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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 Kade Massie hosting today with the whole crew. Audi Winer is here, Eric Bradlo is here, Shane Jensen
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is here, and to add a little flavor, we are sitting in person in the Wharton podcast network studio. Our longtime
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home for years, our home for this show, and we're delighted to be not only in
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studio, but in person. something we only get to pull off, I don't know, once or
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twice a year for the last couple years since CO hit. It's been only once or twice a year. I would say we're looking
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out onto Penn's famous Locust Walk, but the studio is now kind of a video studio. So, we've got lights and the
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windows pulled and we could be anywhere really, but we have good sound, good video, and most importantly, we are all
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together. We are recording on Tuesday afternoon as we typically do. The show will go up on Wednesday. In this week's
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show, we are just gonna roll tape and talk about what caught our eye around the world of sports. We're gonna take
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advantage of being together and not have a guest, just find out where people are,
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what they're listening to, what they're paying attention to. >> Gentlemen, good to see you in person.
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>> Good to see you as well. How about that? >> It's been too long being uh kind of in
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the same physical space with each other. >> We, you know, we cross paths. We do
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every now and then see each other, but we don't get to record the show together. And in fact, Dion Simpkins,
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our longtime technical producer, associate producer of the show, is in house with us, which is also a delight.
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The whole crew is actually here. D Patel, the big boss. Aaron, the video producer. We've got more team members
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out there. It kind of takes a village, as D says, it takes a village surprisingly so to make this thing run.
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Gentlemen, where are we in the sports calendar? We are football season's getting mature.
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>> It feels like football weather out there. Certainly here in Philadelphia.
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Yeah. >> Phillyy's finally feeling like 12. >> I have to announce it's hot stove
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season. >> Oh gosh. >> Oh yeah. >> Which I just recently learned what what
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it refers to. It was it was the cold weather. Everyone would gather around a hot stove in the off season and talk
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baseball. >> Okay. >> And around and so we called hot stove season because there was no other
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sports. Historically baseball was the only substantive professional sport in America until about the 60s really. And
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then hot stove season was just what you do. gather around the hot stove in the cold winter months and talk baseball.
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>> You know, I I associate it with trades and front office transactions, but
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you're saying it's just like people >> anything that happens in the offseason
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is called the hot stove season. >> Okay. I haven't heard that phrase in a
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while. >> Where does Canada come from? Do you know that? Cuz that would that's a baseball
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one. I think it's like Yeah. Something I mean as far as these like you know, you
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know, I feel like >> so much of baseball's contributions to society sound like they came from like
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the 50s or something like that. But I think this is like >> 1950s. Yeah. But like I think this is one where it's
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like um I don't know. I I actually don't know. Somebody described to me it's like
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based on like you know how the stock boys used to like stalk the corn. It would fall off the sh like a can of corn
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and it's like kind of an easy fly ball or whatever. >> Yeah. Easy ground ball something easy
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that you know somehow it was based on like how the cans of corn fell off the I don't know. Somebody should look this up
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for us. >> Anyway, so I have my hot stove uh analyses to talk about. >> Oh. All right. Well, we let's just pitch
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it around and see where people are. Maybe we can do a few rounds of this. We'll go to the bottom of the hour, take
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a break, come back and wrap up with the second half of the show, but let's start
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off. Who's got something? Who's cut what's cut your eye in the world of
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sports? Audi W. >> I will I will do uh the the gold gloves came out. So, I don't need to dissect
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who won the gold glove here and there. That's all fun and but I want I want to
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get into that. What struck me is they're using now combination of analytics with
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basically the usual people's opinions. I think it's still 75% opinions and 25%
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the numbers. What numbers they use are outs above average and defensive run saves.
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>> Like is it is it kind of a public formula or is it kind of average out above average is not a public underlying
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formula. >> So you're saying it's not only 75 25 but of the 25 there are known weights
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component. >> Well and it depends on on the position. So catchers did not use outs above
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average they use a variety of pass ball saved. uh um runners caught above expectation, but it's the usual
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statistical stuff that's now really made its way into the Golden Glove um metric.
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So, I guess Derek Jeter probably would never have gotten one at the at, you know,
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>> the fans would have been so well. I mean, I get it 75% like humans still
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voting on it. He probably still Jeter outs above expected. My memory of the knock on his fielding was that he made
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easy plays look hard because he didn't have much range, >> right? So he he not only made easy pays
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look hard, >> uh he didn't have he wasn't prone for error. So he's can of corn he was fine
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with um he just didn't get to the center very well up the middle and this was
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before they would move the the player. So >> and the analytics would pick up on that
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now. Yes, >> they would recognize his limited range. I mean the average Shorstop would have
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gotten to that. >> Absolutely. I think he he was one that kind of he was an example. Mike L also
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in Boston I think was like this as well where he was very sure hand like he like
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on the plays where you saw him made he made an excellent play on. I see. He just didn't.
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>> It's just that there's this hidden denominator of plays that he couldn't
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make that he didn't, you know, wasn't two feet from in the factor and another
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player would have. >> Let me ask you a question then. >> Discretion is the better part of Valor.
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He's just living out the practical philos. So, let's assume he knows this at some
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level because he is a professional player. Did he for example, this would be a natural reaction. You move farther
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back on the field to give you more angle and you strengthen your arm. So that did
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he does anybody know cuz if I was talking to him those would be the things I know.
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>> I mean unfortunately he like you know I mean I I if if he played now we'd have
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the date on this and I because I mean he played most of his career kind of pre the big shifting crazy
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>> right way before the shift crazy. So which is interesting because today I
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still my reaction to a hard shot up the middle is a hit and I'm still not converted that to an out which is almost
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it's almost always an out now. It's it's it's it's terrifying because those were
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were hits. >> Let me ask another question. Do you know did the Yankees do whether it was
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cashman during most of that time did the Yankees do any I'll call it portfolio
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optimization which is look they can see that Jeter can't do that well moving to
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I guess his left get balls up the middle we got to get a second basement with range and maybe we'll trade that off for
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a little bit of >> back we we saw we saw what they they got a third they got a one of the best
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shorts stops in the field they actually traded for >> Yeah and they made him at third base
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>> but then they put him at third base I mean so they I mean they brought they
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actually brought in the personel how to correct the issue. >> You know, I'm not going to get all this,
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but Yankees were never known for particularly emphasizing fielding. So, what the other thing that I wanted to
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point out about the gold gloves now that they have these numbers, announce them.
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So, the the major one is outs above average, which is an MLB creation using their proprietary data, which knows
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where the fielders are standing at the time of the hit and how far exactly the trajectory of the ball. So, what they
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essentially calculate is the probability of an average player making that play and with what probability.
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>> Okay, but hold on. that doesn't give the player credit or debits for positioning.
