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Welcome, welcome to Wharton Moneyball. Welcome to a full hour of sports analytics here on the Wharton podcast
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network. This is Kate Massie hosting this week along with my longtime colleague, collaborator, co-host, and
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friend Eric Bradlo. Our two other co-hosts, Shane Jensen and Audi Winer, are out this week. They're doing Shane
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and Audie things. They will be back. Some combination of us are here almost every week of the year and have been for
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more than 11 years now. Delighted to be here with you. We are going to run through a regular schedule. We're going
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to record, we are recording on Tuesday afternoon. The show will go up on Wednesday. We're going to do about an
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hour. We're going to do a guest in the first half as we have been lately and
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then some open topics in the second half. We have back on the show for the eenth time and um a very happy annual
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marker of sorts. Aaron Shots is here with us which means football season is just around the corner. Delighted to see
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you Aaron Shots. Welcome back. >> Hey, we made it through another off seasonason. Football people any I I am
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aware there are other sports but football people made it through another offseason and I'm ready to go. I'm ready
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for a new season. I'm ready. training camps are open and I'm ready to uh
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completely get obsessed with whether guys throw interceptions to their teammates and pretend that it means
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something. >> Good. Good. Well, we appreciate the enthusiasm. That's what you're here for.
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Most of you guys know Aaron. If you don't, let me give you just a little bit
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of background. He is presently the chief analytics officer of FTN Fantasy. He also writes for ESPN. He's very well
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known for founding Football Outsiders. many years ago, more than 20 years ago, he was early into the game on advanced
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football analytics. He's the creator of DVOA, which has been doing a lot of work
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in our community for a long time. And um he's always a delight to talk to. I I
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always like to note also that he is the his his writing tree, his analysting tree is as impressive as it gets in
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football, if only that perhaps the two leading lights. He I give you credit for finding Bill Connley and Bill Barnwwell.
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If I think if you do word count right now, the leading word count producer on the NFL side for ESPN would be Barnwell
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and the leading word producer on the college football side of ESPN would be Connley. So Shots is the journalistic
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father of both of those guys. >> A lot of my writers in the past have turned out to be quite verbose. Uh Bill
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Connelly has a new book coming out by the way, so I hope you'll talk to him about that. It's really exciting. And uh
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yeah, my coaching tree includes Doug Ferrar from Athlon and Mike Taneer who has his own site now and Ryan Wilson
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from CBS, Michael David Smith from Pro Football Talk. It's a lot of people. >> You're forgetting FEI, I think.
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>> Yeah, Brian Frimo, who does the FBI ratings? Yep, >> exactly. Freo as well. That's a heck of
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a tree. Heck of a tree, Aaron. Okay, man. Let's get into it. This is uh NFL talk one for us and so God knows we're
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going to kill you with questions. I know you've got some stuff you want to talk
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about, too. I'm going to start at the top with a personal question. All right.
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I'm in a in a dangerous position this year. My favorite professional team is
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at the top of many people's list and my favorite college team is at the top of
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many people's list. It's uncomfortable. You'd rather be there than anywhere
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else, but it's a little uncomfortable. I need to know, Aaron. I need to know
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what's the case for the Ravens. We're used to them being like second, third,
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fourth on most people's list. There's usually somebody like the Chiefs or the
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Bills or the defending champion Eagles up. They're look looking up at them. But
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now everyone, it's ridiculous how many people are saying the Ravens are the best positioned in the league. Now I
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know there it's tight. >> You say Kate, there was a time. Was there not a time that the Bills were
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your favorite team? Like when I first met you almost 30 years ago now. >> Well, you spend a couple years in
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Buffalo and and you get you get soft for the Bills and they're still way high on
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the list for sure. But there I I discovered, Eric, last year, remember they played in the playoffs and it's
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like I didn't know what was going to happen internally when I went to know >> that's how you found out and it was
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clear to me. I'm sorry, dear Buffalo friends. It was clear to me that recent
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recency matters and it's the Ravens. So Aaron, I need to hear your thoughts on
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the Ravens for this year's NFL. >> Well, if anybody who follows my numbers
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knows that they have absolutely loved the Ravens for the last two years. Uh they have been our number one team for
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two straight years and number one in a historically great way like among the top 10 or 12 teams ever measured in the
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regular season and then they go to the playoffs and they fall on their faces. >> So the idea that the Ravens are the best
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team is based on the idea that falling on your faces in the playoffs is not a real thing. that history is filled with
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teams and players that couldn't do it in the playoffs until the year they finally
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did >> get it done. >> And certainly we know that there's no magic sauce that John Har uh John
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Harbaugh can't win in the playoffs because the man won a Super Bowl 13 years ago.
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>> Is there some sort of magic sauce that Lamar Jackson can't win in the playoffs?
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I honestly >> don't think so. Has he struggled so far? Yes. Does it mean he'll struggle
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forever? Just ask Pton Manning or Jason Tatum or Barry Bonds or a number of different athletes if you struggle in
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the playoffs for your entire career or maybe it just happens early and then you kind of get with it. Now, the downside
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for the Ravens is that they are desperately trying to get past the Kansas City hump,
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except they also have to get past another team that is also desperately trying to get past the Kansas City hump,
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right? >> Which is the Buffalo Bills. It's a really interesting table we have in the
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book. Mhm. >> The top DVOA average of a five-year team that doesn't make the Super Bowl belongs
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to the last five years of the Buffalo Bills. >> The second highest average belongs to
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the last five years of the Baltimore Ravens. So these are what great teams would say historically get past a hump
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>> over what period of time are we talking about? >> This is over the uh since 1978.
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>> Oh my gosh. The best 5ear spans since 1978 to not make a Super Bowl are the Bills and
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Ravens of the last five years. >> Yeah. And we just place that on Andy Reid's doorstep and and Pat Mahomes
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doorstep. Geez. Good lord. Okay. Well, tell us why it's different this year.
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Why would it be different this year for either of those teams? >> I mean, it's just a question of, you
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know, when is somebody gonna get it done and and when is Kansas City not gonna have the brakes work for them? And I
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mean, I think Kansas City is a very well coached, very well quarterback team, but
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I don't think that they're invincible. They did show a couple of years ago that
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if somebody could get past them because Cincinnati did. And I think that they're
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not going to have the same luck they had last year. I think they may be better than they were last year, but they're
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not going to have the same luck. So, they're not necessarily going to be the
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number one seed in the playoffs. I think the most likely team to be the number one seed is the Buffalo Bills because
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they have the easiest schedule out of those three AFC top teams, >> right? I mean, Ravens visit Buffalo week
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one and then they go to Kansas City first half of the year sometime as well. It's
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>> that week one game is hugely important for playoff seating. It >> you also pointed out um it doesn't have
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to be this is what I've always thought. It doesn't have to be the Bills or the
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Ravens that defeat the Chiefs. As far as I know, Kansas City goes to San Diego or the whatever Harbaugh team.
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The other >> Harbaugh Chargers, LA Chargers. Yeah. No, I mean, we think Denver is very good
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this year. We think Cincinnati is good. >> Absolutely. The Bengals beat them. The
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Bengals beat them and then the Ravens and Bills, one of them wins. That's what
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I think is actually going to happen this year. Also, uh, it's guaranteed that
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some team from the AFC South will make the playoffs. >> That's Yep. That's the way the NFL
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works. Sure enough. Um, well, remind me what we learned from the Super Bowl. If I don't misreall, the Eagles beat down
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the Chiefs. I mean, not just a little bit. So, tell me what we learned from that about getting past the Chiefs. uh
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that offensive line is a weak link unit. >> Say what you mean more. Say more about
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what you mean by that. >> The idea is that your offensive line is generally only as good as its weakest
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lake. >> And therefore you need to be good at every position. And the Chiefs had
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Caliando at left guard and they had Tuni playing out of position at left tackle.
