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Welcome to Wharton Moneyball. Welcome to a full hour of sports analytics here on
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the Wharton podcast network. Kade Massie hosting with the whole crew. Eric Bradlo
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is here. Audi Winer is here. Sane. Jensen is here. Three of the four of us are on campus actually in offices almost
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as close as we were last week in studio. But we're back on Riverside coming to
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you Tuesday afternoon as we typically do. Show will go up on Wednesday. We are gonna kick things around this week. We
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are checking in with an old friend, maybe the original guest. OG has a different meaning in podcast world. The
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original guest, Neil Payne, might be the original guest for Wharton Moneyball. Neil is a frequent guest over the last
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11 plus years, but he was with us, probably the only guest we can name who was with us in the basement of the
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original building before the studio was built. Neil Payne was a Philadelphiaian at the time. He um has since moved to
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New York for a while and after that moved down to Arkansas all the while doing great sports
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analytics journalism and work and he's carried a water for a lot of different
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organizations. He's got a terrific um terrific uh I've just lost my word
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>> substack. >> Substack. He's got a terrific Substack almost daily. Neil will keep you posted
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in all kinds of interesting ways on sports analytics. And one of the reasons we reached out to Neil this week is
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because there are so many different topics we could talk about. It's hard to
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pick a guest and just choose one of them. Neil has range. Epstein would love Neil Payne because he's got range. He
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can talk about any sport. In fact, he talks about sports we may not be interested in talking about, but we're
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going to focus on any number of sports. NASCAR is what I'm referring to. Neil,
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we'll see if we can get to that. >> Sure. >> But what why don't we say hello to Neil?
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Neil, welcome to the show. Thanks for joining. Hey guys. Hey, it's great to be back.
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I'm excited to talk to the whole crew and uh yeah, just love hanging out with
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you guys. >> Well, we'll take time with you anytime. I think we had you in person about this
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time last year. You came through for maybe a conference, some little football, a little Shabbat. We did a
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bunch of things in that short little visit. I think this was about a year ago. So,
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>> yes, we did. >> We'll take you in any form we can get you. Glad to have a visit. Guys, Neil
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has written his Substack on any number of topics over the last couple weeks. We can just kind of pick and go. Why don't
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Why don't we pass around choice? Y'all choose which of the topics you want to
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hear Neil talk about and we'll see if we can cover four in the in the first half
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hour here. Shane Jensen, do you have one that you want to talk about with Neil? Did you have a chance to look at him
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with his I know Audi looked at a bunch. How about we get Audi the first choice. Audi, you looked at a bunch. Let's see
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what he comes up with. Audi's first. Well, I you know, I was reading all about the Rams and and I definitely was
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going to cue that one up, but I I definitely I just heard from Neil that he's got a new one, not even posted yet,
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on baseball war, and you know, I can't resist. So, why don't why don't I let
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Neil tick pick from those two. Yeah, I knew that was going to be catnip for you guys. So, this is a post that's going to
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come out uh the same day that the podcast drops, actually. So, it's it kind of works out that people can go
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look at it. But I saw Matt Kemp was one of the names on this new uh class of firsttime Hall of Fame ballot uh
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potential uh baseball hall of fame members. It's not a great group, you know, apologies to Cole Hamls. He's
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probably the best one on there. There's Ryan Brawn on there who has a lot of
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baggage. Matt Kemp, Howie Kendrick, you know, guys like that. So, like a lot of Hall of Good type of guys, guys that I
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have nostalgia for for that era of like around 2010 type of uh peak of guys, probably not Hall of Famers. Maybe you
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guys can argue with me on that. But the one that really >> So, you're saying my sons and I may be
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by ourselves in Coopertown. Like, there may be no active player voted on and maybe the veterans committee will put
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some people on, but >> Well, I think they'll add the remember these are just the newcomers. So there's
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some holdovers from previous years that are uh most likely going to get in. Uh so it's really just the um the
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newcomers, but Matt Kemp really jumped out to me because uh as you guys know uh you mentioned I lived in Philly. Uh I
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worked for Sports Reference Sean Foreman uh and and all the great folks there um
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out in Mount Ary and uh I remember very distinctly Matt Kemp being one of our like early war stars. So we had and I
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get into this in the piece about a little about the history of war, how it kind of came out of the a bunch of
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different streams crossing with like Bill James and Windshares and Pete Palmer with linear weights and uh
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Mitchell Lickman with like the super linear weights where he used uh you know fielding data and base running data and
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all that and uh Tango Tiger Tom Tango who now works for MLB. He kind of pulled together all of those and came up with a
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framework for war, which then you had a bunch of folks kind of go off and run and calculate it for themselves. You had
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Sean Smith who created Rally Monkey War, RAR, it doesn't the R doesn't stand for
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reference. It stands for rally monkey. Uh that he was one of the ones. And then Fangraphs had their own version. I think
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Dave Cameron was uh involved in David Appleman in making that. And so that's
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how we ended up with now we have this like multi-olar war world that we've been living in for a long time with the
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fan graphs and the baseball reference the dueling wars. But at the time Sean Smith's war was the one that we had at
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baseball reference and Matt Kemp had a 10 war season and I it always like sticks out of my mind like hey man he
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was a capital G guy that year. He had an awesome season, but that 10- war season
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only lasted for about 7 months because the very next spring uh in 2012, we recalculated war. Uh and uh I worked
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with Sean Foreman and uh you know, kind of we all consulted together to come up with just changes in how we would
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approach the ways that it was calculated, including very importantly putting defensive runs saved as the
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fielding metric instead of total zone rating. And that ended up tanking Matt Kemp's war by a couple of wins uh at
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that time. Uh and so now he is at eight war. So only if you were around, you know, the the younger folks just
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wouldn't understand the reality of Matt Kemp as a 10- war player. But uh if you
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were around at the time, you had that picture in your mind. I did at least. And then now you kind of look at it,
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you're like, uh, you know, not quite as good. And he wasn't the only one that
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got dinged. you know, Albert Pooh's had didn't hadn't had a 10 more season at
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baseball reference, but he did at that time and uh Adrien Beltree as well. So, there were some seasons that just kind
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of uniformly got changed by that. But the only one and and I don't think it really matters for Matt like Matt Kemp,
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he wasn't going to make the Hall of Fame whether he had 10 more that season or
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eight or whatever. >> Just to point out, just 10 considered like >> that's like an epic season 10. Well,
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yeah, 10 war. And I looked at this for the piece is that everyone who had 10 war as a batter at least in a season
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except for Al Rosen who had 10.3 war in 1953 and then he just fell off because of injuries. But every other player in
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that group is either in the Hall of Fame right now uh tracking to be in the Hall
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of Fame Hall of Fame. So we're talking about like Aaron Judge, have to mention
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him obligatory every episode. uh Mike Trout, uh Mookie Betts had a 10- war season or they were left out because of
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non-performance reasons. So Barry Bonds and uh A-Rod and Sammy Sosa had 10 more seasons. So that's your group. It's like
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pretty much there's I think 56 guys and of those 55 are either in the Hall of
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Fame will be or left out because they had a scandal. That's a so it is a meaningful barrier.