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>> It does not. As far as I know, it does not. Okay? >> And this isn't this is a So, in other
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words, it doesn't do that. And that's a major concern. There's also I have other
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major concerns. For one thing, outfielders are all treated as in one bucket. So, outfielders are all the same
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in terms of their ability to to make plays. And so, center fielders are fantastic and right and left tend to be
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pretty weak because >> the center fields are much faster. So an average outfielder, some mixture of a
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corner outfield and center. >> And I assume they do that structurally on the other side of things cuz like you
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know if you know a particular outfield is like moving around the out like you know differentiate you have to be tough
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to kind of grade them. >> So I've actually dealt and played around with this model and it's hard to you
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can't reconstruct it yourself because I don't have the starting position of the
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player. Now we could do what what we used to do which was we never would take that into account and we would just what
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when Shane and I we wrote a paper years ago uh using much more coarse data. We just look at the trajectory of the ball
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and we would say what's the average probability or what's the distribution.
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>> So either positioning or range would kind of confound those two together.
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>> Well, let me build on Kad's point though, which is if I'm trying to
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evaluate a player, you could argue it's a combination of positioning plus range.
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The reason only reason I'd want to decompose it is if I want to improve the player or to possibly manage the player
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in some way. But from a pure evaluation point of view, I don't know that that
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confound matters. Well, before the team got involved with positioning, it didn't
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matter. But now it matters. >> The team does you can see them out there with
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>> the positioning. You can apply across any players, right? >> I didn't say it doesn't matter for
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improving team outcome. I said it might not matter for evaluation. Meaning if I'm a player and I illosition myself, I
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should get knocked for that as part of the total value of fielding >> back in the day. For sure.
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>> Yeah. Yeah. And I mean I I totally agree. I feel like even even now if you
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kind of wanted an omnibus idea of their fielding, it would be fine to confound those two together. That's my
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>> point. And it must be the case also that the team when it's choosing optimum
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positioning >> knows the range of the players. So now we've got another little wrinkle in
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there like even they're going to prescribe different ranges for different people. They should and they'll give the
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more talented players more range to cover. >> Yeah. This is by this is this is
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historical. I mean, if you look, um, the in the old days, the center fielder had
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a lot of stature. The the other corner outfielders would back off and he'd get
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all these extra plays because he was the the star. >> Is that right? >> And not not so much anymore. Now they
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work about work at much more collectively. I mean, this is a big big daily task of the analytic staff to tell
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their outfielders how to be positioned for every player on the opposition. Produc optimally position the center
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fielder without knowing the optimal center, >> right? They do this for all the and this
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is a major task of the of the staff that travels with the team to produce a report tell them where to stand not only
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where to stand I mean how to like find landmarks in the ballpark to help them find their spot because there's no grid
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right so they have to like say you have to be here by the way the coaches do this too I just found this out from
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>> yeah you can see them kind of shoeing people over >> they move them over and you have to find
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sight lines and you can do this really well at your home ballpark because you're used to it you have a much harder
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time at the away >> ball park you get any sense cuz we all know fielders reposition themselves
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based on the batter. Do we have any ability to know that batters have the ability to hit differentially depending
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on who's fielding? Do we have any knowledge of whether they're able to? >> So, this is a big deal. Most most people
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would say no. We'd have to bring in a player or a coach to to tell us that some of the absolute best players were
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able to do that. It was no question um that the tremendous hitters of yester year were had that ability. I mean, one
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tool I think that even current players are underutilizing is the bunt. I would like to see the bunt make a big comeback
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because I do feel like >> you like an article. >> I mean, no, I mean, you know, you can
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personalize the bunt strategy, you know, if you wanted to. Manny Ramirez isn't
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doing it or something like that. But no, I mean, I I when I was over in Japan watching baseball games, bunting is just
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a way bigger part of the game because they it's I think there's more of a
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focus just on kind of run generation and stuff like that and and moving people over and stuff like that. But it's also
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like I I think against some of these more extreme shifts, I mean, you can kind of see if if if you could just put
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a a bunt down the third baseline, often the third baseman's like, you know, halfway to second or something like
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that. It's like an easy if if you can execute that. Yeah. >> Then it's basically an Let me get to my
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my point. They have this thing called outs above average. >> And what struck me is they calculate
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this. It's all relative to your predict position, but the outfield is thought of
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as one position. What struck me as the the Gold Glove leaders at the corner out outfields are smaller than centerfield
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and smaller than and centerfield is about the same size as shortstop. But I'm going to ask a question. How many
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outs above average do you think the gold glove winners are are making or earning
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whatever the statistics per what? >> It's over the course of the season. It's
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not on a per basis. It's outs above average. I'm not sure what the magnitude
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is, but I bet you it's about a quarter of what the you like the the top 10% fielder is about a quarter like away
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like in terms of runs I think adding to his team compared to hitting. >> All right. So
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>> that that would be my I'm giving you a relative you're you're on the right
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ballpark but what and I was actually struck by it. I thought I'll give you my
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hint. I thought it was fairly low. >> Um I thought fielding would matter. >> Yeah. What do you think out? So, it's
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outs above average AC across the season. Okay. >> For which which group that
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>> So, start with center field. Center I'll give you a hint. Centerfield and
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shortstop are about the same. And the leaders are um the center fielders are uh uh Armstrong um what's his name? Um
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Peter Armstrong um what's his last name? Uh >> PR Prow. >> Pico Armstrong. He was he he won the
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gold glove in center. Um Bobby Witer didn't win it, but he was right up there
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second. I mean, roughly I'm expecting this to be two standard deviations or something. I mean, just
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>> Well, it's remember it's it's it's it's not a rate stat. It's it's a total stat.
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>> Yeah. So, I'm going to guess >> I mean, you can just throw out numbers.
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I can just tell you. We can end our suspense. >> My my initial guess was some total outs,
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right? >> Total outs above average. >> I was going to guess somewhere around
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eight. Eight to 10 >> over a season. >> I'll tell you why I came up with that
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number. So, this is just bad math, but but it's rough math. Give us No, I'm
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going to tell you how I thought about it. So there's 27 outs in a game. Y okay
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let's pret. It's a bad assumption. Let's just say you uniformly distribute that
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amongst the nine players. That means each player makes three outs, >> which is not true.
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>> I didn't say it was true. And now I'm thinking of a percentage of that number
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of outs that I think they're going to make an incremental play. And then when
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they do make one, how many outs do they actually save in terms of a probability or expectation? That was the calculation
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that got me to somewhere around 8 to 10. >> All right. So, corner outfield. That's
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exactly right. The leaders corner outfield uh short stop. Uh no, sorry. Corner outfield, first base are right around
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that mark. Nine, eight, eight to 10. >> Out, uh center fielders are 20 to 24 and
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short stops around the same amount. >> By the way, they get more. It's
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fascinating. That was my upper bound. I would have I was thinking my two numbers
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were in 8 to 10 or in the low 20s. >> Good job. Good job. What what I was talking about is like, you know, you
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take like like the 90th percentile fielder versus the median fielder. That difference, I think, is about a quarter
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what the difference would be for the 90th hitter versus the I think fielding is maybe like a good way of thinking. We
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can work it out. So, so here's the problem. How do you convert outs into runs and then runs we convert into wins?
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The usual number for runs into runs into war would be 10. 10 runs above replacement, but these are outs above
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average. But anyway, but Fielding is roughly is fine. We don't have this this
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I think the average replacement. >> By the way, this is the wonderful thing
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about this show for 11 plus years is that I know in the instantaneous second I had to think about it. I was thinking
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about that route. The problem is I didn't know how to compute go outs to runs runs to war. I could have asked you
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and you would have told me. I didn't know how to do that first step. So I abandoned that route just cuz I don't
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know how to do that. >> The thing is I don't never thought about outs to runs. So, I'm just kind of
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guessing that an outs to runs is something like a quarter maybe of of each out is about a quarter.