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And the Eagles pass rush destroyed them. And the other thing we learned, Vic Vangio is a very good defensive
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coordinator. >> That Eagles defense from week six onwards would have been one of the top 10
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defenses since 1978 by DVOA if you if you take out the first four games of the year. That's how good that defense was
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last year. >> All right. Well, let's use that as a pivot to the hometown Philadelphia
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Eagles. Are people sleeping on them this year? I know they're roughly a a a top,
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you know, I don't know, five team or so in most people's expectations, but some
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think Detroit going to clip them this year. What What is your What does the air and shots take?
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>> I'm the opposite. I actually think the Eagles are not quite going to be as good
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as people think they are. They are, I mean, a very good team, but this is something we talk about a lot. Offense
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is more predictable and more consistent than defense. The Eagles had the number one defense in the league. It is very
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unlikely they will have the number one defense in the league again, especially because using the equation that I use to
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look at personnel changes, they lost the most veteran personnel of any defense in
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the NFL this off seasonason. Miami was second. So, with all the players they've
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lost, they're depending on a lot of young guys. They're probably not going
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to be number one on defense again. Their offense in the regular season was not as
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good as it was in the playoffs. So, let's say that they have a little bit better offense than last year. And like
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the fourth best defense in the league, they also have the second hardest projected schedule after the Giants.
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>> That is not a 13 uh win team. >> That's a 10 or 11 win team. >> Okay. Before we go on, I want to go back
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to the first thing you said there, which was that offense is more predictable yeartoear than is defense. This is kind
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of the can this is canon now, I suppose, for football analytics, but it's everybody may not know that because it's
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only been observed, I don't know, the last five or 10 years perhaps, but can
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you give us the intuition for that? Because I think most people might have the opposite intuition. Something about
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offense feels more volatile, so you might expect it to be less predictable. Why is it that season to season defense
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is less reliable, less consistent than a team's offense is? >> We don't.
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>> Is it Is it turnovers? Because that's one stat that they've said is very hard
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to predict from year to year. Is Is it that part of defense, Aaron, or is it some other part?
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>> Yeah, turnovers regress towards the mean strongly and stronger on defense than on
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offense. That is absolutely true. A big part of it is the quarterback position because so much of the offense is
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managed by one player, right? It's very hard to imagine that a team quarterbacked by Patrick Mahomes is
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going to have a below average offense. Yet, a defense with Miles Garrett as its best player can be one of the top three
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defenses in the league one year and one of the bottom three defenses in the league the next year, despite the fact
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that Miles Garrett is still awesome in both seasons. That quarterback having so much control over the offense leads to
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much more consistency. >> Super interesting. So, it's more about offense reliability as opposed to
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defensive unreliability. Super interesting. Okay, I want to come back to that. I know you you worry a lot
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about a hard thing in analytics, which is how do we forecast a quarterback when he moves positions, but let's hold that
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question for one second because we left the team previews one team too early. We
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were talking about Eagles and if you don't like them as one of the top teams,
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you might even like the Commanders better in the East. They are coming and they've got one of the most exciting, if
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not the the most exciting young quarterbacks in the league in Jaylen Daniels. What do you expect from them
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this year? Yeah, that's that's our big surprise projection this year. We
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project the Commanders over the Eagles to win the NFC East. That is not to say that the Eagles are not a great team. I
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think they'll be the number one wildcard team. >> Okay. >> Um the Commanders are going to not be as
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good on fourth down. They were shockingly good on fourth down. That is going to regress. But I think they have
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balanced that out with some of the additions they've made on the offensive side of the ball. Debo Samuel and
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especially Laramie Tonsel to improve their offensive line. We think their defense can be a little bit better than
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last year. They were actually 23rd on our defensive ratings last year. So, we have them projected average like 17
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>> and they have an easier schedule than the Eagles because of which teams in
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which divisions finished first and second last year >> and therefore we do actually have them
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projected ahead of the Eagles this year. >> Okay. >> So, Aaron, just two quick follow-ups to
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that. Um, a how much weight do you put? Um, I was at every Eagle playoff game this year. Um, the Eagles absolutely
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destroyed the Commanders in the playoffs. uh they ran through them. It I forget if they won by 30 or whatever the
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number was. How much weight does that put into anything? The second thing is the team that I didn't think the Eagles
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were much better than last year and got lucky to win. I was at that game too was
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the Rams. So where do you put the Rams? I mean Matt Stafford in that snowstorm, he was one pass away from them going to
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the Super Bowl. So I'm interested to hear, do you put any weight on the fact
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that the Eagles blew the Commanders out in the playoffs? And what do you think of the Rams?
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>> First of all, that's only two games. Let's say that there really is something
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about the way the Eagles play that the Commanders do not match up well with. There's still 15 other games that
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determine who wins the division. >> So, it could be >> predicting necessarily that they're
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going to beat them in the playoffs. You're talking about the division like >> Yes, I'm talking about the winning the
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division during the regular season. >> That's totally different. I agree.
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That's entirely different. >> And the Rams, we like the Rams. We do think their defense is going to take a
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step back. There's a lot of questions in the secondary. Um, their defense improved a lot last year and there's a
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sort of a plexiglass principle thing where they may come back to the pack a little bit. Uh, so we don't have the
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Rams. That's a very strong division. So, we also like the Cardinals this year and
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we also really like the 49ers this year and the Seahawks may be better than we think because their defense because Mike
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McDonald in Baltimore at least had his defense improve a lot in his second year there. So, that's a very strong
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division, but the Rams are a very strong team. >> Okay, let's let's talk QBs. Um Jaylen
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Daniels um after a spectacular year last year, it's it's you know because
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quarterbacks are so important to offense and offense is so important to a team. Understanding where a quarterback's
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going to be is the single most important component in forecasting a team. And yet
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especially early in a guy's career, it's hard to know what kind of steps he's
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going to take. What tell talk about Daniels? Like what do you see in Daniels? What do you expect in Daniels
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long term? What do you expect in Daniels this year? I mean, the best thing I can
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say about Daniels is that when a player is that good as a rookie, you don't expect that they'll take a step forward
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in year two because they were already so good as a rookie that they're not going
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to necessarily get better. >> Okay. >> Uh Marino was like the exception, but
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he's not necessarily going to get worse either. I think I mean he's really good
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last year. He's a great pocket passer and then he's an amazing scrambler. He's
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accurate. He's got a good clock in his head to not take sacks, right? You compare that to Caleb Williams. Now, the
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quarterback projection system that we use to try to project quarterbacks from college to the pros liked Caleb Williams
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better, but the fact is Caleb Williams just he made too much of his own pressure, took too many sacks, and
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didn't have anywhere near the kind of year that Jaden Daniels did. It's so
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hard to predict. Erin, tell me, talk about that because Caleb Williams, I mean, I would say I don't, we'd have to
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go through through the numbers, but he wasn't quite forecasted as a generational guy, but the consensus
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around him >> was he was number one, >> was so strong. I mean, I could just the
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consensus was as strong as it has been in many years. >> I agree with Aaron, by the way. I've
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seen both quarterbacks live, including JD Daniels first ever game, which was uh Commanders at Buccaneers, and the Bucks
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won the game. But I remember saying as I was leaving the stadium, "Thank the Lord the Bucks played them in
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week one. This guy's clock is amazing. This guy's accuracy. He's making the
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right reads." You a lot of times, as you know, Aaron, you go to games and you
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say, "This guy's open all over the field. What was the quarterback thinking?" I don't remember saying that
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once about Jaden Daniels during the game. I think I think you hit it on the head. I I don't know why that would
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regress. Why would his ability to find receivers and his I'll call it internal
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clock not holding on to the ball too long knowing when to run. I'm not sure why that would regress even though
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defense is quote unquote adjust. >> I mean the biggest reason why listen CJ
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Strad regressed a lot but he mostly regressed because the team around him he had injuries with his receivers and his
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offensive line completely fell apart. Washington has tried to make sure that does not happen by going out and getting
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the only good player from the Houston offensive line to improve themselves at left tackle, knocking last year's left
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tackle, Brandon Coleman, into left guard. So, they're hoping for a better blocking to make sure that that Daniels
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doesn't take the step back that Straoud took back. >> What What about Caleb Williams in
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Chicago? you know, expectations. It I I will say that as hard as it is to forecast a QB coming out of college, it
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seems to take us a number of years before we really understand a quarterback in the pros. We we get short
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on guys that end up turning it around at a second or third stop and we get long on guys that end up progressing three,
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four years into their career. What is your current position on Williams? What is your current forecast for having a
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>> I think he can be better. I think we may be making too much out of the new
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offensive lineman that Chicago got. They're gonna have better blocking, but the problem is still Caleb Williams as
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far as the pressure goes. It's not the offensive line. That being said, Ben Johnson is a very smart offensive
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coordinator. Now, head coach is a different job. We have no idea, none, how good Ben Johnson is at being a head
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coach, but part of his job is that he will be running the offense. That we know he's very good at. So, I mean, we
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do think Chicago in our projections, they come out as an above average offense this year.