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>> Huge. Yes. >> Let me ask let me ask a question. I was actually I was going to ask the question
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about how rare a 10 more season is, but you've already kind of answered that.
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Let me ask a different question. Imagine I asked you or Audi or anyone else that
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thinks about war measures and said, "Look, I don't and it relates to what
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you just said about Matt Kemp, like I don't care if you get someone's war that
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accurately, whatever that means, if they have a one or two war, who cares? But I
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really care about getting it accurately, whatever that means, if they're eight
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and above, because then we're talking about the right tail, the distribution.
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These things has high predictive and importance value. Would people construct a different war measure if what mattered
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was getting it right quote unquote in the far right tail of the distribution than if they were trying to get a
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measure that was, you know, if you'd like, reflective of everybody along the
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distribution of war? >> That's a really great question. And I mean, I think uh uh this gets into also
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some of like, you know, true talent versus uh measured performance, like forward-looking talent versus backwards
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looking, giving you credit for what you did because like Matt Kemp, he was not a
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true talent 10 war player. He's probably not a true talent eight war player that
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year, honestly. But the the actions that he did had eight war worth of value as best we could measure it. So, I think
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that is maybe the distinction there of trying to kind of pinpoint like true talent versus what you the worth of what
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you did. But, it's a point well taken because you would think if we were designing a war that it should apply
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equally to an average player versus a superstar player just in the sense of like this is how much these particular
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actions are worth or or not worth uh on the field. But at the same time, yeah, there's huge error bars. And I think
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that's the main thing that I wanted people to walk away from the story with is, you know, there's so much of a
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culture now especially, and you know, I probably contributed to that, a lot of people have contributed to that of
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breaking down like, you know, decimal like fractional differences in war or whatever metric you want. Uh, but I
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think pro football reference and I think Bill James came up with this in baseball
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even the idea of approximate value. We need to keep that in mind for all these metrics because they are still at their
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core approximate like it doesn't matter that it has >> Would you be okay if I did the following
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and you're right you could translate my question into is the standard error of
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war constant across the war scale and it probably is not. Would you be okay if I
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wanted to build a bootstrap distribution of performance based on uh and then I could simulate a gazillion seasons and
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>> No, I would not. That's a different issue that has to do with predictive
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accuracy. >> No, I wasn't doing predictive accuracy. I >> know you're trying to So, the problem
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with the standard error of war, if if you want to call it that, right? So, it's not even it's
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>> I can call it that because it's the standard error of estimated war. I can
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call it that. >> No, but you can call it anything you want. But when you say standard error,
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we we statisticians think sampling variation is as the root of uncertainty as the root. Where is that coming from?
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The uncertainty is not I mean it can be when you do predictive that's that but
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these wars that we're talking about the common war Aaron's 10.1 Aaron judges
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10.1 Kemp's eight or whatever those are historical wars that's what he did on
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the field in the past we have bias these are bias meth problems they're not uncertainty they're bias problems no my
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standard error is coming from the fact that Aaron Judge I'll use what Neil said
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the true score model I did not observe Aaron Judge or Matt Kemp or Massie for let me finish my for 10,000
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observations. I I observed him for some number of finite number of plate appearances. That's a it's a sample of
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plate appearances. Any model observed score equals true score plus error is going to have measurement error. And I'm
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going to adjust war for that random sampling. That's what I was asking Neil about. Well, and I think that really
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gets into when you're talking about the defensive metrics because we can kind of
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work out the value of the offense. Although even that has philosophical questions of like we're using sort of an
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average weight for a single, an average weight for double or whatever when in fact those had different run values
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depending on the context of the situation and then you get into well should we use WPA or you know RE24 or
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whatever but then for the even if you're taking the standard sort of like hey
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we're using generalized values for these actions the defensive uh measurements
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have such uh I think error bars around them because They're ultimately trying
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to kind of measure a negative, measure the play that wasn't made or the runs
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that weren't scored. And so there's a lot of I think uh estimation error
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around that on defense particularly. So listen, I I got to jump in because Eric said something that has to get
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clarified. You're talking about a war that's estimating what what what Neil
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calls true talent. True talent is interesting. We can try to figure that out. We can try to measure that on some
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scale. But but most war values, particularly the the ones we look at in offense, are not trying to measure true
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talent. It's trying to trying to measure what you brought last year in the 650
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observations that I saw, not what you would do next year or what that's not what I'm saying actually. I'm saying
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something different, which is if you know, I'll be frequentist for a second,
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which is hard for me to do, but I'll try. Which is, you know, you observed this 650, but you could have observed a
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different 650. and had to observe that which is based obviously I'm going to
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condition on the observed data that I had and I could observe a different 650 and that would give me a different
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estimate of war. I'm literally talking about the sampling properties of the estimator of war, which is the standard
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frequentist way to think about standard errors. And so that's what I'm referring
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to. And I would guess that the standard error of war or war hat if you'd like is
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not constant along the scale. And that's what I was asking Neil about. But that
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that first I don't think we know the answer to that. I would guess that it's
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probably not. Um but secondly what you're doing is using a frequencies uh understanding of of standard error which
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imagines there's some theta an unknown theta and war is not an estimate of an
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unknown thing it's unknown to us because we don't know how to define it and and
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in defensive measure we get all lost >> it's a different so good by the way by
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the way I just to our listeners out there I completely agree with your premise but that's a different issue I
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would almost use the measurement term of there's a construct validity issue >> is we don't even know What is that thing
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that we're measuring? Exactly. >> I was saying if you could define it and
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if you could say there's a deterministic mapping between performance and that
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measure, then you can create a sampling based estimator of the uncertainty in that because there's a deterministic
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mapping and all I got to do is reshuffle the observations in some way. Hey fellas, we I think this is a very
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reasonable point to wrap on because you said there's a there's a construct issue
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here which is obvious to anybody listens to a single conversation with us about war. So this is one of the clear things
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we take away made salient from the first observation that Kim's got knocked from
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10 to 8. But Shane hasn't jumped in. Let's give Shane a word and then let's
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move to a different topic from Shane. Well, I guess you know since we're talking about things as a construct
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anyway, I I this kind of the judge discussion and u got me thinking with war of course historically we've thought
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about it like the fact that it's it's pinged or normed relative to replacement. I mean it makes sense for
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like roster construction and the building of a baseball team uh to do things that way. Okay. But when you talk
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about something like, you know, if you're trying to measure like the deviation of arian judge or something
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like that or the MVP conversation, I think it makes like something like more that's like, you know, like a war above
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like a average or something like that. I I don't think replacement's the right
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kind of quantile of the distribution or whatever to compare something like that to. And I think if we were doing some
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kind of relative to average baseball player, not only would that kind of just shift things, but I think it might kind
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of change the calculation a little bit, right? Because you'd have a different
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distribution of fielding and offense that you'd be comparing like standardizing relative to.
