's all it goes up.

Next year, hardly any change. The next year drops 900. Big drop off.

Biggest drop off in NBA history with Larry Bird and Magic Johnson there. Then it goes, starts to gradually increase as you go through the 80s. And then in the late 80s, big uptick.

Suddenly it goes to 15,000 fans per game. Well, that can't be Larry Bird and Magic Johnson. They've been there for seven, eight years by then.

What happened? We changed the television coverage. So in the early 80s, and I don't want to say how old I am, but in this case, I would know this.

In the early 80s, I grew up in Detroit. My favorite player is Isaiah Thomas. I couldn't see Isaiah Thomas unless it was the All-Star game.

That was the only time he was ever on TV. So there were no basketball games on TV. The finals were on tape delay.

They didn't show very many games. You couldn't see the NBA. The networks didn't show them and cable television hadn't really taken off yet.

Mid 80s, cable television takes off. We got that in my house. Other people got in their house.

Suddenly in the late 80s, TNT, TBS start showing the NBA every Tuesday and Thursday, Friday night. And everyone was watching the NBA on a regular basis. What were they watching?

Larry Bird, Magic Johnson, Michael Jordan. That's who they're showing. And people are like, ha, see, that's what got you watching.

No, no, no, no. What got me watching was you put it on. I didn't have it on before.

I couldn't see it. How could I possibly have seen it? It wasn't there.

That is the same story as Caitlin Clark. Because what happened is we go to COVID and we put the women's and men's basketball tournaments in these bubbles. And Sedona Prince shows a video and says, the weight room for the men is a weight room.

And the weight room for the women is one rack of dumbbells. That's it. For 64 teams, one rack.

You didn't give us any equipment. You didn't do anything for us. You are treating us differently.

And there was this big media outrage and all these stories and the NCAA Commission's a study. And they say, hey, and I like the way the NCAA put it, we dropped the ball when it came to women as if it was an accident. Whoops.

Whoopsie. No, you didn't drop. You did this deliberately.

You focus all your attention on men. You didn't do anything. No.

After that, suddenly the decision makers at ESPN and ABC said, you know what, maybe we should cover women's sports more often. Women's basketball, for the first time ever, college basketball showed up on network television after that. And when they saw the ratings, they started doing it more and more.

And it is also the case that women's college basketball has an advantage over men's college basketball is that there's no one and done rule. So Caitlin Clark kept coming back. Paige Bueckers keeps coming back.

They don't go away. You get to be fans of them. Sedona Prince, her college career lasted 37 years.

She started playing for a lot of college teams and she claims now she's done. She's never coming back, but she did play a long time. And so the men's don't do that.

It's hard. It's hard for men to develop any kind of connection to the fans because you're only there for a year. And so you don't have any idea with all you're watching.

And so these television coverage changed the story lines. And the beneficiary of that was Caitlin Clark, because she was the star of the moment when that happened. So she becomes a big star.

And then the WNBA has this advantage in that the players roll over right into their league of Paige Bueckers going to be in the WNBA in three weeks. And so that makes it so the coverage just keeps going. So I would argue that it's not Caitlin Clark has magical star power.

It's that there are always stars because somebody wins the games and somebody puts up the stats and somebody does something. And when you change the coverage, those stars become known. Magic Johnson, Labor, Bird King, known because the coverage change.

Michael Jordan became known because the coverage change. There were players like Michael Jordan before Michael Jordan. Elgin Baylor was like Connie Hawkins, Dave Thompson.

They were all like Michael Jordan. But nobody got to see them. So they couldn't be Michael Jordan.

Michael Jordan was a beneficiary of them changing the coverage. And he was star of that moment when it happened. And that's what happened to Caitlin Clark.

So is it going to continue? Yes, I expected totally to get WNBA is going to keep doing well. They will keep drawing.

It is now we're now at a point now where the WNBA their average regular season game last year was a million fans per game. The W the NBA average is 1.4 million. It's not that much different.

And that gap is going to keep closing. They just did a television deal. The NBA negotiated this for $76 billion.

And the reports that I have seen, and I've talked to people that WNBA they know, the WNBA was given $2 billion of that out of $76 billion. It was not negotiated. It's not a market decision.

It is the WNBA. The NBA gave them $2 billion. If you look at the difference in ratings, and it is case NBA has more games, NBA playoffs do better.

But if you adjust for all that, by my math, WNBA is at least worth $10 billion. And if you're only going to give them $2 billion, and you're supposed to give them $10 billion, then $8 billion is being subsidized to the NBA, which means now going forward, WNBA players are now subsidizing NBA players. And they're subsidizing them at a level that far exceeds anything the NBA claimed they were giving the WNBA for the last 25 years.

[Dr. Shirin Mollah] (17:17 - 17:45)
You mentioned that the WNBA catching up to the fans of the NBA. We also talk about how WNBA hasn't been around as long as the NBA. But if it was, we might see, do you think that we might have seen some similarities in other aspects, especially revenue and other parts?

[Dr. David Berri] (17:46 - 24:41)
Yeah, we write about that. In Slang Charles, we tell a story. There was a women's basketball league that was started in 1978.

And it was right after the 76 Olympics. That was the first time the women got to compete in the Olympics in women's basketball. Some people said, why don't we take advantage of that?