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>> Okay. Okay. Well, we we've talked about projecting guys coming out of college
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and the challenge of that. Number one pick last year, Cam Ward going to be playing in the NFL for the first time.
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What hess in general? And then what do you see for Cam Ward? We like Cam Ward better than I
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think uh the consensus was that if Cam Ward had come out a year ago, he might have been the seventh quarterback taken.
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>> Yeah. Right. >> Our projections like him better than that. We have him more like third or
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fourth, like after Williams and Daniels. Um it, you know, it's based on the college performance. It's based on
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mobility in college. It's based a little bit on experience and a little bit on
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age. Now, the age thing is interesting because the change in how college is working means that age and experience
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may not mean the same things they've meant in the past. Guys are staying longer. The COVID year really
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complicated this, but now NIL complicates this. It used to be you'd see a guy was like 24 in college and
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you'd be like, "That guy is beating up on 18 and 19 year olds. How does that
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necessarily translate to the NFL?" Now, that guy is 24 in college, and a lot of
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the other players are going to be 24, too, because they're staying in college
00:21:08
because of the NIL money. So, overaged prospects may not be as overaged as we've thought in the past. Cam Ward is
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not, by the way. Cam Ward is still a young guy, but this was an issue with Daniels. This was an issue with Bo
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Nicks. This was an issue with Michael Penn, etc. >> So, Aaron, let me ask you, as someone
00:21:26
that does mathemat mathematical modeling, how do you then address that issue? I'm sure a lot of our listeners
00:21:33
like in some sense we've seen a regime change in the NFL where you know the age
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distribution has changed but like we can't just project from the past because
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we haven't seen that age distribution before how do you even think about addressing it from an analytical
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perspective or do you assumption do you assume that you look at the 24 year olds in the past and you
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try to project them forward what do you do >> I think early on like now you just do
00:22:01
your projection questions the way you've always done them and you just put words
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next to them. I mean, that's why we have words and not just tables in our book.
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You know, we explain when we think, you know, things are changing and and what it's going to mean now after we've seen
00:22:17
three or four years of this. We'll have to see. Wide receivers is another position where this comes into play.
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Like we've always found wide receivers who come out as juniors are just better
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in the pros than similar wide receivers who come out as seniors. They just are. But what if guys stay for senior years
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because they can make $2 million and get college checks? Like you know like what
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that it's not that they're staying till their senior year because they're not as
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good. It's they're staying till their senior year because they're making lots
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of money. So, it's going to change how we see things. >> So, is that just kind of the art of it?
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And yet, I know, you know, as modelers, we try not to put our thumbs on the scale, but you do put your thumbs on the
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scale when you know your model's missing something. >> I mean, we we all right, I I've heard
00:23:05
people talk about this. As much as we want to believe that our models are objective, the way you build your model
00:23:10
is in its way its own way sort of subjective. So, yeah, I mean, we try not to put our thumb on the scale, but we
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also want to be as true to life as possible. and life has changed. >> That's right. That's right. That's the
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humility of it really. Um you recognize that it's imperfect and you got to sometimes bring a little subjectivity.
00:23:30
We could talk quarterbacks all day long. I mean, another interesting one is JJ McCarthy. So, he's not I mean, he's not
00:23:35
a rookie, but he is a rookie. And what what is a year sitting on the sidelines? He's not even getting snaps, right,
00:23:39
because he's injured, but maybe that year of mental prep makes a difference.
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What what and the team is now completely dependent on him. What are your expectations for McCarthy? rejecting him
00:23:49
like a rookie. There's never been anything like this before. >> Mhm. >> You've never had a quarterback who
00:23:55
missed his entire first year because of injury. You've had guys who sat on the
00:24:00
bench for their first year, but you never had a guy who was supposed to start and then got hurt and so you don't
00:24:07
know what to expect from him. I mean, obviously there are guys who sat on the bench for a year and Patrick Mahomes in
00:24:12
his second year, right, was insane. But in general, I think we have to treat him like he's a rookie. And that's in
00:24:20
our projections. We treat him like he's a rookie. >> Okay. But you he came in in a strong QB
00:24:24
draft. If he'd come out a year later, if he'd come out in the Cam Ward 2025
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draft, >> he might have been the number one pick. >> He's he's that that's how high you have
00:24:32
him coming out of their >> I mean that it's more like people are not as excited about Cam Ward. Remember
00:24:38
Cam Ward, and this is another modern thing. He played for three different schools included including Incarnate
00:24:44
Ward, >> right? Like he he's kind of a late bloomer. >> Yeah. >> So I think that a lot of scouty type
00:24:53
people would have put McCarthy ahead of him. >> Okay. Okay. Okay. Another of these
00:24:59
challenges from a modeling perspective is when coaches change and a lot of us have tried to do coaching modeling and
00:25:05
and we've seen some efforts here and there. for a for a long time we just kind of
00:25:10
called the residual coaching effects. It's somewhere in the residual but it can't be the entire residual. What are
00:25:15
you doing with coaching these days? And when we see coaches move from one franchise to another what what can we
00:25:21
say? >> It's hard because you don't have a history of except for a guy like Fangio,
00:25:27
you don't have a history of, hey, he's coordinated 10 different defenses and
00:25:32
this is what's happened to them, right? You're usually with a coach who's on a
00:25:36
new team, your sample size of his past performance is either one or zero, right? Like we've never seen Ben Johnson
00:25:45
run a team. We've never seen Aaron Glenn run a team. We have seen Mike Vrabel run
00:25:51
a team, but only one team, only the Tennessee Titans. So, we know something about Mike Vrabel, but we don't
00:25:58
necessarily know what was those Titans players and what was Vrabel. Now, Vable is an interesting uh one to talk about
00:26:06
though because there's a flip of this which is there's no way to model like
00:26:10
really bad coaches. Like there's no numbers that say that Gerrod Mayo was completely in over his head even though
00:26:18
everybody says Gerrod Mayo was completely in over his head. So, it's possible that we are underplaying the
00:26:25
change in coaching, not because Rael is more important than we think he is, but because Mayo was so bad.