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>> Well, we know the following, Audi. We know how many runs are scored in a game,
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which is about four and a half, right? And so, 27 outs. So, maybe it's about
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0.15. >> So, that's that. So, the thing is an extra out. It all depends on where it is
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in the inning, right? So, the first outro, >> yeah, you're doing if you want to do a
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context, I would go for 0.15. 0.15. And so if you do that then you then you're
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20 times point you're you're not looking at very many runs. What are we looking
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at? We're looking at five tops. No less than that. Three to four runs. We're
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looking at we're looking at about not even a third of a win >> and added by the best fielder seemed
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low. Yeah, that does seem low because again like you know I'm thinking of like
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you know somebody like the best heel hitters are giving you like say like six wins above replacement or something like
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that. >> This was a very long critique of their criteria >> but not their defensive war. Their
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defensive war is typically around two, right? >> Yeah. No, I'm kind of like I'm saying
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like somebody like you know like like let's assume it's almost all offensive
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at the same the best would be like this is above average. So average is effectively the
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me the middle and war is above the replacement. >> But I think your logic is like for
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fielding at least >> replacement but no but I think replacement fielders are average close
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up to average. But you this is a long way of saying you don't love the sophistication of their defensive
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metric. Okay fine. Let me add some more superficial evaluations to this. I somewhere in my social media feed in the
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last couple weeks I saw a clip on Greg Maddox as a fielder. >> Y'all know these things. I don't know
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these things. 14 gold gloves or something. >> 14 gold gloves as a fielder and they
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they were showing highlights of him fielding and he was like wildly athletic as a pitcher making all these plays. It
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was really spectacular. I had no idea. I don't think of Maddox as seeming like
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that athletic of a guy, but apparently >> you might also think not necessarily
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correlate, but someone that's wildly athletic might be able to pitch more than 90 miles an hour. But but I'm
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saying it turns out there might not be I mean >> well >> I'm just saying you would think he
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therefore might have pitched harder than >> I don't Well, he's an averagesized guy.
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Maybe he's a great athlete with an average size. >> Pedro and Pedro threw real hard.
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>> Right. By the way, on this topic, who are some of the canonical great center
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fielders from a defensive perspective? >> Andrew Jones kind of when I was sort of
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paying attention in the early 2000s, I think was like that. Andrew Jones, Andrew Jones, especially moving in
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>> ridiculous. >> Well, we talking about historically like Willie Mays was thought of as one of the
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great center fielders. >> Is that not because of the one catch? I mean, there were other things that he
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did. I mean that's I you know we that's very so salient. So that's the first
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verse I come up with. >> But who else? Just give me >> without a question.
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>> Was considered also extraordinarily uh graceful. He made things look incredibly
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easy. Okay. >> Um >> Ken Griffy >> Ken um and when he was in the original
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>> Well, Trout was a great centerfielder when he first came up. And >> Jim Edmonds was also great early career.
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>> Yeah, Jim Edmonds was really great. >> I don't even know Jim Edmonds.
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>> Paul Blair was the name I was thinking. >> Paul Blair was crazy. I remember. Who
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did Edmonds and Blair play? Well, Edwards played for the Cardinals mostly >> and Angels for part of his career and
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Paul Blair played for the Yankees like Yankees 2000 to 2015. I guess >> I think there was a time between a
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little earlier maybe between grad school and arriving here. I didn't pay attention to baseball in grad school. My
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adviser George Woo had me paying some attention to baseball and when I got here I got around you guys. I started
00:18:30
paying attention again. But I think there was like a 12 year window where I didn't Okay, let's that's a good one.
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Odd, but let's keep going. Who's got another caught your eye? Shane Jensen.
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Well, uh, I guess I I should talk about the fact that the Patriots are eight and
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two. >> Well, just a surp We do we do have to talk about we we've been putting it off
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because we've been keep saying, "Oh, they're not they haven't been playing
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any good teams. They haven't been doing and now they they finally mean they played two good teams now. Um, and
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they've won it both." So, and they beat the entire NFC South this season. Isn't
00:19:00
that fun? >> That's >> And the two teams they beat, by the way, they beat on the road.
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>> Yeah. >> So, that is not easy. They beat the Bills and the Bucks both on the road.
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>> Although, hold on a second. Hasn't homefield advantage become a lesser
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thing over the years? >> It has become a lesser thing. The gamblers have pointed this out that it's
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just monotonically decreased over the last 10 15 years. And it used to be three points. Everyone thought it was
00:19:21
three points and then we started thinking maybe it's 2.25 but actually it's lower than that. It's less than two
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is the there obviously is differential home field advantage. I know it's not
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that much. >> No, a differential home field advantage is overrated, >> right? No, but I was going to ask very
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little predictive value. Well, what I was going to ask was if you for worse teams, is it harder for them? Like for
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example, the fact that the Patriots have won two road games against two really strong teams. Is that worth more than
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let's say a weaker team going on the road? >> Yeah. In our conversation is that a
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worse team would struggle more on the road. >> Correct. >> I think or at least that's kind of the
00:20:01
hypothesis. >> Why I'm not following this for some reason. What's the hypothesis
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>> that to the extent that there is heterogeneity in terms across teams in
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terms of how they would play on the road that a worse teams would be >> you talking about interaction between
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being on the road and quality? I don't think that exists. No. >> Do you think I mean you would agree that
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an intera like a weather stadium interaction exists or something like that that or a stad a weather home team
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interaction exists? >> Uh there that's been studied and there may be some. It's not as much as you
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think. There's an east coast, west coast thing and there's a division thing and
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this is something that jumps out to me like the Dolphins beat the Bills this time.
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>> Yeah, >> it's surely the case. I think that I know that home field is less for
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division games, >> which is interesting. >> Is it because they travel less on
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average? >> No, but I think it's because they just every every year they're there. Um, and
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that's not the case at all. This is football. This is football. But I wonder
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if there's not more than that. If it's more than just homefield, like in
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general, power rankings matter less among division rivals. >> Yeah. >> Does anybody know, did you look how much
00:21:04
did the Pats go up in the power rankings? My guess is not a lot for winning this game.
00:21:08
>> I haven't actually checked as of yesterday, but but before this one in
00:21:12
the Bucks game, I was marveling that they were kind of they were in like still like around the median basically
00:21:17
and they had the for a while there up until last week FBI had I think the Giants above the Patriots.
00:21:22
>> The Giants were above the Patriots. We talked about this on the show. But
00:21:24
again, the New York Giants are talking above the New York Giants. Correct. We're above FBI, I think, has a big
00:21:31
correction for strength of schedule, which the pads do have again on where they need.
00:21:35
>> I don't know if FBI FBI is not the end all be all, but historically it's been
00:21:39
decent, but they are right now number four in FBI >> and they've moved a lot.