Women's college basketball had just really started because Title IX is 72. So women's college basketball suddenly starts being sort of a thing. And they were at the Olympics, sort of a thing.

And so they start this basketball league in 78. The major star of that league that they decide to promote, and this is the 70s. The coverage is more sexist than you would see today.

The main person they focused on, there were a lot of African-American stars. They focused on a player named Molly Bullen, who looked somewhat like Farrah Fawcett. And she scored about 30 points a game.

And so she was the star. And they put her on Sports Illustrated. She was like the one that they talked about the most.

And she did score a lot of points. But the league only existed for three years. And after three years, the investors were like, we haven't made any money, so we're closing this down.

If you go back and you look at the NBA after three years, it's a total disaster. There's no money being made at all. They're losing money.

If you go back to the NFL, the NFL is a fantastic story because that's the biggest sports league in the world. And the NFL, of the first 40 to 45 franchises that entered the NFL, 90% of them went completely out of business. The failure rate was immense.

Major league baseball, first 18 teams, 16 went out of business. So the early history of the big men's sports leagues is, in the first three years, they all go to business. But the men didn't give up.

They just kept throwing money at it. When the women did it, they're like, oh, well, we give up. Had they not given up, Molly Bullen today would be a household name because she was the first star.

I actually asked somebody, very prominent person, WNBA, who's been around a long time, I asked them when we were working on the book, and I looked up these stories. I said, do you know what Molly Bullen is? They're like, who the hell's that?

That's somebody in professional basketball. The history got forgotten because nobody cares, the league closed. So if Major League Baseball would have gone out of business in 1930, Babe Ruth would be forgotten.

They'd be like, who the hell's that? There was this guy in a bunch of homers. Well, that's a league that doesn't exist anymore.

So who knows? And so it had women's basketball kept going from 1978. We would now be in close to the 50th year.

Women's basketball would be what the NBA was after 50 years, which was a huge deal. There's no reason why women's basketball sports doesn't follow the same path as men's sports. The fans behave the same.

The interest is the same. It grows at the same rate. WNBA is growing at the same rate.

In fact, it's growing a little faster than the NBA was. Women's soccer does incredibly well. Women's softball does as college softball, does as well as college baseball does.

Women's tennis does as well as men's tennis. There's no reason why these can't be the same. It's a level of investment.

And what's interesting about the story of the investment is how shortsighted investors are because imagine if you could go back in time to the early 70s and they put the Boston Celtics up for sale and they said, you know, you can have this team for $5 million, which is I think roughly what they sold for. I think people would go, well, I know it's going to be $6 billion in 50 years. So that's a good deal.

So we already saw that. And yet you have women's sports today. They put them up for sale and they're like, you know, what will you give me for this?

And they're like, well, I don't know, $200 million, I guess. You're like, you paid $300 million for a major league soccer team and that league's not going anywhere. Why wouldn't you pay more than that for a WNBA team where the league is going someplace?

Well, you know, I like watching men's sports. That's what's happened. Men are the ones who have the billions to do this.

You can see that if you look at the Forest 500 list, it's very male dominated. They have the billions to do this, but they tend to invest a lot in men's sports that aren't going anywhere because they like men's sports. They're emotionally attached to it.

We talk about that as laying the trolls. The way we put it is there's an emotional gap. You don't see in the women's investment in an owner like Art Rooney.

Art Rooney started the Pittsburgh Steelers in 1933. The league had had 90% failure rate. It's the middle of the Great Depression.

There's 50% unemployment at Pittsburgh. He decides as a sporting goods owner, I mean, he's not a rich guy. He puts up $15,000 or something like that to start the Steelers.

Not only does he put the money into it, they're terrible. And they're not terrible that year. They were terrible the next four decades.

40 years go by and Art Rooney saw one playoff game. And in that one playoff game, the Steelers didn't score any points. And he kept throwing money at this losing, terrible, horrible franchise because he loved football.

And we point this out in the book. In 1972, the Steelers finally get back to the playoffs. In the game, they're playing the Oakland Raiders.

The score is, I believe it is six to three or seven to six, something like that. The Steelers, they kicked two field goals. That's all they did.

They still haven't scored a touchdown. Art Rooney still hasn't seen a touchdown. Last play of the game, Steelers have the ball.

They're 60 yards from the end zone. They can't kick a field goal. Terry Bradshaw is their quarterback and he's awful.

He is a horrible quarterback. He drops back to pass. Franco Harris is a running back.

Doesn't have anything to do on the plate. He just kind of, he says that's the, I don't know. That wasn't called for me.

I was just kind of running around and Terry Patrick goes back. He's scrambling around. He finally throws the ball downfield.

He misses the receiver by a mile because he's horrible. It bounces off a raider who doesn't know it's coming, goes up in the air. Terry Bradshaw picks it up before it's around, runs in the end zone scores, touchdown, Steelers win.

That's the first time Art Rooney saw a playoff win. First time he saw a playoff touchdown in 40 years. We don't see that on women's side.

Nobody's investing for 40 years in a women's sports team that never wins, never makes any money. And so there's this emotion gap. So that's another, you know, that's another difference between, between women and men.