00:26:32
>> What if every Aaron ju just say, let me ask a question. What if every statistical model, what about if all of
00:26:38
your models, all the other models, Massie, Peabody, whatever it is, had the Patriots last year at seven and 10 and
00:26:46
they went three and whatever they went three and 14. Wouldn't that give some
00:26:51
suggestion? I I wouldn't say it's perfect, but wouldn't we have some
00:26:54
information that maybe Jared Mayo severely underperformed? >> Yeah, I think so. But here's an
00:27:01
interesting thing. Um, so I have an equation called the postgame win expectancy.
00:27:06
And what it does is it looks at the stats of a game and says based on the in the stats of this game, which team would
00:27:12
we have expected to win? >> I love And there are certain coaches who have a history of outperforming what
00:27:17
that equation says, like Mike Tomlin and Andy Reid. There's also a coach who has
00:27:23
a really amazing history of underplaying what the postgame win expectancy would say, and he's considered one of the best
00:27:32
coaches in the game. And that's Kyle Shanahan. >> Oh, I was going to guess Shawn McVey,
00:27:38
but okay. >> No, it's Kyle Shanahan. So, what if does that mean Kyle Shanahan's not a good co?
00:27:45
Right? Like there's a lot of measurements that you try to put into coaching, but I do think that if you
00:27:51
have a consistent record of winning close games and winning more games than your underlying stats would suggest,
00:27:57
it's probably a sign you're a good coach. And the opposite is also probably
00:28:01
true. But that's not true of the Patriots last year. The Patriots did not tremendously underperform the underlying
00:28:08
stats. The underlying stats were bad. Well, that's the thing. The coach gets
00:28:13
some responsibility for that fundamental, >> right? I mean, when you hear that like
00:28:17
Gerrod Mayo was not even aware of like which meetings he should be holding on which days, like you have to expect that
00:28:23
that impacted the underlying stats. >> Yeah. Yeah, that's right. But that is an
00:28:28
interesting that is one glimpse into coaching effects. It's not the whole picture and it's not perfect as you
00:28:34
said, but as you say, as soon as you get a somewhat sufficient sample size, it says something. It says something about
00:28:41
the coaching. >> Let me ask you, Aaron at all because I find this whole topic fascinating. Just
00:28:46
one quick followup to that. >> Do you find that the same stats help you predict, let's call it expected outcome
00:28:54
at different parts of the distribution? Like in other words, can I just have one
00:28:58
set of stats that would predict a really bad team's outcome, a good team's
00:29:02
outcome, and a great team's outcome or >> Yeah, I think it does. I mean I think
00:29:07
using the same stats it uses you know DVOA it looks at penalties it looks at how many plays you run right like DVOA
00:29:16
is more predictive which is an efficiency metric uh than how many plays you run but in a single game how many
00:29:23
plays you run is important right like you want to run more plays that's not necessarily predictive for future
00:29:29
performance but it helps you win that game but I think those underlying stats for like determining single games are
00:29:36
basically the same whether you're a really good team or a bad team. >> Let me ask you one other follow-up
00:29:40
question just for because we may have a big machine learning audience, blackbox audience out there. Um, when you think
00:29:47
about these models or even you and your disciples, it's it was great to hear
00:29:51
from you guys early on what your disciple tree is. Um, would you be happy today just building a machine learning
00:29:58
black box with, you know, kind of throw away whatever you know about the NFL and
00:30:02
whatever does best out of sample prediction, you're just going to jam it into some black box or do you see it as
00:30:06
a blend of the two? Like what do you feel most comfortable with? >> I would say a blend. I will say that the
00:30:14
uh the big data bowl a couple years ago when they did uh trying to predict the rushing yards on a play based on where
00:30:22
the players were, the winners were two dudes from Europe who knew nothing about football and just put everything into a
00:30:28
black box. So that was kind of interesting. I'm also I mean going to just be really honest here, which is I
00:30:33
am not a trained data scientist. Even though I've been doing this for over 20
00:30:37
years, I'm very self-taught. I have an economics degree. There was no such thing as a data science degree in the
00:30:43
mid1 1990s. The people who have come after me are much more adept at teaching machine learning to a computer than I
00:30:51
would be. But I love the answer though um because it highlights that there are different kinds of problems in sports,
00:30:59
never mind different kind of problem. There are even different kinds of problems within the NFL. So the example
00:31:05
you gave was a really cool year where they were predicting the yards from from at any given moment on a rush rushing
00:31:11
play like stop the action and say what's the expected yards from here. That's
00:31:15
very different from saying are the 49ers going to be any good in 2025 with the rushing yardage forecast. You've got not
00:31:24
infinite data but you've got a lot of data. You've got micros secondsonds as
00:31:28
your unit of of analysis and you've got as much videotape from history as you
00:31:32
can cram in essentially because there hasn't been that much change. That's a
00:31:36
good environment for blackbox models. When it comes to are the 49ers going to be any good in 2025, the unit of
00:31:43
analysis is essentially a season, a a team season and that's really chunky and
00:31:49
really coarse and we don't have much data. That's not great for blackbox
00:31:52
models. >> Yeah. I mean, I think there's a lot of subjective things when you look at
00:31:57
whether teams are going to be better or worse from year to year and things like trying to figure out which personnel
00:32:03
changes count and how to count them. >> Yeah. Right. Huge. And that's why I
00:32:08
think that's why we're going to be having these kinds of conversations for
00:32:10
the rest of our lives anyway. We're not going to have these things solved anytime soon. Okay, Erin, that's we've
00:32:16
already taken more time than we should. Let's ask one last question. Give us one
00:32:19
more storyline from 2025 NFL. one more storyline that you think is gonna be interesting, you're gonna have your eye
00:32:25
on as the season unfolds that you think we should pay attention to, too. >> And Kate, I'm gonna get one more
00:32:31
question in here that I really want to know the answer to, too. >> Okay. >> I'll mention, by the way, that all of
00:32:35
these projections and stuff, we do the preseason book we've done for 21 years.
00:32:39
So, I do want to point out to people the FTN football almanac 2025 is available on Amazon or a PDF version which costs a
00:32:47
little less. You can get at ftnfantasy.com/almanac. Uh, one of my interesting picks for this
00:32:55
year is that we like Jacksonville as our favorites in the AFC South. Partly for the same reason that we like Washington
00:33:04
in the NFC East, which is the Eagles were the number one defense in the league last year. It's very unlikely
00:33:11
they'll do that again. The Houston Texans were the number two defense in the league last year. Okay,
00:33:16
>> it's very unlikely we'll do that again. We like the Jaguars defense to improve a
00:33:21
little bit. We like the Jaguars offense to improve a little bit and we may be underelling what Liam can Cohen can do
00:33:28
with that offense if he's a very good head coach. But the big variable here is Travis
00:33:36
Hunter playing both ways, which is the most interesting story of the year as far as I'm concerned because it's it's
00:33:43
only been done a couple of times in the last 30 years. Roy Green had a year where he played both wide receiver and
00:33:50
safety. And Deion Sanders had a year where he played both wide receiver and cornerback. Nobody's ever tried to do it
00:33:56
to the extent that Travis Hunter has talked about doing it for multiple years. It's fascinating.
00:34:02
>> Okay. You did the whole Jack Jacksonville bit and didn't mention Trevor Lawrence. That's amazing.
00:34:06
>> Well, that's the thing is the question. Can Liam Cohen unlock Trevor Lawrence
00:34:10
like he unlocked Baker Mayfield? >> Okay, that's cool. That's good. That's
00:34:14
great. All right, Eric, you last question here. >> Yeah, I just wanted to ask him. So,
00:34:17
these are yes, no questions. We always say half the NFL teams that made the playoffs last year typically don't make
00:34:24
it this year. So, if I'll just list the quickly, you just tell me yes, no. Do
00:34:28
they make the playoffs? The Chiefs? >> Yes. >> The Bills? >> Yes.