00:21:43
>> So, they might have moved a lot, but they're sitting. Let me just review
00:21:45
these for you because it is interesting and and it's hard for me to keep track
00:21:49
of the NFL this year. It just seems wonky. Eagles number one, Rams, Colts, Pats, Colts, Pats, three, four, Seahawks
00:21:56
five. The three the middle three, four, five is Colts, Pats, Seahawks. Then Lions, Bills, Bucks. Those not
00:22:02
surprising, but Colts, Pat, Seahawks. >> That's very throwback power rank.
00:22:05
>> And by the way, you still you still haven't mentioned the Chiefs. >> The Chiefs are below that.
00:22:12
I don't care who they're going to be much better. >> I don't care where they are in the power
00:22:14
rankings. They're going to be in the AFC Championship. >> Well, that's a different matter. And if
00:22:17
you want to talk about it, I did run a sim off of unabated and I used inpredictables power rankings which are
00:22:24
marketbased and they decay and they estimate the decay optimal for predictive power. So
00:22:29
>> supposed quarterback and all that other stuff. >> So and injured quarterbacks and this is
00:22:33
this is so this is marketbased power rankings run through the unabated sim which has a lot of
00:22:38
>> question. You're just going to tell us the results. >> Well, let's do some questions. That's a
00:22:41
good idea. Who do you who do you think's top in both conferences for winning the
00:22:46
conference? And what do you think the what do you think the highest Super Bowl probability is here after what is it 10
00:22:53
weeks of play? >> I think it's probably the Chiefs. I think I'm cheating because I think I saw
00:22:57
that they're still the Super Bowl favorites on most of the >> They are top AFC.
00:23:02
>> They are top AFC. I was going to say that's >> but not the Super Bowl faves at this
00:23:06
point. >> Oh, is it the Eagles? >> Eagles number one right now. So, but oh,
00:23:10
I just told you the numbers. So, it's 13.8% 14% likely to win the Super Bowl
00:23:16
is tops. The Rams, another NFC team, >> is right behind them at 12. >> And what I'm a little surprised by is
00:23:23
that they're given, you know, between the two, they're given half the probability of winning the NFC. So, does
00:23:28
that how does that feel? The Eagles and Rams 50, who do you want, Eagles and Rams or the rest of the NFC to make the
00:23:34
Super Bowl? >> Oh, to make the Super Bowl? >> To make the Super Bowl. Eagles and Rams
00:23:39
or everybody else? >> I think there's I think I would probably take the Eagles and the Rams because the
00:23:45
only other teams that I think are highly highly competitive in the NFC. I think the Lions definitely have to be
00:23:51
considered a serious threat. >> Yeah. >> Other than that, I don't see any
00:23:55
>> The Bucks I think can belong in that conversation. I mean, with a little bit
00:23:58
more health, you know. >> Well, that's >> I mean I mean I don't know. I I I guess
00:24:01
an optimistic view of the Bucks would have them in that conversation. If you're telling me that by the end of the
00:24:06
season, >> Mike Evans, Chris Godwin, >> Bucky Irving, all of their and they've
00:24:12
got Igbuka who's turned out is going to be the rookie of the year probably. If
00:24:15
they have all of that offensive power, then they have an opportunity, but they're not better than those other
00:24:21
three teams. >> And I think I I might be with Eric. I think I might. Rams Eagles, I think I
00:24:25
might. >> Okay. So, the model gives them 47% total. So, it's about >> I was going to go with the with the
00:24:31
field only because I love the field. >> We always bet. always make a field. So
00:24:35
just cuz I feel overestimate >> say 50 years from now will you hope when you're dead on your tombstone
00:24:41
>> it says no we'll be looking at the results be like a the field one finally won the
00:24:46
Super Bowl audi's happy >> so Eric's intuition was very good the next NFC team is Detroit and it's at 17%
00:24:54
to make the uh to make the Super Bowl and then a big drop and after that so who you're missing between the Lions and
00:25:00
the Bucks because there's a bunch of them who you're missing is Seahawks at
00:25:04
13% % to make the Super Bowl. Packers who didn't look great last night, 11% to
00:25:08
make the Super Bowl. >> And I think I think we're questioning like I mean you react to the Seahawks
00:25:14
and I think we're reacting like I would say react to the Pats and Colts the same
00:25:17
way. It's like we have a lot of teams where I think there's higher uncertainty
00:25:21
because they really are kind of mismatching our priors coming into the season. Like the Colts are are look like
00:25:27
I mean if you just looked at this season you're like oh these guys are like you
00:25:30
know a powerhouse or whatever. But you know it's like you knew where they were.
00:25:34
Same with the stats and you're unabated. You use power ranks that you've
00:25:37
estimated somehow. >> We grab them from anywhere. So you can load in, you can put your own grab
00:25:41
somebody else, >> right? Do you add a probability distribution on the power ranks, a
00:25:45
posterior probability? >> No, but we we put uncertainty into the Sims. >> And how do you do that? Specifically, we
00:25:53
simulate the outcome of a game >> and then you add that into and we update
00:25:58
the >> I should at a future date I will we'll report the results of a study that one
00:26:03
of my students did to compare >> putting a posterior on the on the parameters which you don't do versus
00:26:10
adding the the noise into the through the simulation. It's it's an interesting result and it
00:26:16
is as I expected >> but the trick is you need the the the course to be to to match and so you want
00:26:22
to update as you go. So you need find to put a poster I mean >> you should take a draw you should have a
00:26:28
you should have a prior >> you have to draw the next observation and add that simulation error. Yeah.
00:26:35
>> The each week has to build on the outcome. have to put the outcome of the
00:26:39
well the answer is techically no if you simulated an infinite number of games in any given week then in theory
00:26:48
the theta the parameter and y would give the same amount of information. The problem is most sims aren't doing it
00:26:55
that way but if you did it that way you should get the same answer. In other words whether you're doing
00:26:59
>> well >> infinite simul not the same thing and not even close. Well, let's we I'll be
00:27:05
interested in the paper to see how how often it is, but often when you're running sims like that, you want to know
00:27:10
a lot of internal metrics like what happened, how often it happens, that kind of thing. And so, you need a
00:27:14
realistic path through the sim. >> But let's just be clear, what I'm
00:27:18
separating out is taking no at >> there's two forms of infinity I'm
00:27:23
talking about. One is I do your forward simulation an infinite number of times, but that's not the one I'm talking
00:27:28
about. I'm talking about between week t and t plus one. I do an infinite number
00:27:32
and then average that to even move on. >> You can't run those sims. So you're not
00:27:38
can theoretic theoretically can but you're like you like unabated is anybody
00:27:43
can log on here and get a 10,000 SIM while they wait for it and you just can't you can't do that with that.
00:27:48
Anyway, let's at least celebrate that there is uncertainty baked in because you you baked it in. Most of the
00:27:55
problems are that people don't and by the way to be clear there's a >> I don't know how this one's done but in
00:28:01
general when Massie Peabody does it we have a prior and we we're going to draw
00:28:04
from that prior initially. >> Yes. >> Right. So that you're not going to get
00:28:08
you're not going to say everybody starts at this number. It's like we we that's
00:28:10
the expectation but they might get a different number even. >> So the reason why I brought it up is
00:28:14
that NFL this year does seem to have more uncertainty in the rankings the power rankings than traditionally. I
00:28:21
mean, in other words, if you put in typically what you do is you put in two power ranks and outcomes a probability
00:28:26
of victory. That's usually a logistic function of some kind. What's happening
00:28:30
this year is it seems to be that that spread in the power ranking is not matching the usual probability that
00:28:36
comes out of it. >> Yeah. I mean, I mean, >> it's a scale factor.