[Dr. Shirin Mollah] (24:41 - 24:55)
I have more questions, but we do have a question from Diego. Does the NCAA women's lack of one, one and done have more to do with women's college basketball or the much lower WNBA salaries compared to NBA?

[Dr. David Berri] (24:56 - 34:32)
It's, it's, it's partly low salaries. So a number of WNBA stars are coming, a number of college stars are coming back because they know that the collective bargaining is going to be renegotiated. So really you don't want to come out right now.

The salaries are really low. The NBA, the salaries are artificially depressed by the NBA. So just so everyone understands in the class, the NBA owns at least 60% of the WNBA.

And I, I, we have a quote in the book from the chief executive officer of the Atlanta dream, Suzanne Abert, and she said very clearly to me, if the, if the 12 WNBA owners want to do something and the NBA says, no, the answer is no. The NBA is in charge. The owners don't have a say.

And that's why charter flights took a long time to happen because the NBA wouldn't sign off on it. The NBA decides what to do to understand how low the salaries are in the NBA league revenue in the NBA, WNBA in 2023, we know from a Bloomberg report, we're $200 million for the league, 200 million. That is in real terms, what the NBA earned in the early seventies when it was about the same age, 200 million in nominal terms.

So the NBA was only bringing in about $30 million in revenue in the early seventies. At that time, they agreed to pay Walt Frazier, $300,000 a year. And there was actually other players also making 300 to $400,000 a year.

So the league is $30 million in revenue paying out 300, $400,000 contracts. WNBA has 200 million in revenue. The most they pay out in contracts is $250,000.

So in real terms, Walt Frazier was getting 10 times what WNBA players are getting. So the salaries are really, really depressed. And that does make a difference.

Now, you should understand, there's all these endorsement things that WNBA players get. Caitlin Clark didn't take a pay cut to go to the WNBA. She still made a lot of money, but her salary is low.

It's artificially depressed. So that makes a difference. But the other issue is that the number of teams is so small.

The NBA in the early seventies had like 17 franchises. The WNBA is now getting to where they're going to have 16 in a couple of years, but it was only 12 for a long time. And this has led to a really bizarre outcomes.

If you watch WNBA draft in next week, you should understand the first round players, the first six almost definitely make a team. The next six, pretty sure, pretty sure they're going to make a roster. But when they go into the second round, it's a 50-50 shot where they even make the team.

And when they do the third round, it's meaningless. Third round picks don't mean a damn thing. It's almost impossible for those players to make a team because the rosters are stuck at 12.

They don't let them expand. There's no G league. And so there's 144 slots and it's really hard for any rookie to make any of those teams.

And even if they make the team, the odds of them playing is really small. Alyssa Pealey was the eighth overall pick for the Minnesota Lynx last year. She barely got on the floor.

It's just really hard for them to find any playing time for these people. There's so many veterans that have been there for a long time and the veterans are better. And so there's no reason to come out before you're eligible.

Obviously, they also have a rule in place that you're not even allowed to come out even if you wanted to because you have to play until you're a junior or senior anyway. So there's that too. So the rule is actually there.

But even if there wasn't a rule, there's not enough roster spots for you to have a place to play. They don't pay a lot. And these are all NBA decisions.

They're the ones who call the shots. They're the ones who decide all this. We should note the NBA, I'm sure that the students have heard this, that the NBA doesn't make any money, that it doesn't make a profit.

The NBA has said that about the NBA. They first said it. Well, as far as I know, the first time they really explicitly said this was in the late 60s, early 70s, NBA, ABA wanted to merge.

The US Senate and the courts wouldn't go along with that. The NBA said, we have to merge. We don't make any money.

And the court said, we don't care. You're not merging. After they merged, they did an Oscar Robertson rule.

So we're going to have free agency. NBA salaries were up to like 60% of revenues. In 1983, the NBA said, we're going out of business.

We're going to go out of business. If we don't cut NBA salaries, we're going out of business. Are you really going out of business?

No, we're lying. That's totally a lie. We're not going into business.

But they said it. They said it to everyone in the media. We're going out of business.

We're almost on the brink of bankruptcy. The league is dying. It's dying.

And you look at the attendance numbers. It doesn't look like it's dying. It looks like you just signed a new television deal.

It looks like you're doing pretty good. Now we're dying, dying, dying, dying, dying, dying. So because I said that, the NBA players agreed to a salary cap and player salaries got cut.

And the NBA was, oh, this is so good. So they came back to that same argument again. They kept coming back to it.

We're not making any money. In 2011, this was my favorite. This is the first time I weighed in on this as a sports economist.

In 2006, the NBA reached agreement with the players. It was barely even in the papers. They renewed the agreement.

They were perfectly fine with it. 2011, the NBA decides, no, we want to pay cut. They go to the media and say, we're losing money.

We've lost money in every year since the last deal was made. And I wrote a Huffington Post at that time. I said, how is that possible?

When you signed the agreement in 2006, you knew what the player salaries were. You knew what the gate revenue was likely to be. You knew what the broadcasting deal was being.

How could you have agreed to a deal so easily if you knew you're going to lose money? That makes no sense. You're lying.

And I got a nasty letter from a vice president going, we're not lying. And I said, well, then show me your financial statements. No.

Well, then you're lying. So and it worked. The NBA players agreed to pay cut.