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>> So that's the question is like what would that do other than just rescale
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it? Because the rescaling alone wouldn't be interesting, but I but there may be
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other knock-on consequences. So you know for example um different positions might
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the gap between players and average might be different that >> or or or I don't know how the fielding
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models are like like does it it would change the pool that the field that like like the actual modeling components of
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it the pool of players over which you would estimate those models I think would change
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>> I want to >> because you're starting to talk about average price you talk about regular
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players so now you're just kind of you're almost conditioning on kind of
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starter like you know a different kind of type of player basically that you'll
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be kind of calculating these models of. >> Yeah. And the value uh I think first and
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foremost the value of sort of like the bulk of playing time would go down because you'd be compared to a zero of
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average. The whole thing the in fact in Tango's model the whole thing that uh
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differentiates wins above average versus wins above replacement is literally just
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playing time. it's giving you value for how much you played because ultimately
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uh his insight was that there is value to a very slightly below average player that plays a lot at a level above
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replacement. That's the entire point of war. But I think you're totally right,
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Shane, that for purposes of asking questions of like greatness, the the zero baseline point should not be the
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replacement level player because that player, we know they're not great. an average player is a lot better than a
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replacement level player, but we're talking wins above average would and they actually have this at baseball
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reference if you look at it. Of course, it still has Aaron Judge as the leader by a significant margin over Cal
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Raleigh, but uh it is sort of a more reasonable point for those conversations because ultimately wins above average is
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what you did to literally help win games for your team. The average team is 500 and whatever you add to that gives your
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team a winning record. But you could set that baseline point anywhere. You could
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say wins above all-star, wins above Hall of Famer, and most players would be drastically negative under that. But
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that could be a cool exercise like build your own replacement level. >> Eric's trying to jump in, Eric.
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>> No, I was just going to I I thought you wanted to change the topic. I was just
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raising my hand to change. >> I want to let you do that. I'm going to ask one. I'm always trying to get
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calibrated myself on these things and this is one of these things I am not calibrated on. You talked about the
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threshold of 10 war and we talked about when hopefully we don't talk about judges MVP over Rally, but let's just
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touch on that for a moment. Um, what was the war produced by those two players this year? I'm curious how close Raleigh
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got to 10. >> Well, a baseball reference judge was almost exactly 10. He was 9.7 and then
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Raleigh was 7.4. Now, that could open up. I know you guys have talked about this. You know, I have a whole can of
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worms where I think MVP is like a narrative storytelling award and that we should give credence to the the, you
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know, unprecedented historical nature of things in in ways that maybe aren't
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reflected by a stat. You >> mean Judge the first guy to win the batting title and hit over 50 home runs
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in 60 years? You are right, Neil. >> Yeah. No, that's exactly what I was
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talking about. I wasn't talking about demolishing the catcher record for home
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runs by more than a dozen. >> That sucks. or the switch hitter record either.
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>> Yeah, that too. Yeah. >> All right, guys. Let's go. Gradle, pick
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us a new thread from Neil's Substack or other writings. >> I will. So, I noticed this actually as I
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was preparing for the show today. It's in the rundown I put and Neil noticed
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this as well. So, two things struck me about the NBA right now. I know we're
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only roughly 15 games in, but first, OKC is 14-1 with a 15.5 differential. Now, that's, as we know, would break their
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last year's record, which broke the record for the highest point differential ever in the history of the
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NBA. But that's not what shocked me the most. The thing that shocked me the most
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is that there are five teams with a minus 10 plus on the record. And actually, I started to say to myself,
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first, you know, OKC is going to be playing those teams. you know, maybe OKC breaks the record this year of 73 and N
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on a historically set of bad teams. And two, I've just never seen a distribution
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like this. Now, it's early in the season, but I mean, if a bunch of teams end up with a minus 10 differential and
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OKC breaks the record by three or four points, I know running up the score on these bad teams. Wow. So, that was the
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thing that caught my eye. I know you have looked at this, so I wanted your thoughts on it. Yeah, you said you've
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never seen that before. That's because it's like literally never happened
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before. And that was something that I wrote about because I noticed the same exact thing where it's like, okay, see,
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they had this historic year last year. Uh, but we've been having historic points per game or net rating, whatever
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you want to measure it in, differential seasons in the NBA going back almost on like a yearly basis recently. Like the
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Celtics a couple years ago were in that conversation. Obviously, we had those uh
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Steph Curry, Kevin Durant uh Warrior teams before that, but we uh we've kind
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of had teams challenging this record. And last year, I noticed this as well because people were asking me, "Hey, do
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you think it's more that we have good teams or that we have a bunch of bad teams?" And so, I looked into it and
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when I did it last year, I found that yes, there was a slight effect of the really bad teams, but mostly it was just
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Washington. They were like the team that was uh substantially worse than the average for their slot. Cuz I looked at
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it by like, hey, what's the average differential for like the number one ranked team, the number two all the way
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down to number 30? The Wizards were way worse than the average number 30 over the past, I think since the the last
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expansion, so 05. But uh the the top teams were better than their averages. So I concluded that it's probably like
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the good teams are good with a little bit of bad teams are bad. This year though, it does seem like it's being
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driven mainly by the bad teams being really bad. And if you look at the distribution, you have this like
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ridiculous historical uh number of teams that are minus 10 or worse, like you mentioned, Eric. And then you have a lot
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of teams that are way better, especially the top three, Oklahoma City, Denver, and Houston.