00:28:38
>> I I don't know. I mean, you could you could see right my hypothesis is that
00:28:42
like there's more of a truncation in that. I think most power rankings when we think about park power ranking
00:28:47
consistency, we're really thinking about like the top 10. I mean, who really
00:28:50
cares about the 10th team versus the 20th team or something like that? And the top 10, I think because I think
00:28:54
things have kind of truncated, we don't have enough like I I I think there's not
00:28:58
a lot of standout. >> And so I think our we've got let me draw an analogy between what AI
00:29:04
is saying and my you know what I spent 20 years on in an educational testing. So I've got a ability parameter of a
00:29:11
person and I've got a difficulty parameter of an item. There's a distance
00:29:15
between the two. If you want in your language, there's two teams and I take the difference between the two. But
00:29:19
there's another parameter which is a slope parameter that multiplies that difference. That's called an item
00:29:25
discrimination parameter. Some items have a steeper slope or what we might call in statistics factor loading on
00:29:31
true ability than others. What Audi's saying is if my guess is if you did a time series of that that discrimination
00:29:37
is going down, which means the ability of strength parameters to predict outcomes is getting worse. Why would
00:29:45
that be going down? >> There's not as much. So that's a different question about as to why, but
00:29:50
I'm guessing the empirical result. Well, a couple reason. I'll give you a couple reasons. One
00:29:56
reason is there's error in the estimates of those. So that could be one possible
00:30:01
reason. >> Of course raises the question of why that would be. >> Another possibility is that's possible,
00:30:05
but the error, the stochastic error that I'm drawing on each game is going up. So
00:30:12
that's flattening the distribution of probabilities. That's another possible
00:30:16
reason. So it's not that measured. It's not that your game itself has changed.
00:30:22
>> You can you can argue this and there are new rule changes and it does look like
00:30:24
it makes an impact. I watched so many punts yesterday. I'm sick of it. But they land in different spots.
00:30:30
>> I assume by the way in Elo models or the type of paired comparison models I know
00:30:33
in marketing we can do this. You can estimate that scale factor. And so >> you could probably answer it
00:30:40
empirically. Does it appear that the stochasticity of games is going >> but we would have to see it over
00:30:46
multiple years of course just to put it straight straight in front of you. Let's
00:30:50
put it in football language. An 8-2 team with a certain win differential might not be the same and from year to year
00:30:56
>> possibly but Shane but Shane that's underlying both of the whole thing
00:31:00
>> but Shane has a more parsimmonious explanation I think or at least hypothesis.
00:31:03
>> Sure that there's Go ahead. Well, no, that well think >> that yeah, that that I think we we tend
00:31:09
to when we think about consistency across year to year, we're really kind of thinking about the top teams. And I
00:31:13
do think that there's this year it seems like, you know, the top teams don't seem
00:31:18
to stand out as much in my mind as as you know the other ones. I I I think there's more parody I think like say 1
00:31:24
to 10. I know that usual. I think this is my thought is that conceptually this scale factor is
00:31:33
meant to be invariant to the locations of the teams on that scale. Conceptually it's meant to be.
00:31:40
>> Okay. Interesting. All right. Well, estimate the scale factors please and
00:31:43
report to us. >> It just has to do with these this distribution of the probabilities and
00:31:46
why but but but Eric has offer Eric has asked the question is it changing over time systematically in one direction? I
00:31:54
think that's fair. >> And I'm wondering if there's a mechanism
00:31:56
and just you more afficados of the game. I I notice the game looks different. >> Just there's more
00:32:03
>> a hell of a lot more gambling on it than there used to be. I don't want to be
00:32:06
like cynical, but maybe that's the stoastic element we're looking for is
00:32:09
gambling. >> Clearly more uh kick returns. I mean, that's a huge >> I'll give you two I'll give it one you
00:32:14
gave, which is rule changes could change that. Here's another one. This is the
00:32:18
classic uh parody argument. Everyone I'm making this up, but not entirely. Everyone's using analytics today and
00:32:25
what that's causing it's causing a compression >> and that compression is actually going
00:32:31
to cause this scale. I'm just coming up with theory. I like the theory. I like
00:32:34
it's possible that theories the style of play has homogenized. Correct. >> That's another possibility.
00:32:41
>> Maybe analytics related. It was very entertaining last night when they were
00:32:44
when they were going for it at midfield at fourth and 20 or fourth and whatever.
00:32:48
And uh and that's an obvious I mean not that's such an it's an obvious analytics
00:32:52
move and and the the playby-play announcers saying I can't believe they're doing this but that's what they
00:32:57
all do today and what who are we >> those teams that want to win games that's what they all do today. We we we
00:33:02
need to wrap up and take a break, but I just want to push it one step further and make sure I understand is it true
00:33:07
that so let's just take that hypothesis and say let's say this is true that
00:33:11
something about the game has homogenized whether it's analytics base or just you
00:33:14
know wisdom or whatever that everyone's playing more similarly now are you still
00:33:19
going to get this result where you for the same difference in power rankings it'll be less diagnostic you would get
00:33:25
more similar power rankings >> correct yes it's a different it's a
00:33:28
different thing >> it's a different dynamic that the locations are getting scrunched, but
00:33:32
that doesn't mean that the differences are less predictive of outcome. >> Okay, so we need we need more we need
00:33:38
more evidence on. Um, but great question. All right, guys. That's the first half of Wharton Moneyball. We
00:33:43
still have a half to go. Come back and join us. >> Welcome back. Welcome back to Wharton
00:33:48
Moneyball. Welcome back to a very special episode in that we are in person. We are in studio and all four of
00:33:53
us are here. This happens about once a year these days. We always enjoy it. We're playing a little What caught your
00:33:59
eye? We're going guest free this week. Give us a more chance. Give us more of a
00:34:03
chance to kick things around. Um, we made it through two in the first half of the show. Two. And it was going to be a
00:34:08
shorter second half of the show. We're going to kick it off with Eric Bradlo.