And it totally worked. And so the NBA has been going back to this playbook again and again. So they've said about the WNBA, we're losing money.

Can't make any money at this. And they were saying for years, we lose $10 million a year. And then this last year happened and attendance went up dramatically and merchandise sales went up dramatically.

And they came out and they said, okay, you know what we're saying? We're losing 10 million. They wrote this.

The New York Post wrote this last October. They wrote a story saying the WNBA lost $40 million last year. Wait a minute.

You said they were losing $10 million before. It went up four times, but your revenues went up, but your player salaries haven't changed any. How is that possible?

That's not believable. But the New York Post, and this is the thing that I said over and over again, I said this to reporters over and over again. If the NBA says this or any sports league says this, we are losing money.

The New York Times will report that as the NBA is losing money. And when I was at Forbes, I said that's not the correct way to report that. The correct way to report that is the NBA has asserted that they are losing money.

And I had an editor at Forbes say, you can't say it that way. I said, but that's what they did. There's no evidence.

They didn't give us any financial statements. They have asserted something. So we should report it as they've asserted this.

They said, no, we have to report it as it's true, but we don't know it's true. How can you report something that you don't know is true? And they said, well, we can't do it that way.

I'm like, oh, so you have different rules for reporting depending upon who gives you the information because that doesn't make any sense. If I told you something and I know evidence, you would just say, I asserted that. But if they say it, then it's true.

That's not the way reporting works. And so one of the many reasons why we broke up. But you should understand that the WNBA is probably not losing money.

That's nonsense. The WNBA is also not subsidized. There was an owner of the Atlanta Dream made a very emphatic statement about that.

He said, if we're being subsidized, I've never seen the checks. I don't know where they're coming from because I get no checks. We pay our own way.

We're not being subsidized by the NBA. The WNBA is not losing money. That's probably not true.

The NBA just says things. They say it because they know it's a negotiating tactic that works. And they just go back to it every time they're negotiating.

And it's not a coincidence, I think, that they told the New York Post that, and three days later, the women opted out of the collective bargaining. They knew they were going to opt out three days later. That's why they wanted that story in the papers.

And it works every single time that they do this. It's what they do. It's their negotiating tactic.

And the reporters keep buying it. Apparently, nobody ever makes money at basketball. The NBA can't do it.

What's really weird, and I'm going to write about this, I think, tonight or tomorrow, the league unrivaled league to have their first season. And they announced to, I think it's front office sports. They had a story this morning.

They said, we're not sure we made money this year, but we fully expect that we'll make a profit next year. Wait a minute. How is it possible that a league basketball league could make money?

It's like, well, it's not that hard. I mean, we know what we're doing. It's like, apparently, only when the NBA runs it do they not make money?

So weird. So but that's why they tell that story.

[Dr. Shirin Mollah] (34:32 - 34:46)
I know that there's a lot of students that are interested in doing their projects on sports betting. Could you talk about that? And I mean, I know you do women's sports, but you can just talk about it generally, even if you want to tie it back.

[Dr. David Berri] (34:47 - 35:07)
I do all sports. I do everything in sports, except for betting. So if you look at my textbook, it's the one subject I didn't put in there.

I will say this about betting. I'll say this about sports economics and betting. A lot of economists do study sports betting.

And I remember this. So you know what Victor Matheson is, right?

[Dr. Shirin Mollah] (35:08 - 35:08)
Yes.

[Dr. David Berri] (35:08 - 40:58)
Yeah. So Victor Matheson is a fairly famous sports economist. And he and I have something in common.

We're both amazingly loud. So if you go to a Victor Matheson presentation, or you go to my presentations, you'll notice that neither of us need a microphone. You can hear us in the hallways.

And so there's a debate among sports economists who's louder, Victor or me. It's probably I don't know, we're close. And so but I remember Victor doing this once at a meeting.

He was doing a study on sports betting. And we this is when they first got data where you could see the gambling line during the game. So you can place bets during the game.

And you can see the odds change and the betting change as the events in the game. And he was showing that something happened in a baseball game, home runs hit or something. And the betting line adjusted within seconds.

And I remember him standing in the room pointing to this in a very loud fashion as Victor does. And he goes, look how rational these people are, how quickly they adjust how rational it has the word to use, how rational they are. And I'm sitting in the room going, gamblers are are rational.

These are people who bet on sports, like, like a regular thing in their lives. That's not that's not rational behavior. That's insane.

Why would you do that? I question the premise that gamblers are rational people. I just find that hard to believe that that's, it seems like there's so many things you could do with your money besides betting on sporting goods, because the odds are adjusted so that it's a 50 50 shot.

So it's, it seems like a lot of gamblers suffer from immense levels of overconfidence that they think they know something that all the other gamblers don't know. Because you can only make money if that's the case, you have to know something the other gamblers didn't know. There is somebody who actually does this.

I've gone through it. This is detailed the textbook. I've gone through it.

I've measured productivity of basketball players. And what's interesting about the measurement is basketball analysis tends to focus tremendously on the people who score the most. So whoever scores the most is considered to be the best players, because that's the one that the eye fixates on.

That's the one you see scoring so that they must be the best. If you go through the data, you can see that basketball outcomes, wins and losses are determined by three basic factors. You have to get possession of the ball before the other team scores.