00:34:33
>> The Ravens? >> Yes. >> The Texans? >> No. >> The Chargers?
00:34:39
>> No. >> The Steelers? >> No. The Broncos, >> yes. >> The Lions,
00:34:46
>> yes. >> Eagles, >> yes. >> Rams, >> yes. >> Buccaneers,
00:34:56
>> yes. >> Vikings, >> no. >> Commanders, >> yes. >> Packers,
00:35:03
>> yes. >> That's >> That's the whole field. That's the whole
00:35:07
field, man. >> That's great. >> All right, Eric, I just realized you're
00:35:10
wearing your Bucks colors. This you may intentionally not >> no this is an R this is not
00:35:14
>> Tampa Bay >> Mike Tir's chapter talks about Tampa Bay deserves more respect as a really good
00:35:21
team and not just as a team that gets to go because somebody from that division gets to go.
00:35:27
>> Okay, I'll believe that when I see it. But okay. >> And we love Baker Mayfield, let me tell
00:35:31
you. >> All right. >> We love Levante David. We love Levante David. >> Erin Shots, great to talk to you, man.
00:35:38
Great preview. Wish you the best. Fun time of year. Have fun for the next month as we ramp up.
00:35:43
>> Absolutely, man. I hope everybody enjoys the NFL season. ftnfantasy.com/almanac
00:35:49
to get the book. >> There you go. That has been Aaron Shots, formerly football outsiders, one of the
00:35:55
real pioneers in football analytics. Welcome back to Wharton Moneyball. Welcome to the second half of this
00:36:02
week's show. Kade Massie here, hosting with my longtime colleague, co-host Eric
00:36:06
Bradlo. We are gonna do the second half of the show as an open topics half number of things to talk about but we
00:36:14
just got off the line with Aaron Shots. Aaron is a frequent contributor here at Wharton Moneyball has been for all of
00:36:21
our 11 years I'd say and is good sign that NFL is upon us. Football is upon us. And he does a great preview. I think
00:36:27
Aaron does a fantastic preview. Super helpful, super insightful. Eric, any observations coming out or or let's say
00:36:33
anything left to say about the NFL here about a month out? No, I I like I loved what he said. I mean, he said that
00:36:39
offense is more persistent. Um, partially he said defense is less persistent because of turnovers. We've
00:36:46
talked about that. There's actually reversion, mean reversion that typically
00:36:50
happens in turnovers. Um, offense is more persistent because quarterbacks don't bo and weave that much. And so, I
00:36:58
thought that was a very good insight. And so what he basically said was is that if you have a team that was average
00:37:06
offensively but great defensively and like for example the Eagles and that's
00:37:11
what made them a great team. You'd have to forecast some sort of regression towards that. And I think that's the
00:37:19
thing I like about it too is, you know, it's in all the complex models and worlds we have now, that's something you
00:37:26
can explain to somebody and it it doesn't it doesn't it's not just empirically true, but it makes sense.
00:37:33
>> Yep. Um I found his team by team breakdowns helpful. It's interesting
00:37:39
that they're a little short on the Eagles. If you go to the markets, our friend Neil Payne sometime the last two
00:37:44
weeks summarized the market forecast like the probability of a team winning a Super Bowl. He got market forecasts from
00:37:50
two places, FanDuel and Poly Market. This interesting new market, Poly Market, the for the numbers are very
00:37:56
highly correlated. And you can look at what it says going into this year. We've
00:38:01
got five teams at like 10% or higher. No, four teams. Four teams 10% or higher. And that's more than we've had
00:38:09
in a few years. It's definitely more bunchy at the top. And despite Aaron's
00:38:13
take, the Eagles are the highest, at least on the poly market side, at about 12% chance of winning the Super Bowl.
00:38:21
>> Yeah. So, I love this bunchiness um that there's more teams at the top. Um I
00:38:26
could debate just because I was there and you know, again, this is a bias that I have. I think people are underelling
00:38:33
the Rams. Um, that was a damn good football team that came into Philadelphia and was one play away from
00:38:40
going to the Super Bowl. Um, they're not that low, you know, they're like the
00:38:44
seventh or eighth best team. >> Well, let's say what that is, but but as
00:38:47
a as a fraction, it is so much smaller. It's like 4% or something. Yeah. Yeah.
00:38:52
Yeah. >> Yeah. The other part that's interesting is a lot of that bunchiness, this is
00:38:55
what we talked about with Aaron, is the Chiefs, Bills, and the Ravens, and only one of them Super Bowl.
00:39:01
>> That's right. That's why the Eagles That's why the Eagles are popped up
00:39:04
above them because that market poly market understands that and they're they
00:39:08
just have less competition in their competition. >> Actually, you brought up a really
00:39:10
important point because not a novice, but someone that's not thinking about it
00:39:13
as carefully might say, "Well, of course that means the Eagles are the strongest
00:39:17
team." No, the Eagles are in a weaker division. They have really one serious
00:39:22
contender. Not that they don't have others, but the Lions I think people would consider in that top tier.
00:39:28
>> Yeah. in the AFC. I mean, there's a lot of teams. There's a lot of teams that
00:39:33
could be competitive and certainly the Ravens, Bills, and Chiefs. That big three,
00:39:37
>> you know, three versus two tier, three versus two top tier teams changes your
00:39:42
probability of going to the Super Bowl and winning dramatically. If you have one other top tier team, you have to
00:39:49
beat one. If you have three, depending on your break and the playoff uh seating, you may have to beat two. And
00:39:55
that's a big difference. Well, that that concentration is so high as well. So,
00:40:00
three AFC teams above 10% to win the whole thing and then nobody down until somewhere below four. So, it's just
00:40:08
heavily heavily weighted to the top. And and Aaron, maybe the most stunning thing
00:40:12
Aaron said was that since 1978, so almost 50 years worth of data, the the two highest five-year runs of DVOA,
00:40:21
which is his advanced analytics measure for quality of a football team, the two highest five-year runs without appearing
00:40:27
in a Super Bowl belong to the current Bills and Ravens in the last 47 years. It's absolutely stunning. That's because
00:40:35
Chiefs >> the last two years, you you might have a different opinion. I think it's hard to
00:40:38
argue. I'm not arguing with the outcome. The outcome was the outcome. >> I think it's hard to argue the Chiefs
00:40:43
were a better football team than the Ravens or Bills the last two years. I don't I'm happy to go back three, four,
00:40:49
five years and say that, but not the last two. And I don't expect I do not expect the Chiefs to be a better
00:40:55
football team. And let's even talk about Aaron also talked about postgame matchup
00:41:01
beating expectations. I think the Chiefs are going to excel at that. You even mentioned they got Andy
00:41:07
Reid. I mean, come on. That's worth a lot. I'm not saying John Harbaugh is not
00:41:12
a very good coach. I'm not saying um Sean uh why can't I think of his last
00:41:16
name? The Bills coach. >> Yeah, I never can do names either. Sean. >> Yeah. He's obviously a very good He's
00:41:23
obviously a very good coach, but he's not Andy Reid. And so I think the Chiefs
00:41:28
may be the third best team in the in the AFC. And I think right now I would put them as again since they still have Pat
00:41:35
Mahomes, they're still the favorite to make the Super Bowl. Why not? >> All right, so we got we got we started
00:41:40
our football previews a little bit early this year. We're going to we're going to
00:41:43
slow walk them in. We're going to stage them in over the next few weeks. We've
00:41:45
got a five weeks or so before we launch NFL. We've got some college football
00:41:49
previews coming up in future weeks. Eric, I know you're just back from your annual pilgrimage with your cousin and
00:41:56
the boys to the Hall of Fame inductions for baseball. How'd it go? What stood
00:42:02
out to you? >> Well, couple interesting things that I heard. First, um, Billy, there's only
00:42:09
eight, what was it, eight relievers that are in the Hall of Fame, full-time relievers. Billy Wagner's one of them.