00:34:12
If we have any time left, I'll add one at the end. Eric Bradlo. >> Well, ours might be the same one. So,
00:34:17
you know, I was looking at college football and I was thinking about the number of teams that are essentially,
00:34:23
you call it in the playoffs now. And I don't mean the teams that are in the playoffs. I mean, let's take our friend
00:34:29
Cade Massiey's team, Texas. Like, the playoffs have started for them. Like, they have two losses. Like, they have to
00:34:35
win now and every game left to make the playoffs. >> Oh, you're talking your define play like
00:34:40
teams that are like in like have to win out. >> Have to win out to make it. And I was
00:34:44
thinking, you know, Texas is playing Georgia this week. I think it's at Georgia. And I'm thinking, wow, what sim
00:34:50
is going to have Texas right now having any significant probability of like they've got to win at Georgia? My guess
00:34:57
is they're not favored at Georgia. >> Six and a half point underdog. >> Okay. So, but they have to win that
00:35:03
game. Like if they get there's there's no way this year the way it's going, I
00:35:06
don't think the three loss Texas is making >> speaking with too much confidence. And
00:35:09
one of our missions on this show, you think if Texas loses the game, they have a chance to make the playoffs
00:35:16
>> if they Yes. depends on what happens >> because well one it heavily depends on
00:35:20
what happens to other teams >> but they can't they're in the I forget
00:35:23
what they're in the SEC they can't win the SEC if they lose this game to
00:35:26
Georgia >> they have a hard time winning it even as it is but they but Eric they would have
00:35:29
still in front of them&m who's a top three team in the country so if they
00:35:33
beat them they'll be Arkansas if they lose Georgia beat Arkansas beat&m they
00:35:37
>> be nine and three >> and they would have beaten an undefeated number three team in the country on the
00:35:43
last week of the year and their two two of their three losses would be to Ohio state and Georgia who would probably be
00:35:48
top five teams. So, I'm not saying they're in. I'm not saying they're in,
00:35:52
but it's not zero. >> I guess a follow up empirical question. The extent that anybody's sim
00:35:59
forward, how many times does like a three win or three loss team get in? I mean, I guess it sounds improbable to me
00:36:06
under the old rules, but you know, we're all still getting used to kind of what
00:36:09
what I guess what bubble this kind of 12 team structure >> provides. I wasn't putting just Texas in
00:36:14
that bucket. I personally think I mean K to correctly I think Notre Dame's in
00:36:17
that bucket. I think Notre Dame has two losses. They have to win out. >> Oh, that that people take that as a
00:36:22
given. >> Okay. I think Oklahoma >> almost certainly would have to win out.
00:36:26
>> Georgia Tech. >> Yeah. >> Okay. Utah. >> Oh, yeah. For sure.
00:36:30
>> Okay. Well, so >> but they don't have they don't have the
00:36:32
I'm Look, I'm not I would defend >> they don't have the degrees of freedom
00:36:35
that they don't have the schedule. All I'm commenting on is I'm fascinated by
00:36:39
this bucket of teams that with three games remaining essentially to win the national title,
00:36:46
>> they have to start winning now. Every game now >> they're essentially elimination.
00:36:51
>> Every game is an elimination game for them. And for some reason this week I
00:36:55
was looking through this more than normal. >> Well, I mean in the old days every game
00:36:58
was like an elimination game. It was like one loss and you're out of the playoff out of the two game playoff.
00:37:03
>> That is my point. Yeah, >> I'm loving the fact that there's more
00:37:06
teams now. Like I I just I'm finding games exciting because I mean obviously
00:37:11
I would probably watch the Texas Georgia game anyway, but the fact that it's in
00:37:15
my mind an elimination game, not with certainty for Texas makes it even a stronger game to watch. The same thing
00:37:23
for Notre Dame and this whole set of teams now. >> No, and I mean your observation is true
00:37:28
that that game would be essentially meaningless in the old scheme because Texas would definitely be out of like a
00:37:33
two team Georgia would still be in the mix, you know, long shot kind of thing. But I
00:37:37
mean, we've gone from two teams >> at the end to four teams at the end to
00:37:42
now 12 teams at the end. Of course, that just broadens the number of meaningful games late in the season and and you're
00:37:47
talking about something that I think is exactly right and fun. Um, that there's
00:37:50
still that many in the mix. Um, and that we're looking at, you know, early round
00:37:54
playoffs kind of already. Certainly many many people, by the way. So, I mean, I I'll I'll kibbitz on yours in the same
00:38:00
way I kibbist on Shane's and maybe we'll skip any actual what caught my eye, but
00:38:06
I ran the I looked at the athletics college sim and this is the first time I've ever looked at it and you know the
00:38:14
athletics part of the New York Times now. So, this is what they everyone points them to and you know they're
00:38:18
doing the same thing. They're grabbing power rankings and putting them in and I
00:38:21
think it's an example of a sim that doesn't have enough uncertainty into it.
00:38:24
They have it's just they're I feel way too sure about teams making playoffs and
00:38:31
and way too sure teams aren't going to make playoffs and they give for what for
00:38:34
example what do you think Eric you're paying some attention to college football this year. What do you think is
00:38:38
the highest probability any one team has or should have for winning the national
00:38:43
championship. Right now there's three regular season >> a champion point. Three regular season
00:38:48
games left a conference championship round and then depending on how many times you have to play whether you get a
00:38:53
buy or not three or four games in the >> Okay. So I'll I'll do my I'll go around
00:38:56
the room here. Okay. >> What's the maximum? >> You want me to give a number or do you
00:39:00
want me to tell you how I'm thinking about it? >> Both. >> Okay. So I'll tell you how I'm thinking
00:39:03
about it and that will lead me to a number. So there's going to be some set of teams that win the power conferences
00:39:08
that get a buy in the first round. There'll be another set of teams 9 through 12 that have to play five
00:39:14
through eight. But let's get to the final eight at. So there's 12 and a half% on average probability given to
00:39:20
each of those eight teams. Okay. Let's assume a team is the favorite in that
00:39:24
round. How much pro what's the most probability I'd give to any of those
00:39:28
final eight teams? I would say I I was going to say 25%. >> I'd jump to the same place
00:39:36
>> somewhere like that. So that's my prediction. >> Double double. But so you think but that
00:39:40
>> but that's giving by the way very low probability to the five through eights.
00:39:44
It's not giving zero probability because I actually I'm not going to count Ohio
00:39:47
State at one the same I'm going to count. >> But but but but Eric you're but you're
00:39:52
giving them a pass to that point. I don't think that's fair. I don't think
00:39:55
there's any team you can say right now is guaranteed to be final eight. I mean
00:39:59
happens. >> Well Ohio State just has to win the Big 10, right? because then if
00:40:04
>> to get a to get a pass that's true they so that's that's true
00:40:09
>> four teams four teams will get it we'll get you I'm just catch I'm catching up
00:40:13
with you >> I think they'll be one of the top four remaining >> so you are they guaranteed I mean no
00:40:18
they have to beat Indiana in the Big 10 championship >> and then maybe maybe in some world both
00:40:24
of those teams get a buy but some that's not given >> can't happen now right it's not based on
00:40:30
rankings like I think the top It can happen now. Yes. It's it's based on
00:40:34
rankings. Last year it was it was conference champions. >> Oh, it's the opposite.
00:40:38
>> The only the only wrinkle they changed in the college football playoff setup is
00:40:41
that they went away. The top four teams get buys and they're the top four ranked.
00:40:47
>> Oh, there's no guarantee then that Ohio State's the top four. No, definitely
00:40:50
not. Now that I thought it was the other way around. You're right. They switch it
00:40:52
from conference ranking. >> But that improves your chances. It doesn't hurt your chances because some
00:40:56
there's some chance that the Big 10 loser still gets a buy and there was no chance before. Either way, I watched
00:41:01
Indiana since my wife's a Penn Stater. >> That's not a good football team. Come
00:41:06
on, >> Eric. No, you're Eric, you're speaking with too much confidence on these
00:41:09
college football. >> They're not a great football team. How about that?