You got to rebound, you got to force turnovers. You got to make sure that you avoid turning the ball over back to them. And you got to make sure you get offensive rebounds when you miss.

So the two factors first two are rebounds, turnovers. And then the third one is obvious. Once you have the ball, you have to make the ball go in the basket, which means you have to shoot efficiently.

It's not how much you score as the individual, it's did you do it efficiently. So shooting efficiency rebounds turnovers. And when you look at that player like Carmel Anthony, who right now just got in the Hall of Fame, was never a very good basketball player because he never shot very efficiently.

He wasn't a great rebounder and he didn't really avoid turnovers. He just took a lot of shots. That was what he did.

And it worked for him. He became a Hall of Famer. He got paid hundreds of million dollars because basketball is irrational.

And that's what that's in my textbook. And I've written about that extensively. There is a guy out there I discovered, and he created a sports betting thing where he said, I'm going to bet on basketball based on my understanding of that, that I understand shooting efficiency rebounds, and the market may not know that.

And my understanding of this, I don't know that this is totally true. My understanding is that this guy's made money doing that, that you can actually make money. And you have to look at games where, because obviously the big thing that's going to drive the betting line is, you know how good the teams are.

We can see the one loss records. We can see points scored, points given up. And so once that's known to all the bettors, you don't have any advantage anymore because those outcomes reflect shooting efficiency rebounds turnovers.

However, if there's a trade that happens, a team acquires an inefficient score, the betting line initially, from my understanding, is going to think, hey, that means that team's going to be great because we think that score is phenomenal. And the person who understands basketball is going to go, I noted that against that team. That's not going to work out for you.

That's a bad deal. And so there's going to be a game to be made in that brief moment in time. And my understanding is this guy's been taking advantage of that.

But I don't know how you, as a professor, feel about money. But academia is just a weird kind of job in that. But what I do for a living is I talk, which I like to do, and I write, which I like to do.

And my advisor from when I was in graduate school is 90 years old and he's working on his next book. It doesn't feel like, you know, the stock market went down. I did bother to check.

I was curious, how much money did I lose? And apparently I lost a lot. But it's retirement money.

When exactly am I going to retire? I don't know when that's ever going to happen. My advisor's 90.

He doesn't seem like he's retiring. So I don't have a lot of incentive to spend my time gambling on basketball. What would I do with the money?

I don't need it. So I don't do it. So I don't care.

But this one guy was like, you can do that. Well, okay, I guess you can do that. You're not a professor, though.

So, you know, professor is just a weird job. We're not working construction here. We can do this forever.

So I don't know how you feel about that. That's how I feel about it.

[Dr. Shirin Mollah] (40:58 - 41:30)
So I do have a question on the basketball because you did mention, so you did mention about like the shooter's mentality. And it's like they keep shooting. What is your perspective on the hot hand fallacy?

Because there's a paper that's like working paper right now on hot hand hot hand by location. And I think it's a really neat paper. But not only that, it's like when you're watching basketball, you're like, okay, I see what they're saying because it's behavioral economics.

[Dr. David Berri] (41:31 - 46:27)
But okay, so this is a really famous behavioral economics paper that was done. I don't know, what was it 40, 50 years ago. And it was this idea that there's no such thing as a hot hand.

And they couldn't find the data. So there was a couple of sports economists. And I remember them coming to the, so for years, it still happens, actually.

Sports economists started meeting first at the Western Economic Association back in the 90s. And I started going soon after that started. And then for about 10 years, I was running the meetings.

I was organizing it all. So I was going to all these sessions. And we would get, we would have about 15 sessions a year.

And a session has four papers in it. So there was 60 to 70 papers a year being presented across all the days of the meetings. And they were very well attended.

So if you've been to an academic meeting, typically, your audience is about four people. Sports econ would have like 50 people sitting there. And so there's just tons of people there.

And they were from all over the world. And they were all going to these meetings. And there was a couple of sports economists who were just obsessed with this hot hand thing.

And they hated it. Their objective in life was to prove this is wrong. There is a hot hand.

There is no policy. And I remember one of their papers, they started off, and that was what the guy said when he started off his paper. He said, I know this is wrong.

So I set out to prove that it's wrong, that it does exist. And I was like, well, that's not the way we begin science. We don't do science that way.

We don't start with our conclusion and work our way back. But the guy did. He's published papers on it.

One of them actually wrote a book on it. He was very pissed off about it. And so there's a lot of discussion on it.

And my sense is that if you play with the data enough, you can probably show anything you want to show. And I think people have shown that if you look at it this way, there's a hot hand. And if you look at it this way, there isn't.

I don't know that it's something that's terribly operational, that a coach could take advantage of it. So it is a case that runs are going to happen. You're going to hit shots in a row.

And that can happen. And so, yeah, so it can feel like that. And certainly, if you've ever played sports and things are going well for you, it feels like something magical is happening.

But that's just your natural reaction to it. I mean, if you were flipping a coin and you got heads five times in a row, you'd feel like your hot hand on heads, right? But you know, that's not really real.

So I think there are people who definitely believe it exists. I tend to believe I don't understand the mechanism by which it would exist. Certainly, there will be streaks.