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>> They would all break the record. >> They would break the record, right? And
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this is through uh I didn't compare uh full season from the past to the first
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13 games this year because that would kind of skew things. We were talking about sampling earlier that you're going
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to obviously have a wider distribution in a smaller sample of games than an 82 game per team sample. So I just looked
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at the first 13 games per team of other seasons. And even compared to that, this
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is a wildly different uh distribution. Much wider. the highest standard deviation of team points per game
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differential to start a season ever, at least since the the merger. I didn't
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look before the merger, but I think that that's telling uh that you have also one
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last thing, you have a weirdly good middle class of teams relative to how good the middle class usually is, and
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those teams are feeding as well on these really bad teams. So, it's going to
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completely distort what we think of as sort of the benchmarks for a good team. What regular season success means
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predictively for the playoffs when you get rid of the Wizards and and the Pacers and the Nets and the Pelicans and
00:23:01
Kings and all these really bad teams. And so, the NBA has had a legitimacy problem for its regular season for a
00:23:08
very long time. And this is, I think, probably shaping up to be the worst that I can remember in that regard where we
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know OKC is good, but like how good and relative to other playoff teams that some might be pacing themselves, some
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might be load managing, some might be injured, but getting better by the playoffs. We just don't know how good
00:23:29
these teams are relative to each other. And it's like this entire 82 game multimonth sample going into the
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playoffs is like I don't want to say completely worthless but like it's not
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giving us the signal that we're used to. I was going to ask a question related to
00:23:43
this. So as our resident both basian and probabilist theorist etc. Would you expect the distribution of let's say
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average point differential per game? Could I make an argument that the central limit theorem would apply
00:23:57
because it's shots and then of course it's games and it's averages of games
00:24:02
and the question reason I'm asking is if I don't know if Neil looked at this but
00:24:06
if I looked at the histogram of point differentials would it be approximately normally distributed or should it
00:24:11
conceptually therefore okay so if it is can we significance tests against that to see I
00:24:19
mean listen even one last part of the sentence could we score seasons on how non-normal they are and maybe this is
00:24:26
what Neil did and you know I I'm just asking you a question from a good idea
00:24:29
actually >> I'll just throw in I would guess that the true talent whatever your true
00:24:33
differential is on a neutral field or whatever you want to measure that is probably also normal doesn't have to be
00:24:38
but I would imagine it probably is it might have a spike in slab or something like that you know some tail marginal
00:24:45
tail probability giving you >> true talent in in in terms of the team quality or individual
00:24:51
>> team quality yeah team quality Okay, >> team quality. I mean, remember the teams
00:24:55
are a bunch of averages to start with, right? Um, but they don't have to. And
00:24:59
then, of course, the actual what actually transpires over the course of a season is probably normally distributed
00:25:04
conditional on your true talent. That's probably true as well. So, you're going
00:25:07
to you're going to get something that's approximately, but I think you're you're
00:25:11
your your your inquisitive look there, Kate, suggests that there's no reason
00:25:15
why true talent should be normally distributed, right? >> I just I don't think the individual
00:25:20
talent is normally distributed in the professional league. So that that's that
00:25:24
>> no no no not at all but but team if you look at sort of the distribution of the
00:25:28
winning percentages historically. >> So what you're saying a just for all our
00:25:31
listeners out there is that you're basically going to get a Gaussian a normal mixture of normals which will be
00:25:36
normal. But of course if if what Kate is suggesting by his expression is that the
00:25:42
distribution of team talent was skewed or multimodal then you're going to get a
00:25:45
non-normal mixture of normal. They provide a different distribution. That's right. But either way, I I I like this
00:25:52
idea of like let's do a significance test on the distribution of point differentials and maybe we could score
00:25:58
seasons by how non-normal they are or this we could look at the variance across seasons, look for patterns and
00:26:03
stuff. >> Great, great, great. But we are being geeky analysts here instead of asking
00:26:07
the practical question which is why why would it be that we have these tails this year?
00:26:13
Well, I think one of the reasons why is that you have like your usual tanking teams uh that are just like perma bad
00:26:20
and have been bad. I mentioned the Wizards. I mean, the Wizards just like, you know, they they have not really been
00:26:26
relevant in a while. You also have teams that I think, and I had an interesting conversation with someone, one of my
00:26:32
commenters about this, where they were like, well, did the Pelicans really like try to tank by getting worse? And I
00:26:38
looked at it and I was like, well, you know, they did bring in Jordan P, who might be like a one-man tank uh
00:26:44
operation himself. But I think they had this premise of, well, we won 49 games two years ago, won 21 last year, but
00:26:52
Zion Williamson was injured and like all of our guys kind of underperformed at the same time. So, we're just going to
00:26:58
kind of cross our fingers. We'll make a few uh superficial changes but then cross our fingers and hope that on the
00:27:04
other side we can kind of regress back to that 49 win mean. Now they just fired their coach Willie Green which indicates
00:27:11
that and and Zion has missed like half the season which indicates that they did not regret the mean they regressed
00:27:16
toward was the 21 win version not the 49 win version. Uh so you have a few teams
00:27:21
like that. Sacramento also in that group where it's almost like passive tanking
00:27:24
like they just made some bad moves and they've they had some success a few years ago which was rare for them and
00:27:31
then they misread that as being capable of being carried forward but they didn't
00:27:34
do enough to keep the momentum going and so instead they've just kind of like
00:27:38
slid into oblivion. Then I think the Indiana Pacers are really interesting because I think they're doing a version
00:27:44
of if you remember the 1997 9697 season in the NBA. David Robinson was hurt really early in the season for the San
00:27:52
Antonio Spurs. And so they just kind of did like an impromptu tank. This was a team that was like a perennial 50- win
00:27:59
conference finalist type of team for years, but they opportunistically decided like, hey, the Admiral's out.
00:28:06
We're not going to be uh worth anything anyway. I think it was Greg Papovich's
00:28:09
first year as coach as well. So, they were just like, "Let's do a situational
00:28:13
tank. We'll try to get as good of a draft pick as possible and then we'll
00:28:17
reload next year when he's healthy and we can kind of uh, you know, move forward that way."
00:28:21
>> You're going to tell us this got him Tim Duncan >> and it ended up getting them Tim Duncan.
00:28:25
They got very lucky in the draft as Celtics fans. Maybe you Shane could remember this. Uh but uh they they got
00:28:31
lucky in the lottery to be able to get Tim Duncan, but it was also very shrewd, which I think is the right way to do
00:28:37
tanking of not this like deliberate multi-year kill the fan base type of like we're just this malaise sets in,
00:28:44
but situationally if you're Indiana Tyres >> call that they call that the process.
00:28:48
>> The process. Yes, that's what we call it now. We've developed that for it. Uh
00:28:52
which, you know, that's a whole other thing we could open up. But I I like this Indiana approach of if you're going
00:28:57
to tank, Tyrus Hallebertton is out for the year and you're coming off this finals appearance, but it was a little
00:29:03
bit of a fluky finals appearance. They would be one of the weirder teams to have won even though they got to game
00:29:08
seven. Arguably, you know, should have or could have won that game if he doesn't get hurt, but they would
00:29:13
definitely be one of the more mold-breaking champion teams if they had won that. And so now they're just going
00:29:19
to be as bad as possible and be in the hunt for there's a number of good prospects in the draft next year and
00:29:26
then they'll get Hallebertton back and then they'll have another guy that's you
00:29:30
know poised to to make a difference coming up and they could be good again. But I think it's this confluence of like
00:29:36
you're getting to tanking from like multiple different uh possible ways that
00:29:40
are making them so bad. And then OKC, you know, we shouldn't downplay them and
00:29:44
say they're a product of uh of these bad teams. I mean, they're a really great
00:29:49
team. Uh Denver looks amazing as well. Houston with Kevin Durant, they they actually did make changes to improve
00:29:56
their team. Then you have other teams like San Antonio, Detroit, where they're
00:29:59
kind of emerging from they did do a tanking type of uh cycle, but now they've got the stars out of that and
00:30:06
they're moving forward uh with that. So, it's like the confluence of a bunch of
00:30:10
different like team timets syncing up at the same time in the league right now to
00:30:15
produce this crazy lopsided distribution of teams. >> All right. Well, um, Eric, do you want
00:30:20
to jump on this before we move? >> Yeah, I just had two follow-up questions
00:30:23
to that, Neil. So, when do we get to a point quickly that you would, uh, predict OKC may break the record of 73
00:30:30
wins? They're certainly at a pace right now above it. And given the number of
00:30:33
bad teams, um, you may you may get to that point. Um, and uh I don't remember
00:30:39
my second question, but that was my first one. Oh, I remember my second one. I'm going to give you OKC,
00:30:47
Denver, and Houston, and I'll take the rest of the league. How do you like that to win the finals?