00:42:18
Billy Wagner's right-handed. He broke his right arm as a kid, so learned to pitch left-handed. So, he's a
00:42:25
left-handed pitcher that made the Hall of Fame who's not left-handed. So, that
00:42:29
was one thing I thought was interesting. >> I'm sorry. I don't understand what
00:42:32
you're saying. You lost. >> He's right-handed. >> You mean pitches lefty?
00:42:37
>> He's right-handed outside of baseball, but he pitches he pitches with his left
00:42:41
hand. Okay, got it. >> That is correct. That's because he broke his arm as a youngster and couldn't
00:42:45
pitch with his right arm. >> Okay. Okay. That was one thing. The second thing is that um
00:42:53
Ichiro besides giving a hilarious speech um he had no hits until age 27. >> No major league baseball hits.
00:43:05
>> Correct. >> Yeah. Yeah. Yeah. Yeah. >> And they actually published a list. They
00:43:09
showed it actually up on the screen. I'll make it up. Like Tai Cobb had like
00:43:12
1,600. You know, there were 11 players that had a thousand of their 3,000 hits by the
00:43:18
time they hit that age six. Wow. >> And Icho had zero. >> And of course, his first 10 seasons
00:43:26
record, obviously, all 200 hit seasons, including his fourth year, we had set the all-time record of 262 hits in a
00:43:33
season. Um, he averaged 236 hits per season in his first 10 seasons. So, that's a lot. Let me just real real
00:43:41
quickly. 236 is is pushing one and a half a game. And how many at bats do these guys expect to
00:43:50
get? Not that many more than three. So, it's almost half of his at bats he's
00:43:53
getting hits. Maybe maybe they get four at bats. Maybe it's >> maybe it would have to be. And actually, I
00:44:02
have to look at his batting average after his first 10 seasons. I think his career batting average was 331. I'm just
00:44:08
doing it by recollection. I'm not sure, but it could very well have been between
00:44:12
340 and 350, which would be exactly your math. If he got, you know, four at bats
00:44:18
a game, 640 a season, and he got one and a half hits per game, that's hitting 350
00:44:24
out of four. Okay. So, that could very well be. He may have had a 350 lifetime batting average after 10 seasons.
00:44:30
>> What do you think his longest hitless streak was, but in games or or at bats?
00:44:38
Well, I mean, if he's basically hitting onethird of the time, then the probability of not getting a hit in a
00:44:46
game is uh well, he'd have to it's 2/3 to the fourth. So, 8 over 8 over 9 8
00:44:56
over 8110th probability. He doesn't get a hit in a game. So if you call that a
00:45:01
geometric distribution, his the expect I don't know 10 I don't know uh games
00:45:06
without a hit. I was going to say 10, but that seems way too high. >> That seems too high, right? The way you
00:45:12
just went through it, that seems too high to be more than 50%. >> It does seem way too high because
00:45:16
there's a 10% chance roughly that he won't, you know, 2/3* 2/3* 2/3 times
00:45:23
2/3, which is not hit, not hit, not hit, not hit. That's eight out of roughly
00:45:28
that's one10enth. If you put a geometric distribution on that, like I'm flipping
00:45:32
a one out of 10 coin. Um, oh, the waiting time. Yeah, the waiting. I I don't know. Maybe I'm computing the
00:45:40
distribution of the maximum wrong. That's probably what I'm doing. I'm just
00:45:43
probably thinking about the distribution of the maximum wrong. I don't know what
00:45:47
it is. >> Okay, let's stop. Let's stop the math now and give an intuition. Like six
00:45:50
games or so. >> Yeah, I'm going to say five or six games. >> Yeah, something like that. That's that's
00:45:54
extraordinary. Okay. Um, but I interrupted your Hall of Fame thing. >> No, no, no. The only other thing, the
00:46:01
only other thing I would say was that I also had forgotten when I looked at his stats how great a player Dave Parker
00:46:07
was. You know, he was close. Not I don't know. He had 20 over 2700 career hits. I
00:46:14
assumed his stats were much worse. And so I now have to wonder why he wasn't
00:46:20
potentially in the Hall of Fame earlier. Um because just because I maybe it was a
00:46:24
different era when people were voting and everything else like that, but I compare him to a lot of the players that
00:46:29
have gotten in recently and you know to me he was as good I saw them both. He was as good as Andre Dawson. He was as
00:46:35
good as Andre Dawson and you know he was as good as a lot of people that are currently in the Hall of Fame. So that
00:46:42
was the other thing that struck me. >> Eric, remind me remind me what was so
00:46:47
special about those Pirates teams back then with Willie Starel and Dave Parker like that. There's something that like
00:46:52
the fish that ate Pittsburgh or whatever the what was so crazy about what was going on with those guys. I forget what
00:46:56
was going on with those guys. >> Well, I think a bunch of it was just they were very interesting big time
00:47:02
personalities. I think that was part of it. Also, they just had an amazing, you know, an amazing pitching staff, amazing
00:47:09
hitting team, and it was also just, as you remember, Pittsburgh was title town back then, right? That was the Steelers
00:47:16
uh era. >> Don't remind me. Don't remind me. No, I'm just saying that was a big era for
00:47:21
the city of Pittsburgh. Um, and they were just I think um Pittsburgh again Dave Parker obviously just passed away
00:47:30
two months ago. His son spoke. It was he was just saying it was a team with a lot
00:47:34
of personality. >> Yeah. Fun. Fun. Okay. All right. Let's do a little bit of contemporary baseball
00:47:38
because your boy Judge just hit the IR or whatever they call it and DL whichever one it is. And meantime that
00:47:46
pesky catcher out of Seattle dinged a couple more. I think I'm liking my I think I'm liking my position on the on
00:47:52
the Raleigh versus Judge bet. >> Well, now all of a sudden you're looking
00:47:56
good. >> Hey, who's that? You could you had to factor in injuries. Judge is not exactly
00:48:01
injury robust. >> Yeah, of course Judge's injury was from throwing the ball. And so the
00:48:06
interesting part from the Yankees perspective, and you I forget if we talked about this last week or not,
00:48:11
>> if Judge can't throw, then Judge can't play the outfield, which means Judge has
00:48:15
to DH, which means you now put Stanton in the outfield because you you got to play Stanton. He's the second or third
00:48:22
best hitter on the Yankees, maybe fourth. So you got to play him. And so now you put him in the outfield and then
00:48:28
you get defensively much worse. So the they've got a lot of trouble. Um, I now
00:48:34
put it at at best. I think Raleigh has 40. I think Judge has 37. I may be wrong, but I think he has 37. Judge is
00:48:42
on the 10day injured list. If he comes back, I still like Judge, but not by much. He might be five behind by the
00:48:50
time it happens. And there'll be only 55. Actually, I I don't know how I can
00:48:54
say I like Judge. If he's five behind with 55 to play, his rate, well, it would have to be 0.1 more per game,
00:49:03
which means over 162, I'd have to think he's a 16 better home run hitter than
00:49:09
Raleigh, and that seems unlikely. >> It's a little strong, but on the >> on the on the other hand, these things
00:49:15
do seem to be chunky. So, there's a lot of chance there, just you might not expect it. Um, but I think Rley got to
00:49:23
40. I may have this wrong. I thought he got two in a row relatively quickly. I thought he was at 41, but perhaps
00:49:28
>> Oh, he could be. I just the last time I heard he was at 40. >> Okay, Eric, I want to give you some bits
00:49:34
and bobs from around sports. >> 41. >> All right. So, he did sneak out there a
00:49:38
little bit. Um, the things that have caught my eye are a little unusual. Maybe it's because it's the time of
00:49:44
year, but we're a little bit in a in a in a Eb in major sports, but some of the
00:49:49
interesting bits have been a little bit more businessy. We don't do a lot of
00:49:52
sports business here, but some of these are businesses. Some of them are stuff from women's professional leagues. So,
00:49:57
for example, I just saw, you know, the the the Euro the women's Euro finals was
00:50:02
this past weekend, and England won. We saw some headlines around that, but I just saw the TV numbers for that. And
00:50:09
the the the US numbers were the were a record for a women's soccer game. There's something like I'm missing the
00:50:16
exact same like 1.4 four 1.5 million viewers, which is a 50% increase apparently over the 2022 Women's World
00:50:24
Cup. And even the the the whole tournament, not just the final, but the whole tournament was averaging 458,000
00:50:30
or something like that, which is a 100% increase over 2022. And people are thinking that this is because the NWSL
00:50:38
has become so popular around here. And then those players go overseas and play in some of these um national tournaments
00:50:45
and their interest goes with them. But so how when you just like raw numbers, this is one thing we ought to do more of
00:50:52
Eric and I and I think we've been trying some in recent years is just to be calibrated on the number of eyeballs on
00:50:57
various sporting events because that's what drives revenue in sports. And so we
00:51:01
need to have some sense of what's a big event, what's not a big event. When you
00:51:04
hear 1.4 4 1.5 viewers and it peaked at like 1.9 for the women's Euro final in
00:51:10
the US. How does that strike you? >> First of all, I love women's soccer. I
00:51:18
love watching it. I love the game. Um, in some ways I can um not associate, but I can like watch the game and you know
00:51:27
identify more with it than the men's game which I can't identify with at all.