People will have streaks that will happen. I find it hard to believe that that's something that's consistent. But I guess if you want to believe it exists, that's fine.

I just can't imagine a coach really being able to systematically take advantage of that. It's like, you know, you had three shots. I can see a coach doing that.

You hit three shots in a row. What the hell? Give them another try.

What the hell? Maybe it'll work. But I just can't believe that you could systematically sit there and organize your team that way.

And also, it's the case that one thing to remember about basketball, given the importance of how number of points scored dictates everything from the player's perspective in terms of salaries and playing time. I've done lots of studies showing that. It's number of points scored dictates draft position, salaries, playing time, awards.

There are two competitions in every basketball game that the competition, two teams. And then there's a competition on the team who gets to shoot. And it's really weird when you watch a basketball game and you hear an announcer say, this strikes me as very weird, where they'll say the they'll say a big man makes a defensive player at the end and runs the floor.

And the announcers will say when the point guard throws in the ball, you have to reward him and let him shoot because he did a good thing over there. You're like, well, that doesn't make any sense. Nobody does that in any other sport.

We don't sit there and say if a wide receiver makes a block, well, the next play, you better go to him. Well, yeah, if he's open, I'll go to him. But if he's not open, I'm not throwing him the ball.

He's not open. I mean, this is not a game. Every play is unique.

I'm not rewarding anybody. It's that you did your job. You're supposed to do that.

But they do that because they know that scoring is what dictates outcomes and you have to let people shoot. And so that's the nature. It's really weird that basketball people seem to know this is true.

And that that's but that's not that's not how it determines wins wins don't go that way.

[Dr. Shirin Mollah] (46:27 - 46:57)
So I have a question because I do labor economics. And I just chose like a contract because it's such a big contract. And we're in LA.

And I wanted to know your perspective on how you think of it as like the present and future value of Shohei Ohtani 700 million 10 year contract and economics perspective. I know we all know about the contracts, how it is, but more of economics or even finance.

[Dr. David Berri] (46:57 - 52:06)
Well, it's given his age and given how player performance changes across time. It seems likely at the end of that deal, that's not gonna look so good. And that's, you know, that was the Albert Pujols effect.

It was the Miguel Cabrera effect and Miguel Cabrera at the end, the Tigers took a huge chance on Miguel Cabrera. They gave him a massive contract last three years he could barely hit. And they would trot him out.

The last year he played, they trotted him out like every week as like, you know, hey, it's Miguel Cabrera night. He's going to go up and swing. And will he hit?

No, he can't hit anymore. His legs are shot. So he can hit a single.

But that's as far as he can hit it because he doesn't have the ability to hit the ball very far anymore. His legs don't have it. And at some point Ohtani is not going to be able to do this anymore.

And if you sign somebody with a 10 year contract when they're old, well, in their late 30s, it may all go away. And baseball is one of those odd sports where it feels like it goes away like on a Tuesday. It's like, I could do this yesterday.

And then today now I can't do this anymore. Like what happened? I don't know.

I just ain't working. I'm this far behind that I can't do it. And you see that I remember as a kid when I collect baseball cards, you'd get these Hall of Famers, you look at their stats and it's great, great, great, great, great.

Last year hits 180. I retired in May. You're like, what happened?

I don't know. So it's likely that at the end of that contract, probably not good. But this is something I'm working on and writing about right now, because I'm working on a book.

I'm trying to write a sports econ book that's a little different than a textbook with more fun. And one of the stories I'm telling is I think what we want to know in labor economics and what we believe is that there has to be some way to objectively know what somebody's worth. And there's this moralistic argument that goes all the way back to JB Clark, who I don't think your students probably don't know who that is.

So there's the JB Clark medal, which goes to every economist under the age of 40. I've written before that I don't think anyone should be allowed to win that award unless they can tell me who JB Clark is, which means I don't think anyone can win it. Because I've actually, we've hired a bunch of brand new people in my department and none of them know who JB Clark is.

I'm like, none of you are eligible. But it's in my textbook, I do talk about who he is. But JB Clark had this idea that you could just you could objectively know what somebody's worth.

And but if you go through the sports data, and we have the Gerald Scully method, and what we discover, and I write about that in the textbook, well, it is an objective. Gerald Scully's model tremendously exaggerates the value of a baseball player in the late 1960s. His model actually said that players were worth more revenue than the actual revenue the teams had, which doesn't make any sense.

And in the paper he wrote in the American economic review in 74, it's pretty obvious, I think when you read it, that he knew this, that he knew he made a mistake. But nobody had ever done it before, somebody could check on him. And so he starts doing this in the paper, he goes, well, I estimated the gross MRP of the players, and I got this number.

But the number that we're going to use is net MRP. And you're like, well, what is that Gerald? He said, I'm going to deduct from the player's value, capital costs, training costs, equipment costs.

I'm sorry, Joe, that's owner expenses. That's not player expenses. But if I don't do that, the players are worth way too much money, and my model looks wrong.

So I'm going to make up this thing. You're like, that's not even labor economics anymore, just make enough stuff. And then I know in the textbook, if you do the same model, but now you do it with recent data, you get the exact opposite result.

Now the players aren't worth anything at all. And the issue is, it's how much fixed revenue is there? And fixed revenues are revenues that don't vary wins.