00:30:56
Uh, I, you know, could I swap out uh Cleveland for Houston? At least those are in my model. Those are the top three
00:31:03
cuz they would have around a combined 60% chance. uh OKC, Cleveland, and Denver. But if you're giving me the
00:31:09
Rockets, I still probably take it because it would be about 55 45. >> Well, I know Audi's going to take the
00:31:14
field, but you're going to take OKC, Houston, and Cleveland. And all right, we're so good. We'll track this.
00:31:19
>> OKC is really carrying that probability, right? >> It's about them at kind of a really high
00:31:26
amount. That's all OKC based. Yeah, I think it's the majority OKC and then uh
00:31:33
Cleveland and Denver around double like low double digits in there. Um what was the first question? I forgot OKC break
00:31:39
the record. Can they get it to 73? >> Oh, so I think they need a little bit
00:31:43
more. So the they're projected in my model for about 65 wins right now. I think their overunder at FanDuel when I
00:31:49
looked at a couple days ago was like 65 and a half. So that tells me they need a
00:31:53
little bit more. But probably if they sustain this for another month, they would be like their over under at
00:31:57
FanDuel might be above 73 wins by then. >> Neil, I have one follow-up question. Um,
00:32:04
you know, we talk about owners on the show a fair bit and thinking broadly people appreciate more now than they
00:32:09
used to, how important owners are, but probably still don't appreciate how important owners are. Just observing the
00:32:14
Pelicans owner is the same as the Saints owner. Am I wrong to be judgy about that
00:32:19
particular ownership group? Well, in general, I think owners make a huge difference in the NBA and it it has
00:32:26
to do with like setting the culture, convincing players to come there, the management, uh, like it just filters
00:32:32
down from the top. So, I think we had always traditionally as analysts undervalued the importance of the owner
00:32:39
in general. In terms of that ownership group, I mean, it's tough to say when it
00:32:44
came to uh it probably they have been responsible for giving Zion such a long leash even when he's been out of shape,
00:32:51
even when he's been injured every single year and they've just kind of pinned all
00:32:55
their hopes on him rather than trying to think of like, okay, this Zion thing is
00:33:00
not working out for us and we might need to think about moving on. It's like that
00:33:04
lottery with Zion was a long time ago. like I was still at 538 and uh it was like pre- pandemic uh I want to say. So
00:33:12
that tells you like you can get it in your head that a certain player is like I don't know you fall in love with them
00:33:16
as a transformational talent and certainly when healthy Zion is that type of player but at a certain point you
00:33:23
have to kind of understand and recognize that he probably is never going to live
00:33:27
up to what you thought he was going to be and then uh move on >> yeah it's I think it's important to
00:33:35
recognize there's a reason for why this happens in basketball and it has to do
00:33:38
with the smallness of the team and the ability ability of a generational talent by himself to bring you to at
00:33:46
championship or near it. And because of that, an owner just thinks they could they don't they could just do it right
00:33:53
with and kind of get involved and put all your chips behind one or two players and tell them this is who we should be
00:33:59
drafting. And >> all we could do, Audi, is forecast who that generational talent was going to be
00:34:03
with certainty. We'd be all set, >> right? But, you know, they don't even
00:34:06
come along that much. So, I think you wouldn't see it in baseball because it's
00:34:10
such a damn big organization with with 26 on a roster and and 200 as a minor and football rosters are huge. No one
00:34:18
would have that. I mean, I shouldn't say no one. People have very big egos, but I
00:34:22
would imagine that that kind of hubris is ridiculous to try to imagine you can manage.
00:34:26
>> Well, this is really neat. I've never heard that before. And it's an
00:34:28
interaction between ownership hubris, which we know to be a thing, and structural differences across sports,
00:34:34
which we know to be a thing. I've just never thought about the interaction between those two things. I think it's a
00:34:38
really interesting observation. Why don't we wrap the first half there since
00:34:43
we've been so slow to work through Neil's production. We'll keep him
00:34:46
around. We'll do the second half with Neil, too. So, come back and join us after the break.
00:34:55
Welcome back. Welcome back to Wharton Moneyball. Welcome back to the second half of this week's show. talking sports
00:35:02
analytics as we always do as we have been for 11 and a half years now and I got the whole crew in here. Shane Jensen
00:35:07
is here. Audi Winer's here. Eric Bradler's here. This is Kade Massie. We
00:35:11
are talking with our guest Neil Payne. We like Neil so much. We're going to keep him around for the second half of
00:35:16
the show. Also, he's so dang prolific. We have to keep him around to work through his stuff. By the way, I just
00:35:22
realized I I was reading Barnwell this morning for the first time in a long time. He's another prolific guy, right?
00:35:27
When he decides to write something, he's going to write something. Those are long
00:35:30
pieces. super insightful, but really I thought Neil, y'all are kind of cousins
00:35:35
in in the way you do your work. I mean, you're great writers, but also good analysts and you're very prolific and um
00:35:42
I was thinking about you while I was reading this stuff. We um anyway, for what it's worth. All right.
00:35:46
>> Good company to be in. >> It's good company for sure. Okay. We
00:35:49
talked about two of Neil's recent pieces. We've talked about baseball and
00:35:54
basketball. Shane is going to pick a thread, then I'm going to pick a thread.
00:35:57
Shane, what do you got? Well, I wouldn't mind uh talking a little bit about the
00:36:02
recent article you read on or wrote on the Rams, I guess, and basically talking about how it seems like I I mean, you
00:36:08
could talk a little bit about the details. They're they're you know, they're kind of a the number one kind of
00:36:14
team in in the foot in football kind of in terms of at least balance defense and
00:36:18
offense. And it's kind of it's interesting to kind of I I mean I don't
00:36:21
disagree, but one of the kind of points you make I think in the article is that it's not only that they're the Rams are
00:36:27
good now relative to the rest of the 2025 NFL, but they're good kind of relative to past recent Rams kind of
00:36:33
McVey Vay Rams teams and I think about those some of some of those old like other Rams McVey teams where they had a
00:36:40
I feel like a lot more kind of talent skill kind of people like Donald and Cup and these types of players. So maybe
00:36:48
maybe talk a little bit about how how the Rams are doing it. How this Rams team is somehow better than those kind
00:36:53
those past teams. >> Yeah. Well, I thought it was really interesting. You know, the Rams uh they
00:36:58
were among the teams, you know, they went to the playoffs last year, almost knocked off the Eagles. A little scary
00:37:03
moment there. Uh at least speaking as a Philly fan. Uh and so, um, you know, they've kind of made this comeback, but
00:37:10
it's just kind of built on itself. Uh, and this year you make a really strong
00:37:14
case that they've been the best team in the NFL. They have the highest SRS simple rating system, which is just
00:37:20
schedule adjusted point differential in the league, especially after beating Seattle, who's number two in the simple
00:37:26
rating system. It was not like a super convincing win. it looked like it was going to be early on, but just uh you
00:37:32
know the fact that they have emerged as the the possible best team in the league
00:37:38
was something that I don't think people would have thought just a few years ago
00:37:41
because if you think about the early version of the McVey Rams, it was all about almost this like I called it like
00:37:48
a get-richqu scheme type of approach to team building, which was just like spend
00:37:53
a lot on stars, lock in your your bigname stars if you've got them, go out, get free agents, trade away all
00:38:00
your first round draft picks. They famously went, I think, seven straight years without a first round pick. And
00:38:06
ultimately, it was like a win now at any cost type of approach. And they went to
00:38:11
the Super Bowl. And then a few years later, after they uh traded from Goff to Stafford, they won the Super Bowl. And
00:38:18
that seemed like that was going to be it though. It was going to be like, okay, you pushed all your chips into the
00:38:23
middle, you won this big bet that you made, now the Bill has to come due. And you know, it was a nice run. And then I
00:38:28
think they went 5 and 12 the year after which was one of the biggest drop offs by a defending Super Bowl champion ever.