00:41:12
>> They've got They've got possibly the best quarterback in the country. And in
00:41:15
college football, the best quarterback is going to go along. >> If they played Ohio State right now,
00:41:20
what would be the point spread in that game? >> On a neutral field, I'm not looking at
00:41:24
anything, but their power rankings are close. Um, no more than three and possibly less. Wow.
00:41:30
>> No more than three. >> We don't have the the >> I'm certain of that,
00:41:33
>> Kate. We don't have the distance that we used to have back in the day
00:41:36
>> when Alabama would be like six points above somebody else. >> That is correct. And also, it's the
00:41:41
thing that Shane was saying a minute ago about the about the Colts. We can't get
00:41:44
it into our head that the Colts are decent. They may not be decent, but it's
00:41:47
the same thing with college football. We can't get same state, by the way. Same
00:41:50
state. We can't get our head around these Indiana football teams. >> They don't even do the time difference
00:41:55
uh the time change. It's very confusing. But I mean, this is a >> What are they doing over there?
00:42:00
>> I mean, it's a big deal because historically, I I don't know the ins and
00:42:03
outs of the tournament structures and leagues and the power conferences the way you guys do cuz I don't watch
00:42:07
college football. But what I would have done was looked historically at how often the, you know, the top ranked team
00:42:15
in the season was categorically different. >> I just think I can't do that.
00:42:19
>> Categorically different. And I think it's and and because of this diffuseness
00:42:23
of talent, you don't have this this elomeration in just a couple teams who just walk all over everyone because
00:42:29
everyone has to be at that team because you're not getting paid to be somewhere
00:42:32
else and a lot too. >> Is Indiana too >> in the power rankings? They're the
00:42:35
closest to >> they were going into the games last weekend, I think. >> So, it's possible that uh&m will jump
00:42:41
them. Um Ohio State be one and then it'll be Indiana or&M because Indiana
00:42:45
struggled with Penn State. Um which was an that Did y'all see the catch? That's
00:42:50
>> I heard about that. >> I think it's the best catch. It's It's
00:42:52
certainly one of the best catches. It's a that I've seen in my lifetime of
00:42:56
watching C of football, period. I mean, name me a better catch. It would have to
00:42:59
be a diving thing. This wasn't a diving thing. This was a foot in the back of
00:43:02
the endzone thing. But between the quality of the catch and the moment because it was a game-winning catch, I
00:43:07
think I made the >> There's no greater combination. >> The greatest catch I've ever seen is the
00:43:12
Giants against the Patriots. What was the guy's name that the helmet? Tyrie.
00:43:16
Well, that was the That was the flu. That was given the moment >> that was the biggest catch of all time
00:43:21
maybe like like I think like Julio's catch in the Atlanta Super Bowl where ended up not actually changing the
00:43:26
outcome but like was a better actual catch >> or that OBJ one from way back when he
00:43:32
like I I mean I can think of a lot I can think of a lot of catches in ter like that kind of hit the spectacle part of
00:43:37
it but in terms of content >> what about what about the one at the end of the Super Bowl was
00:43:42
>> the Edelman one no I I know was it Steelers Rams or >> Steelers Cowboys there a toe tap catch
00:43:49
in the uh in the end zone to win the Super Bowl for it was um Antonio I don't
00:43:55
know it wasn't Antonio Brown it was somebody >> but it was the Steelers beating
00:43:58
>> it was the Seahawks >> Steelers Cardinals was a great game >> maybe yeah whatever Kurt Warner
00:44:08
>> we're also not we're not also not The Cardinals were ahead late and the
00:44:11
Steelers went down and that catch at the end like 5 seconds left. A touchdown catch. I don't remember that catch.
00:44:18
Okay, >> it wasn't as spectacular, but in terms of consequence, the game-winning catch
00:44:21
by Malcolm Butler and for the Patriots against the Seattle Seahawks was also one of the most consequential catches of
00:44:27
all time. >> Consequential, but not. So, was my 25% even close? >> What's the number
00:44:33
around the room? >> I wanted to chip it a chip. I wanted to chip it down. I think it's a reasonable
00:44:37
way thing you did, but then I don't want to give him a pass into the final eight.
00:44:40
And so I want to I want to knock that down by some >> I was going to be naive.
00:44:45
>> You didn't ask me for which team. I just said one team. So you asked me the
00:44:49
maximum probability. You didn't say which team it was. >> But you have to apply it to same some
00:44:54
specific. >> No, no, no. But some team is going to be in the final four and some team is going
00:44:58
to be the top ranked team. And I think the top ranked team, whoever that might be, is going to be
00:45:03
>> It's a big difference. >> It is a big difference. But but I'm
00:45:05
asking the question, I'm going to give every team a probability right now. What
00:45:09
is a reasonable maximum probability? >> That's not what he's asking. That's not
00:45:12
the question he's asking. >> Well, he did up to that point. >> No, he's saying at the time of the
00:45:16
playoffs. >> No, no, no. But ask or I mean I I I could get I can even say now out of some
00:45:22
team I don't know who it's going to be, >> but he's not asking. He's saying we're
00:45:28
not interested in that version of the question. >> No, it's the same question.
00:45:30
>> No, it's not. >> I'm sitting here now. some team has a there's a maximum probability. No, he's
00:45:37
supposed to know what it is. >> That's not interesting. >> Yeah,
00:45:39
>> we want we want to know of the specific teams that we're observing right now can
00:45:44
place bets on or >> you didn't say which one. You just said the maximum probability.
00:45:48
>> We don't have to. We're going to we're going to we didn't he's not asking about
00:45:51
Ohio. He's saying if you take all the teams out there and and calculate whatever system as of today, what are
00:45:57
their probability of winning the college football championship? What is the maximum of those numbers? He's not
00:46:01
asking what Ohio's number is or what Oklahoma's number is. He said when we
00:46:05
once we rank them, find the max. >> Yeah. I mean, my naive much more naive
00:46:09
version of that that answer would be like, you know, cap like >> you know, the the best team's going to
00:46:14
make it to the to the final eight and then flat from there. >> Okay. >> So, that would that would give you like
00:46:19
what like 8% or something like that or >> Well, which team has the highest
00:46:23
probability of getting a buy at the final eight? I'm giving a very naive my He's given him buys there, but then his
00:46:30
coin flips. So, it's going to end up some somewhere between these two guys is
00:46:32
my is my guess. >> So, my my my guess is there be there's a there's one or two teams that are almost
00:46:38
certainly to get a buy uh right now. >> Well, if you believe that, then you got
00:46:42
to go towards my number. >> That's right. It's it's close to your
00:46:45
number, right? >> Okay. So, >> but it's going to be a little less
00:46:48
because there isn't any team that has that and that has a little smaller factor and you got to multiply that. So,
00:46:52
you're going with 25. I'm gonna probably go with their 18. >> Yeah, I'm with odd because I don't I'm
00:46:56
not giving anybody a pass to the final eight right now. Um I'm going to go with
00:46:59
odd. go 20 and the top one's 29 which I think is absurdly high. >> Yeah.