And then in the 1960s, there's really very little TV revenue, almost all the revenues at the gate. And so it's all being driven by things that would drive winning. And you go today, so much broadcasting revenues, nothing good wins at all.

And so the question is, what is Otani deserve? What is he worth? And the answer is, I don't know, it depends on what you want to give him, it's all bargaining power.

And Otani is worth a lot, because he's such a unique talent, and he brings in so many fans from around the world, that it may be the case that if you look at his productivity, at the end of this contract, he's not going to be worth that much. But it's also probably the case that right now, he's worth way more than you're ever going to be paying him, because he's drawing in so many fans from everywhere. And he's so incredibly unique as a player.

So really, what you're doing is, you're underpaying him now, and you're going to overpay him later. But if you want to know what exactly is he worth, what does he deserve? I would argue there's no objective way to know the answer to that.

We don't know.

[Dr. Shirin Mollah] (52:07 - 52:20)
So how do you think data has changed or helped us inform sports decisions, whether it's a business side or even just performance? Do you think it's changed over time?

[Dr. David Berri] (52:21 - 59:09)
For some things, yeah, baseball, yeah, baseball, the data analysis is just insane, what they can know. And you can pick up on it. When you watch them interview managers during game, how analytical they are.

They'll ask questions about what do you think about your picture? And they'll say, I don't feel like the curve ball is hitting the spots that we want. I don't feel like he's placing the ball right where I want him.

I like the velocity, but I don't like this. And you're like, that's really, and they got it down to, I know how many RPMs the ball is spinning at. And I know the break on the ball, and I know this, and the hitters know all these things.

And they had to outlaw the shift in baseball because they got the analytics to a point where like, I know where you're going to want to hit the ball. I'm going to put my fielders everywhere and now you can't hit the ball at all. And the hitters were like, that's not fair.

And the solution to that was like, this actually happened in the, I was watching the Tigers play the Yankees today. They can't do the shift anymore. You have to put two fielders on one side and two fielders on the other side.

But the Yankees did this with Colt Keith. They actually moved their third baseman almost to the shortstop spot. So there's this, they did it.

They like shifted them all. And they said that they said Colt Keith saw that. And he, he tried to hit the ball where the hole was.

And they said, I think he almost broke his back. He likes, he like twisted in a way. It's like, I don't think you can do that, Colt.

What are you doing? And, and, and what the players learned was that they actually couldn't hit the ball in specific spots, that the analytics was so good. They, even when the, the player knew that I know, you know, I do this, I can't stop myself because this is how I hit the baseball.

I do hit the baseball that way and I can't stop myself. I can't direct where the ball's going. So it's all based on tendencies.

So baseball, very, very good. In basketball, I would argue it's a total disaster. So much of the information they have is like, that is useless to know that.

Plus minus is useless. It doesn't tell you a damn thing, how well a team does with and without a player on the court. There are 10 people on the court, outcomes are dictated by those 10 players.

You can have players who have an outstanding plus minus because they're just playing with specific players, or it was just a quirk in the data. The box score data in basketball really does tell you exactly how good they are. You don't really need much more information than that.

It is just shooting efficiency, rebounds, and turnovers. That's really all you need to know. And there are such differences in how good the players are, that the, the basic stats are going to tell you, yeah, that player is way very good.

That player's not. And they're not going to change. Players in basketball don't change very much.

They are remarkably consistent year after year after year. Their box score statistics stay remarkably the same. And that's because LeBron James is way better than everybody else.

And, and everyone knows he's way better than anybody else. And you would think if defense mattered and coaching mattered and teammates mattered and schemes mattered, LeBron James stats should go all over the board because he's changed coaches and teammates and schemes consistently throughout his career. And it never makes any difference.

A player can go from one team to another from one night to the next. And their stats are identical because it doesn't make a difference who they play with. They just do the same thing regardless.

So basketball, I don't think the advanced stats are telling them anything. It's just noise. Football.

Football is really, really hard to do advanced stats or any kind of stats because the problem that we have as researchers is I know the outcome of the play. You threw an interception. You completed a 15 yard pass.

You did this, you did that. The problem is, I don't know what play you called and I don't know what you're trying to do. I can't tell.

I know what you did. I can see it. But it's like, what were you trying to do?

And there are plays. Tom Brady did this analysis once. He said that he was watching a quarterback play and they said the announcers were very happy because the quarterback dropped back to pass and he ended up running for 15 yards.

And Tom Brady said, yeah, you shouldn't have been happy about that because when that quarterback got to the line of scrimmage, I saw the receivers all run slants. And I saw the defense that he was facing and they were playing this particular defense and slants were never going to work. They were not going to be open.

He had to run 15 yards because the play that he had called was never going to work. And he should have known that and he should have called a different play. He should have gone to line of scrimmage and gone, okay, they're playing at work.

Call something different. I know that. But he didn't do that because he didn't know that.

And so he ended up running 15 yards because he made a mistake. So he doesn't get credit for that. He should be penalized because he did it wrong.

And Tom Brady says, I know that because I've done this. This is the only thing I know. I know how to read defense.

And so the analyst doesn't know that. I don't know what play you were calling. I don't know what you're trying to do.