00:51:31
Um, the women's game I think is a beautiful game to watch. >> So, hold on. Let me Rick, let me jump in
00:51:36
on that. Um, my advisor used to say, he's a golfer. He used to say, I think we ought to all watch more
00:51:43
women's golf instead of men's golf because we can't really expect to do
00:51:47
what the men do, but our swings, if we if we tried to mimic the women's swing,
00:51:51
we'd be better off. >> I completely agree with that. And I I played golf this weekend. I need to
00:51:55
mimic something other than my own swing. But um you know I'm I'm surprised at
00:52:01
that number. I'm not surprised at 1.35 million. I'm surprised that it's a
00:52:05
record for women's soccer because you know if we think that there's I don't
00:52:09
knowund 100 million US households that's still only a and you know I don't know
00:52:14
how many TV viewing households there are. you know, I don't like I think the
00:52:19
average NHL game gets about that number and so and so it's not large compared to
00:52:26
other sports and premier games from other sports, but I'm glad to see that it's growing. And you're right, we are a
00:52:34
business show as well and the business of sports is generated by TV revenue. That's the business of sports. The
00:52:41
reason the NFL players get paid well, MLB players, etc. are the TV deals and packages. That's the primary source of
00:52:50
revenue. And I hope this trend continues. If you would asked me to guess what the highest ever
00:52:57
this game, I would have probably guessed the number around five to six million. >> Right. I definitely would have been
00:53:03
three or four. And you make a very good point. I mean, can you imagine that in the, you know, the US women's
00:53:07
championship in what was that 2000, the the the World Cup, 2000 against China, we had fewer than one and a half million
00:53:15
Americans watching that match. That's really surprising, but apparently apparently true. Um, but the increases
00:53:23
also the increase from the last Euro um championship are notable that that that we're jumping that high essentially
00:53:31
year-over-year or tournament over tournament. >> Yeah. Just to let you know I this is the
00:53:35
wonderful thing about large language models. So the average Major League Baseball viewership per game on Fox,
00:53:43
ESPN, TBS, the national networks is 1.84 million viewers. >> 1.84. So the average MLB
00:53:52
that's the average tele like all in a given night like all the games they're
00:53:57
all they're a on a random Wednesday night or whatever they're averaging 1.8.
00:54:01
That's probably better than I would have expected. >> And NFL, by the way, what's your guess
00:54:05
for the NFL? >> Oh, it's an entirely different thing. So, I know I just saw the stat. You see
00:54:10
variations on it, but like 72 of the highest 100 programs in 2024 were NFL games.
00:54:17
>> Yeah, it's 17.5 million >> for the average NFL game. Yeah, exactly.
00:54:22
Okay, Eric, what I think we're doing and we ought to do more of is basically the
00:54:26
analytics of sports business. So, we like analytics, right? I don't care that
00:54:30
much about business, but if we can make it more interesting analytically, but this is just fundamental calibration.
00:54:35
This is this is what drives dollars. It drives signings. It drives everything. So, just be calibrated. We we can keep
00:54:41
on trying to to be calibrated all. So, let me give you I don't have the numbers
00:54:45
on this. Actually, did while I'm asking you this question, Eric, do the research
00:54:49
on the average um TV audience for the WNBA game. Give us that. And then let me make the following observation. I just
00:54:57
learned this. So, we know that the new TV deal is coming for NBA, WNBA, and they're expecting a whopping um
00:55:05
increase. So, I think they're expecting something at two or $300 million. And
00:55:09
that's more than a two-fold increase. It's I'm I'm getting the numbers wrong.
00:55:14
It's a massive increase this coming season. And here's the interesting bit,
00:55:19
Eric, and this is what I just learned in the past week. Because players and agents have known that that's when the
00:55:25
new TV contract was going to come up. And because they've anticipated the numbers going much higher, no, everybody
00:55:31
has set their contracts to expire this off season. So essentially, unless you're on a rookie deal,
00:55:38
>> the entire the entire veteran crop of WNBA players is going to be up for free
00:55:44
agency this off season. So, you're we're going to see something in the WNBA we've
00:55:49
never seen before, which is a I don't know if it I think it's the majority of
00:55:54
players are going to be up for signing with whatever team. It's going to be a
00:55:58
super super interesting offseason. >> So, so if I had asked you to guess the
00:56:01
ratio of NBA to WNBA average viewer, what would be your guess on the ratio? I'm not even asking you for the number,
00:56:08
the ratio. >> Well, I'm not I don't walk around with high expectations for NBA audiences. My
00:56:16
sense is that they're down a fair bit and they keep on coming down. So I think
00:56:20
they may be as low as like 2 million or something. Um and so and I'm working to
00:56:25
the ratio, Eric. I have to do it this way with basketball, the women's basketball, I'm going to go in the high
00:56:33
six digits. And so I'm going to put it at about 3 to one. >> You're very well calibrated. You're not
00:56:39
off by much. You're you're off, but not by much. Men's is at 2.68 million.
00:56:44
higher than I thought. >> Women's is at 1.32. So it's two >> also higher than I thought.
00:56:48
>> But also but I'm saying though I mean if you would asked me I would have guessed
00:56:52
five or seven to one not just the NB WNBA. I would way overestimated the NBA. >> Yeah. Yeah. That No, I've been that's a
00:57:00
story over the last few years that just keeps on coming down and people are amazed at the valuations keep on going
00:57:05
up. No, but your point is is that you know the shirts that you and I both support that the women's shirts were pay
00:57:13
us the damn money we deserve. If the ratio is 2 to1 the salaries might be 100 to one, 50 to1, 25.
00:57:21
>> Yeah. Yeah. So that's that that's a that's a big topic and one we probably
00:57:25
ought to tackle. Whenever they get into those formal negotiations, we should talk about it because it's a really
00:57:29
interesting question. The biggest issue is the val the club franchise values are
00:57:34
really going up in the WNBA. That's where the owners are doing great on franchise values. Revenue is is moving
00:57:40
and it's about to move. It's about to move again this offseason, but it's not
00:57:44
anything like the changes in franchise values. >> No, but Eric, hold on, hold on, hold on.