00:38:33
But it really defied the expectations that then they were able to kind of retool off of that. They didn't even um
00:38:40
rebuild. They just reloaded and they kept pushing forward. And so I was like digging into why that happened. Some of
00:38:47
it is Matthew Stafford has been awesome this season and he has been a very inconsistent quarterback over the years.
00:38:53
a lot of it. You know, when he was in Detroit, he had not that much supporting talent aside from Calvin Johnson to kind
00:39:00
of work with, but uh he has always in my mind early in his career, he had this reputation of being a guy that like the
00:39:07
itest like better than the stats. Uh and you'd think like he has Mahomes type
00:39:12
talent, but where's the where's the production? But he in LA he has kind of
00:39:17
evolved and especially this year he has been rightly considered one of the MVPs.
00:39:22
Puka Nakua helps as well. I did a little thing where I did a principal component
00:39:25
analysis. You guys will like this on a variety of different receiver stats trying to kind of compress them down
00:39:31
into two dimensions. One of which was like usage and one was efficiency. And that could be efficiency on like deep as
00:39:38
a deep threat or as like an underneath guy. But basically it's like how are you
00:39:42
doing your production and then how often does the team call on you as like a target share. And Puka showed up as
00:39:48
being one of the highest guys in terms of combining efficiency mixing both the attributes of an underneath guy and a
00:39:56
deep guy and then having one of the highest uh target shares I think just behind Jackson Smith injigba
00:40:04
uh on the season. And so, uh, I thought that that's like, okay, that's an
00:40:08
underrated part of Stafford. But then the main thing that I think separates this Rams team is that their defense has
00:40:15
been really good, which was not a hallmark of the early gooff, Todd Gurley, you know, that type of Rams
00:40:20
team. Even when they went to the Super Bowl, they were outclassed. Even though they had Aaron Donald, they were
00:40:25
outclassed by that Bellich Patriots defense in that Super Bowl. And it was this idea of like, well, if you're this
00:40:30
high-flying offensive team, sometimes defenses can just shut you down if you don't really have that other gear. But
00:40:36
they've been one of the best defensive teams in the league. And they've done it
00:40:40
almost entirely through like lower round draft picks, undrafted guys, guys that they got from other teams. Only two of
00:40:47
their defensive starters this year were players that they drafted themselves with a pick in the first two rounds. So
00:40:53
to me that's like conditional on them making this turnaround despite trading
00:40:58
away all those picks and spending all that money uh you know and not being kind of capped out. The only way they
00:41:03
were ever going to be able to make this pivot was Stafford finding the fountain of youth and then discovering a bunch of
00:41:08
unsung guys. I mean Puka Nua is also a fifth round draft pick and you look at that guy now in his production he's like
00:41:14
he's probably the best receiver in the league and you were able to get him at
00:41:16
at such a bargain. So, it's a testament to the scouting that they did, the coaching, the cap management, and you
00:41:23
got to get a little lucky to make to hit on so many guys, but it's really worked
00:41:26
out for them so far this year. And I'll just sorry again, I'll just add on top
00:41:30
of that one more thing just because you talked several about them kind of mortgaging their future and past drafts.
00:41:34
They actually now are a team with, I think, two draft pick. They have two first rounders. Yeah, they flipped it
00:41:39
and Atlanta's their their other pick. And Atlanta, that draft that draft slot's moving up the board as as we see
00:41:45
it is. and they also have some of the most cap space for next year. So they've
00:41:48
totally flipped that identity as being now they're kind of a balanced measured
00:41:53
we're being running this team responsibly type of operation. >> That it's interesting that they think
00:41:58
they have both gears. You know, most front offices have one gear or the other. And so that that's impressive,
00:42:03
but everything you said is impressive about the front office. And what I the main thing I'm taking away because I'm
00:42:08
kind of at a distance from this is I would have thought any story about the Rams would have centered around McVey,
00:42:14
but McVey is the offensive guy. And so for you to say the defense has been kind of a surprising and important part of
00:42:19
this is say oh well it's gonna I mean he affects the whole team but his real
00:42:24
caches on the offensive side of the ball. So it really puts more of the premium especially based on the player
00:42:28
acquisition that you've talked about on the front office. What else? >> And MC,
00:42:32
>> oh, I was just going to say McVey, uh, you know, one of his best qualities
00:42:36
seems to be as a manager. We've seen so many times that these guys that are really great tactician coordinators when
00:42:42
they become head coaches, they screw it up and they can't really get it right. I
00:42:46
mean, that's like the story of a lot of guys in the league. Even guys from McVeyy's own pipeline uh, have have done
00:42:51
that and certainly other coaches trees. Uh McVey seems to be really good at like
00:42:56
delegating to the right people, managing the team, and just running it as a professional operation, especially for
00:43:01
somebody so young. And he is shooting up the list. I was looking at the list of like career winning percentage. And it's
00:43:07
like, you know, he's I think top 30 in wins above average or wins above 500 uh
00:43:12
all time in NFL history at this point. So, it's sort of like pretty soon we're
00:43:16
going to look up and we're going to see it's Shawn McVey is not this like
00:43:20
babyfaced kid that we think of him as, but instead it's like, oh, he's like
00:43:23
literally one of the best coaches of all time. >> That's a neat stat you just quoted win
00:43:28
percentage, but you said wins above 500. So, that combines both rate and duration
00:43:33
essentially. >> Yeah, exactly. Yeah, it's like they have uh it's it's like our wins above average
00:43:37
that we were talking about in baseball, but for coaches um they have that at uh Pro Football Reference, which I think is
00:43:41
a really cool stat because like you said, you can't if you do winning percentage, you have to set some kind of
00:43:46
threshold and it's like how many games should be in that. So, it's a more
00:43:49
organic way to measure that. >> Awesome. Eric's trying to get in. Eric?