I can't tell. How am I supposed to evaluate that? And so I would say in terms of sports analytics, baseball, amazing.

Football, really hard. Basketball is a simple game. They didn't need it.

And then there's hockey. One of my friends is Megan Chica who's got a company called Staff Leads up in Canada. She is the guru of hockey stats.

She does provides hockey stats to most NHL teams, most hockey teams all over the world. She's a major company. She's a data analyst at the University of Toronto.

And I actually had her come to my campus. And she's a stats person. And my students, they're like every econ major everywhere.

They're learning econometrics and learning how to do stuff. And one of my students said, well, how would you do an analysis of hockey? Would you like use something in Stata, run a regression?

And her response was she looked at them and she didn't say it this way, but it was the body language, the way she said it. It almost came across as, it's so cute that you think that would work. That's adorable.

She was like, you could start with something like Stata. That's nice. And I'm like, well, what do you use?

We have advanced film work and we track the players across the ice and we have a massive data set. And even then we're like, there's some tendencies that sort of, it's kind of like that. Can you run a regression?

Of course not. That would be ridiculous. But it was so funny with the way she said it.

She had this look on her face like, well, that's just adorable.

[Dr. Shirin Mollah] (59:11 - 59:28)
So didn't you use a lot of the technology data in economics? That was my next question, how you just mentioned on the rink they have, there's more data even on football players that have it on their jersey, but do economists use that and can they use it?

[Dr. David Berri] (59:29 - 1:04:02)
I was given this by the Minnesota Lynx this last year. They now have data where they can track the nearest defender. So one of the issues that we had in basketball analysis is you actually couldn't know how well they did on defense because you don't have data on it.

There's no data on who exactly is the defender. I can look at it on a play-by-play basis and I can say, well, the center is being guarded by the center, but that's actually not true. They could be guarded by the center, but there's a lot of switching that goes on.

And so we actually got, they actually have data now where they can track the players and they can tell you this is the nearest defender. So when that shot went up, that was the defender. I know that.

And the FISA Collier was the player, defensive player of the year last year in Minnesota for the league. And when I looked at the data, the shooting efficiency against the FISA Collier when she was shooting nearest defender, she was the best in the league. So the perception people had that she was the best defender matched the data.

And so I was like, hey, that's really cool. So I incorporated that in measuring their productivity. It didn't change things terribly.

It almost came out to the same result because before that I treated defense as strictly a team variable. But I did now I had data on individuals. I could do it that way.

Now everything in the box court could be linked back to an individual and I could do that. And I was like, hey, that's great. And I did it.

And I got that result. Cheryl Reeve is the one who gave me the data. And what was interesting about a conversation I had with her about it is I was talking about some players and she was asked me to rank them.

And I said, well, you know, overall, it's this way. But I said, you gave me that defensive data and that one player, they're the best in that group. And her response was, they're not any good at defense.

So it's your data. You're the one who gave it to me. So I was like, okay, we don't even believe you.

Okay, that's fine. But so you can do that. You can track it.

There was a comment by Stan Van Gundy once where they told him that they're going to put trackers and shoes and tell you how much they run. And his response was, why the hell would I want to know that? I'm not watching a track meet.

I don't care how much you run. I'm not getting credit for that. Again, we're keeping score at the basket things, not the running thing.

What the hell is that? So there's a problem in data analytics in that a lot of times people are tracking data that doesn't tell them anything. It's not doing anything.

You have to know whether the data is good or bad. Are you telling me something I need to know? Or is it just noise?

And in basketball, there's a lot of noise. And I would imagine there's noise in football. One of the great things about football that I think makes it easier for the coaches is there's only like 60, 70 plays in a game.

They know what plays they call. They can grade it. The assistant coaches are grading every player in every play.

They know what I know what I told you to do. I can know whether you did it. And so therefore, they already know this.

They already, I already know how good the players are because I told them what I told them to do. And the fans are at home going, your defensive end doesn't have that many sacks. They're not that good.

And the coach is like, I didn't ask him to get sacks. I asked him to defend against the run and do this and this. And he did exactly what I told him to do.

So he's the best player I got. And you're like, but I don't see the stat. The stat doesn't mean anything.

I don't need that stat. I wanted to do these things. And so the analytics, you have to understand what information the coach has, whether or not it's possible for them to figure out the answer on their own.

I think in football, you probably could. Basketball, there's just too many possessions for you to know that. And the box score data does tell you the answer.

Baseball, again, back to baseball, they have data on every single pitch. It does tell them an awful lot of information. And so baseball works really well.

I'm trying to work with Megan Sheik on hockey. I'm going to meet with her again. We're trying to do a paper together.

She's going to have to explain to me what exactly she does, but I don't know if she can. She's got to use really small words and speak to me in very tiny words. So thank you so much, Dr. Barry.

[Dr. Shirin Mollah] (1:04:03 - 1:04:30)
And this was very insightful on your book on slaying the trolls was a, you know, it's a very good background and, you know, hope everyone reads it. Until next time, teammates, I'm Dr. Shroom below. And this is a sports economist.

If you enjoyed today's discussion, please be sure to subscribe and leave us a review. And don't forget to follow us on social media for more insights into the fascinating world of sports economics. Thanks for tuning in and we'll see you next time.