00:57:49
This is the key point. Historically, >> professional athletes haven't participated in franchise increases.
00:57:55
They participate through revenue. And it's a whole it's a whole question of
00:57:59
whether they can get a part of franchise and that you that now we're talking
00:58:01
about are we talking about labor versus capital. So it's this interesting philosophical question.
00:58:06
>> No, no, I just loved your previous I I I appreciate it now even more than 30
00:58:11
seconds ago or two minutes ago when you said it like you'd be a fool to sign a
00:58:15
long-term WNBA contract right now. Why would you sign it now? I want my contract to be expiring. No, they that's
00:58:23
and everyone saw it and so it's just going to be this amazing offseason moment where it's it's like be a
00:58:28
free-for-all essentially resigning all these veteran players. All right, last one for you, Eric. And this is instead
00:58:34
of a a business question, I'm go back to statistics, but I'm going to stay in the
00:58:37
women's professional world. It's a little detail I saw in the bottom of this article. So, there's a young rookie
00:58:44
who just made her debut, a PGA debut at the Scottish Open this past week, Lahi Wde. Lahi W. She's done real well as an
00:58:50
amateur. She's done ridiculously well as an amateur, but this was her first um
00:58:55
professional tournament and it counts as a PGA tournament even though it's the
00:58:58
Scottish Open. She wins the dang thing. All right. So, that's great. We should
00:59:02
all keep an eye on Lahi W. And by the way, the the women's I think it's the
00:59:07
women's is it the US Open is this weekend? I think it's No, no, no. We've
00:59:10
already had the US Open. Is it the British Open? Essentially, the Europe there's a major this weekend and I'm
00:59:15
shame on me for not knowing exactly. I think that's coming up this weekend. But
00:59:18
here's the question. >> She just won Scottish. It's probably the British because they probably do what
00:59:22
the men do. Scottish than British, >> right? Okay. Here's my question for you.
00:59:26
I get your I want to hear you talk this one out loud. What do you think in the 75 years of the
00:59:32
LPGA? What's the longest streak of a new winner? What's the longest streak of new of
00:59:42
between a a winner repeating anybody repeating? What's the longest streak of
00:59:48
um not not first- time winners? I mean, just the longest streak of not having a repeat winner in 75 years of LPGA. And
00:59:56
I'm tell >> you're talking about a given person the distance between their first win and
01:00:00
second win. >> No. >> What are you referring to? >> I'm saying for anybody to repeat. So if
01:00:07
you know, so Lahi W. If she if she won five weeks from now, that would be a four-week streak of No. Well,
01:00:17
let's say four new winners and then Lahi Wins again. That would be a four-week
01:00:20
streak of there not being a repeat winner. >> Oh. Oh. What's the longest streak of
01:00:25
there not being a repeat winner? >> Yes. Yes. Yes. >> Oh. In the LPGA.
01:00:30
>> In the LPGA. This is a harder problem than I usually give you guys. So, let's
01:00:34
just talk about how what's your expectation. I'm going to tell you that they just hit their record mark in 75
01:00:41
years. and I would have had no idea how to think about how to calculate. I'll
01:00:45
give you the answer, but I first want to hear you talk about estimating. >> Don't give me the answer first. Let me
01:00:49
think tell you how I think about it. So, um I don't I would imagine this may be
01:00:55
this may already end me and doom me for too low a number. Um I doubt there's
01:01:00
been any year on the LPGA tour where there hasn't been someone that's won
01:01:06
twice. Now, if that's true, if that's true, I'm not saying it's true.
01:01:11
If that's true, then the number has to be less than the number of tournaments
01:01:15
in a year on the LPA LPGA tour. So what I'm computing the stat is the maximum
01:01:22
number of wins by a player in a given season. And if that number is two for every season, the maximum of your
01:01:33
statistic can't be more than about 25 or 27 or however number of tournaments
01:01:38
there are in a given year. So that's why I'm going to guess somewhere in the high
01:01:43
20s because I don't think there's been an LPGA season whether it's Nelly Corda,
01:01:47
Anukica Soren Stam, Nancy Lopez, Ro Jang or whoever the hottest golfer was in a given year. Somebody's won twice in that
01:01:57
year and therefore that's how I'm going to bound the maximum from above.
01:02:02
>> Well, that was my first thing I was going to say. You you didn't come up
01:02:04
with a real answer. You just bound it. So you're saying less less than that >> down from there a little But but it's
01:02:09
interesting to me how top down you went because usually we build things very very bottom up and you you just kind of
01:02:13
went cluji in the middle which is fine. It gave you a bound. >> I could do the other thing too.
01:02:17
>> Yeah. Let's try to go bottom up to come what? Let's give us a more precise
01:02:20
number underneath that bound. >> Well, if I went from the bottom up, let's just say there's someone let's say
01:02:26
a very good golfer has a 5% chance to win a given tournament. Right? So the expected weight time until the next win
01:02:34
is geometric with probability 0.05. So the expected number is 20 20 weeks 20 events it would take that's not the
01:02:43
distribution of the maximum number of weeks but I also have a large number of players I mean I could simulate this in
01:02:49
about two seconds and see what the answer is. Um >> but that's hold on let's say because
01:02:56
what you just did is really interesting. You said for a good player your expectation is that they might win every
01:03:02
20 tournaments or so, but then so but then we're talking about records, right? So we're like how what's the most
01:03:10
extreme? >> I know. >> And and we're also talking about multiple players and so it kind of those
01:03:15
go in different directions. >> Exactly. >> Multiple players are going to shorten
01:03:17
that but the maximum is going to lengthen it. >> Tell me the answer is something like 60
01:03:21
or something like that. >> No, no, no, no. Like look what you just did. For example,
01:03:24
>> I'm staying with my number. I'm staying my bottom up and top down seem to have
01:03:28
some sort of convergent validity and I'm going to stay with a number in the 20s
01:03:33
somewhere. >> Well, I want to I want to say again that you're you you you did a real simple
01:03:37
thing. You said one player, decent good player, 5% chance. I would expect that player to win every 20 tournaments. And
01:03:44
then I said, well, there are two other factors. One, we're not looking for the
01:03:47
expected. We're looking for that how what's the extreme version of that? The
01:03:50
max of that that pushes it longer. On the other hand, we've got more than one
01:03:54
player and so somebody's going to do it below their expectations. So that factor
01:03:58
goes the other way. You might say just kind of heristically since I've got factors going both directions, I'm going
01:04:03
to stand on 20. And had you done that, you'd have been shockingly close to the
01:04:08
answer. Their record as of this week, it may go longer. It's not done. It could
01:04:12
go longer. The record is 19. >> Yeah. So, but I also forget whether I was close or not close. I like well I
01:04:20
was I like the fact that the top down and the bottom up both led to or the upper bound and then the more granular
01:04:28
probabilistic led to similar answers. >> Well, cool. That was it's always fun for
01:04:33
me to hear you hardcore basian statistitians work through the way you think of these things and sometimes it's
01:04:39
very involved and sometimes it's heristic and I think both can be instructive. All right, why don't we end
01:04:43
it there? Eric enjoyed the visit. Thank you for being here. Thanks in absentia from our colleagues Shane Jensen, Ali
01:04:51
Winer. Thank you to the big boss Dion Simpkins for keeping the wheels on the track. We hope all is well today as you
01:04:57
are away doing doing Deion Simpkins things. Thank you guys for listening as well. Come back and join us next time
01:05:04
between now and then. Enjoy your sports. [Music]