00:43:53
>> Yeah. So, football's an interesting construction in the playoffs. So, let me
00:43:58
ask you the following question, Neil. Right now, I think most predictions would have to have the Eagles as the one
00:44:04
seed besides strength of schedule remaining. Um, they also beat the Rams, which we could question. I mean, they
00:44:11
beat the Rams on a block field goal, but ignoring that they beat the Rams. If the Eagles played the Rams right now,
00:44:20
Eagles have home field, let's say, who would be favored in that game given what
00:44:25
you just said that the Rams, By the way, I looked at the It's interesting that I
00:44:29
I I saw what you were working on, but I had done some stuff independently. I mean, the Eagles, I understand you did
00:44:36
schedule adjusted point differential, which I think is great. Eagles are only 33. The Rams are plus 100 this year.
00:44:42
They're not even close. How much stronger are let's forget that the Eagles would get a buy. Let's imagine
00:44:49
they meet in the NFC Championship game like one versus two, but the Eagles are at home. Are the Rams that much be what
00:44:56
would be the line? What would be the win probability for the Rams in that game? >> Well, so I like to look if you're
00:45:02
talking about hypothetical uh lines, I like to look at Mike Buoy's inpredictable. I know you guys uh know
00:45:08
that site, but they have the sort of like generic points favored metric uh based on the lines from recent games.
00:45:14
And the Rams are a plus 6.3. The Eagles are plus 5.1. So if that was like a neutral site, the Rams would be like a
00:45:21
point and a half or one one point to one and a half point favorite. Uh but to your point, Eric, the the stats from
00:45:29
this season would not have it anywhere near that close. the the Rams would be massive favorites. But I think there's
00:45:33
an element of a little of what we're talking about in the NBA of this sort of
00:45:37
like teams pacing themselves. The Eagles haven't revealed their true talent this
00:45:41
season. It's only been half a season. We have to regress to their prior, you
00:45:46
know, all these things of like we know the Eagles, the Eagles seem to win every game and I watch all every Eagles game.
00:45:52
It's like some of the ugliest games possible. I know some of that is like the tush push and being able to just,
00:45:58
you know, you can grind out wins whenever you need to, especially on like closing drives and, you know, when
00:46:03
things are are tight, but the the stats like SRS and even all of our predictive metrics, they are geared toward blowing
00:46:11
teams out. They want to see you impress in your wins. And the Eagles have been highly unimpressive, but in a different
00:46:18
way than like maybe the Broncos, uh, who have also been highly unimpressive in their wins or the Chiefs last year where
00:46:24
theirs feel like a string of like fluky circumstances just repeatedly like they flipped heads 10 straight times and it
00:46:30
ca, you know, they called heads and it came up heads 10 straight times. With the Eagles, it does feel like almost the
00:46:34
coin is weighted. And maybe I'm biased in saying that, but it does feel like
00:46:38
they know they can play a particular style of game and win it if it gets to be close at the end. But the question
00:46:44
is, can you really rely on that 100%. And don't we need to see some level of
00:46:49
dominance at some point? I would love to see some amount of dominance. >> Yeah, for sure.
00:46:54
>> Start watching the Patriots, bro. >> I know. That's the crazy thing. Talk
00:46:58
about regressing, you know, to their prior though. >> The Patriots, it's like 2015 or
00:47:04
something like that in the in the AFC. >> It's remarkable. >> It is crazy.
00:47:08
>> It's an interesting interesting season. You know, the thing I was reading from
00:47:12
Barnwell was about the Chiefs actually, and they're sitting there at 500 right
00:47:15
now. He's like, "Do we count them out?" And so, he really makes cases both
00:47:18
directions on counting them out or not. And I'm in I I'm in a thinking I'm not
00:47:23
counting them out. Those >> No, I'm not counting them out. Better they better indie at KC. They better uh
00:47:28
Indie at I'd still put them above 50% to make the playoffs. Whether what happens
00:47:32
from there, I don't know. >> Well, for you know, anything can happen if you if you get if you get in there,
00:47:36
especially if you got somebody like Mahomes. All right, last thread. I'm gonna go to the Connor Baddard thread,
00:47:42
which is is this young supposed star, former number one pick, finally showing that he's going to be a great player.
00:47:49
So, I'm interested in Bedard in particular, but I'm let's do a little
00:47:52
hockey. We've done the other three major sports. Let's do the fourth. But I think
00:47:54
it generalizes to this question of when do we know a young player is going to be
00:47:59
or not be what we hope him to be. So, for example, JJ McCarthy with the Vikings right now. Pennix just goes out
00:48:05
with a knee injury. these young quarterbacks, there's always a question of how much do we need to see Sam
00:48:10
Darnold? I mean, we got we thought for years we had that one picked. So, this is an interesting question in general in
00:48:15
sports. So, Baddard, for those of you who don't know, number one pick, massive
00:48:20
attention. Blackhawks got him three drafts ago. And then, you know, we have another one right behind him. I I I
00:48:25
don't know if you wrote about it, but Celibbrini playing his first full season
00:48:29
with the Sharks. He was consensus number one. So when you get these consensus number ones, when do we know whether
00:48:35
they live up to it or not? >> Yeah. And that is uh something that is kind of pertinent across all the
00:48:40
different sports because we had one year where we had Bedard, we had Wimby in the
00:48:46
same like year. Uh a couple years earlier we had Trevor Lawrence. That was kind of the NFL version of that. These
00:48:52
like generational prospects. And then we had Caitlyn Clark in the um WNBA as well. So, it's like there's there's
00:48:58
number one picks and then there's like these people that get talked about generationally and that gets thrown
00:49:04
around way too much, I realize. But, it is it is true that like Wimi was being talked about on a totally different
00:49:10
level than even like Cooper Flag or someone like that. Like there's just this like there's a regular number one
00:49:16
pick and then there's transformational. And Connor Bernard was talked about as
00:49:19
being transformational as well, just because he had this combination of like the most ridiculous shot that you've
00:49:25
ever seen in your whole life, and then also this like awareness of of, you know, the trademark of every great
00:49:33
center in the in hockey of like knowing where everyone is, where the puck's going to be, who how to set up your
00:49:38
teammates and everything like that. Uh Baddard, you know, he's fine his first
00:49:42
couple years. Uh I I had kind of written things that were defending him because people were you know the people love to
00:49:49
start creeping in with the bus talk or the kind of hey maybe we overestimated. The only thing we love more than
00:49:54
building these people up is to then tear them down when they don't perform like
00:49:58
immediately at the level of like one of the best players in the league. Uh and so I had written about like hey calm
00:50:04
down. He's still one of the best uh young players like through age 20 of all
00:50:09
time. you know, maybe not quite as good as Crosby was at the same age, but like close or McDavid, but close to that. And
00:50:16
then this year, he has been one of the best players in the league, which is why I wrote this story because it's like
00:50:21
this breakout moment that I think you have to have within the first handful of seasons. I know it varies by sport, but
00:50:27
I talk about Trevor Lawrence. We have not seen that yet from him. And I think we would all have to agree that our
00:50:34
estimations of him being the next Pton Manning or, you know, someone like that or Andrew Luck, they're just not there.
00:50:41
Like we have to downgrade what we think the rest of his career is going to look like cuz he just hasn't, you know, quite
00:50:46
elevated himself to that level of like he he should be where in the rankings where Matthew Stafford is right now, you
00:50:53
know, if if he was that type of guy. Uh, and so it's always encouraging when we
00:50:57
see like Wimi at the near the top of the NBA rankings and Connor Baddard at the top of the hockey rankings because then
00:51:03
you can kind of say like, okay, we're probably right about these guys and their generational uh potential. And
00:51:10
when I looked at this for hockey especially, it seemed like probably by age 20 you need to have like this bump.
00:51:17
I looked at a number of other guys like Gretzky, McDavid, Crosby, Yarm, Yagger, Ovuchetkin, Mariel Lemieux. All those
00:51:24
guys, a couple of them had shown signs of it even before age 20, but they all had a bump in their performance at age
00:51:32
20. Now, you could still make the Hall of Fame without that, which I thought was kind of interesting. like the this
00:51:37
is truly the definition of like value above baseline Hall of Famer where it's
00:51:42
like uh if you're talking about being uh on that inner circle level, you really
00:51:49
need to produce uh one of the best seasons in the NHL, you know, for that season by age 20. If you don't do that,
00:51:57
you're probably just you your ceiling is probably just regular Hall of Famer,
00:52:01
which is like, "Oh, no. I'm only a normal Hall of Famer instead of an inner
00:52:06
circle hall of famer." But it does matter. It really does seem to matter. >> Interesting. Eric's trying to get in.
00:52:11
Eric, >> no. I was going to ask the question that Neil just said, which is are what are
00:52:14
you looking for? Are you looking for like an extraordinary peak performance year? like if you know uh if Connor
00:52:21
Bdard had three let's call them.95 distribution years before age 20 be like yeah he's targeting towards a regular
00:52:29
hall of famer he needs a one year or at least that's a like a real n you know
00:52:36
99th percentile year for you to project him as you're right generational talent.
00:52:41
So it's not it's not the summation you're looking for a peak performance.
00:52:45
Yeah, a little bit. Especially since like peak is kind of all you have when somebody's 20, you know, especially as
00:52:51
they kind of get toward that level of like the years in which we'd really expect them to have at least figured out
00:52:57
what it's like to be an NHL player. You give them a little grace in those first
00:53:01
few years and then it's like, okay, you've been here for a while. You know
00:53:04
what this is like. Now it's time to kind of take off and do that. And yeah, you're right about the percentiles
00:53:09
because it's like extraordinary claims require extraordinary evidence. And our
00:53:13
claim going in was that this guy is the next McDavid. And so you have to provide
00:53:18
extraordinary evidence of that. >> Neil, it strikes me that you're talking
00:53:23
about the sport where we see the youngest player on the full professional stage of the m of the four major sports.
00:53:29
So baseball is famously long pipeline. Football, they just get drafted later. They get thrown to the wolves mostly,
00:53:34
but they get drafted later. Basketball, they they mostly get drafted at a little
00:53:39
bit later age. these high school these these uh hockey players get drafted basically coming out of high school. A
00:53:45
lot of them go into some kind of development work. The team maintains their rights but they go to college and
00:53:48
they go to one of those smaller leagues. The very best players and this is my question like how did they develop Bard?
00:53:54
How quickly do they put them on the ice? Because it's kind of it's kind of um
00:53:58
striking to hear you say they got to do it by 20s. Like my god that guy's a kid.
00:54:02
>> I know. Yeah. It's it's a little like Olympic gymnast or something, right?
00:54:05
Like there's just so much younger. But I do think in some ways the the hockey
00:54:10
development pipeline is a little bit more accelerated like you were talking about. They uh often the best ones they
00:54:16
don't go to college. Instead they go through juniors and they kind of are playing up uh compared with their age
00:54:22
against players that are older or better or just kind of they're 16 and they're
00:54:27
going uh almost playing professional at that age. Uh and and it really kind of accelerates the development. And it's
00:54:34
similar to like in baseball, somebody can be drafted and in, you know, the summer and then like play in the major
00:54:40
leagues like that year. Uh in in baseball sometimes like we've seen this with pitchers. Um
00:54:47
>> rarely, right? Rarely. >> Yeah. Sometimes. Oh, well, if it's like
00:54:50
a Paul Ske, who I think is sort of also in that conversation as well. So, I I do
00:54:55
think that hockey kind of combines all the different elements that would cause you to see something at a younger age
00:55:00
than other sports like the accelerated pipeline, the ability to jump right in. And I'm really fascinated that the NHL,
00:55:07
you mentioned Mlin Celibbrini, Matthew Schaefer as well, he was the top pick for um the Islanders. He is now having
00:55:13
one of the best young seasons by a defenseman I think since Bobby our which really also says something. So, uh,
00:55:19
before the season in the NHL, I had done this thing where I looked at the fact that the average age of the league in
00:55:25
terms of just weighted by playing time or or player value had gone up for seven consecutive years, which uh was sort of
00:55:33
spoke to the stagnation of the league. We'd also had like the same finalists in
00:55:37
multiple seasons and all these things. And it was like when are we going to get this this change in in the hockey right
00:55:43
now? And it seems to have come this season led by Baddard, but also those other guys where you're seeing a
00:55:49
disproportionate number of the top players in the league in terms of like value over replacement or just scoring
00:55:55
uh be the younger stars. Now, it's like this next generation is finally taking
00:56:00
over the game. Now, that doesn't mean that Crosby is being pushed out. The Penguins have actually been amazing,
00:56:05
surprisingly, shockingly, this season. uh or McDavid, you know, he's still in
00:56:09
the prime of his career, but you've got these young guys kind of nipping at the
00:56:12
heels of the of the established players in a way that we really had not seen in a number of years in hockey.
00:56:18
>> All right, good fun. Well, listen, why don't we wrap it there? We managed
00:56:22
unintentionally to cover the four major North American sports in our four topics. Many, many thanks to Neil Payne.
00:56:28
Neil, you can find him. We can't recommend his substract strongly enough. which is fantastic writing, keeping you
00:56:33
as apprised and interesting uh across across the board in sports. We didn't get, for example, to your piece on
00:56:39
NASCAR, which I was mocking for, but I wanted to hear about because he talks about tournament design essentially a
00:56:44
thematic topic for us here over the years. We'll pick that up at some other point. For the whole crew, Eric Bradlo
00:56:50
for Shane Jensen, for Winer, this has been Kate Massie. Many thanks to Neil Payne, many thanks to Dion Simpkins, D
00:56:56
Patel, Mariss, Marissa Rena, the whole team. Many thanks to everybody and to you guys for listening. Come back and
00:57:02
join us next time. Between now and then, enjoy your sports.