00:47:04
>> Oh, by the gambling metrics >> by by the athletic sim >> sim and that's not the only that's not
00:47:10
the only sim. >> And what does the gambling I bet you the gambling metrics would go would be what
00:47:13
does Vegas do? >> Great question. I don't have that in front of me right now. So we can we can
00:47:16
find it but I don't know. >> So the question is >> I bet it's lower than 29%. So the
00:47:20
question is what's Ohio State >> better than plus 300? They have to be
00:47:23
more than plus three. Plus 300 plus 25% on well there's a vig in that. So we
00:47:28
take but it's not that high. Why don't you look? >> Okay, we'll get it. In the meantime, let
00:47:32
me say give you one other bit on college football just in terms of updating everybody. Um that that people think
00:47:37
people started talking about like this week is the split on the playoff bids between the Big 10 and the and the SEC,
00:47:45
>> right? >> So there, think of it as being basically there are four teams that were going to
00:47:49
be in from some other conference. Notre Dame's going to get in as long as they
00:47:53
win out. Um, there's probably a group of five, maybe. Well, there's should be the
00:47:58
conference winners from the from the ACC and the Big 12 and the top rated group of five. Right.
00:48:03
>> By the way, you want a fun wrinkle? The ACC is so bloody awful this year.
00:48:07
>> Yeah, they're awful. >> So, the the the the playoff format isn't
00:48:11
>> the champions of the best four conferences and then the best fifth one from one of the group of fives. The
00:48:16
playoff format is the highest rated top five conference champions. And so it's
00:48:21
possible if the ACC champ is so bad that there could be two group of five champs
00:48:27
that are higher rated and the ACC could theoretically miss the playoffs altogether and two group of five
00:48:32
champions would be it. Would that not be spectacular? You want chaos, Eric? >> That would be great. I'm all right with
00:48:37
that. >> Two group of fives. >> You want to know the answer? >> Yeah.
00:48:40
>> Below 29%. >> No. Vegas. Well, the Vegas odds are slightly above it, but when you subtract
00:48:44
the Vegas, it's 29%. >> Oh my goodness. So Austin something >> uh plus two plus 200. It's about right.
00:48:52
>> I want to short theid. I want to short the Buckeyes winning. >> And it's the Buckeyes by the way.
00:48:56
>> Yeah, it is. >> Yeah. Yeah. Yeah. >> I I Okay. I I would short that. I'll
00:48:59
take I'll take I'll I'll give those odds. I'll I'll >> way that's a good bet.
00:49:04
>> So 185 is what is the worst bet you can get. Now 225 is currently the best you
00:49:09
can find right now. And that's 225 is right around uh 31%. Subtract the VIG,
00:49:14
you're right around 29%. Interesting. Okay. Well, I can believe that they have
00:49:18
a lot of attention. I don't think that's smart money. >> Let me ask you a different question. I
00:49:21
mean, related though, it's the same topic. So, I gave an answer of 25%. And then you guys, it's fine. I I understand
00:49:28
the logic behind that number is even too high. But like I always find it interesting when people try to move you
00:49:36
off like you wanted to go lower and the answer is actually higher. So, what's
00:49:40
then wrong in your logic? Because that sim, it's not even just the betting odds. This is a sim. So why are you guys
00:49:48
all with reasonable arguments saying 18 19%? >> I don't think they have enough 29%.
00:49:53
>> Yeah. And I think the market is too sure the I mean >> market will bet up the favorites.
00:49:58
>> Yeah. We we know that >> I wasn't worried about the market bet
00:50:00
but the sim >> there's not enough uncertainty in the sim and I see that from other 25 to 18
00:50:08
that degree. >> That's the problem with sims don't have enough uncertainty. No, no, no. I I give
00:50:11
you you look you look at more than just that number and you just they're too
00:50:15
sure they know what teams are going to make it. Look at the probabilities. They like they're certain they know like
00:50:20
>> I don't know 10 of the 12 playoff teams and there's just no way with four rounds
00:50:25
four games ahead left in the schedule that they can be that sure. You just see that there's too much uncertainty, too
00:50:30
little uncertainty in the >> Ohio State by I think you would agree with this. For Ohio State not to be a
00:50:34
top four, they would probably have to lose two games. No, they could. They It depends on what else happens, but if
00:50:41
they don't look great in the Big 10 final against Indiana, that could happen.
00:50:46
>> But you said it was the top ranked teams. >> Yeah. >> You're saying they could fall to number
00:50:50
five even with just one loss? >> Well, it's a fair question. Could that
00:50:54
happen? What what has to happen is that three SEC teams have to jump them because it's not they're not going to
00:51:01
come from I mean in if tech Texas Tech goes in and blows somebody out in the Big 12 final are they going to jump Ohio
00:51:07
State? So it would be have to be Texas Tech, Alabama, and Georgia potentially, but they're probably playing each other.
00:51:13
And so two, yes. >> Or what if there's a greatl looking SEC team that just misses the SEC final
00:51:20
because they are lose some tiebreaker. >> Say this could happen. And so you you
00:51:26
have two strong SEC teams in the SEC final. You have a third one floating around that lost a tiebreaker and
00:51:32
they're just as good as the other ones. Maybe they even like them better. The
00:51:34
the markets like them better. And then you have a really strong tech. So I've
00:51:38
given you now four possible teams that could >> I just don't see them passing Ohio State
00:51:44
with only one loss. I just don't see it. >> It's possible. It's I I it's got to be
00:51:49
something. But you've talked me into believing that it it's higher probability than
00:51:52
>> and just to kind of calibrate in in in the Houseion days of like when Alabama
00:51:57
was like 10 points above the next highest team. What would be the max like Alabama you you would ever given ma talk
00:52:04
if we were in one of those seasons what's what's the m what's the probability you would have assigned the
00:52:09
max in one of those season like would you for what winning the championship >> yeah the same one you're arguing is way
00:52:15
too high at Ohio State at 29 >> at this point in the season yeah >> but we have a very different playoff
00:52:20
system now >> right >> yeah I guess I'm trying to say like you know pretend like the we had the same
00:52:25
kind of team separation we we had back when Alabama was so dominant Oh, I see. But current structure
00:52:31
>> current structure, but you know, Alabama is it would be interesting to see what the
00:52:37
upper bound essentially is on that probability logic. We'll give him a pass. We'll give him a pass into the
00:52:43
final four >> and then we're just going to do something more strong with the Eric's.
00:52:48
Eric started out saying one over eight and then he went double that for the better teams. Correct. And we would just
00:52:55
it would be less than because their their lead was about 10 points higher than the next best team.
00:53:00
>> No, that's too much. >> Is it too much? No, it was pretty high.
00:53:02
Was it 33? >> This is the kind of intuition I'm getting at. The fact that you instantly
00:53:06
reacted to that being too much. So if you use my rule of thumb, which is not accurate for college,
00:53:12
>> seven was big. Like I would say five or six was a typical >> each point multiply by two and a half.
00:53:16
>> 17 and a half. So 67 to 2/3 over the second best team. and a lot more over
00:53:23
>> over the next one. So I see. So you'd say something like 75% over the second
00:53:28
best team, maybe 80. >> Got in the in the extreme years. >> Yeah, in the extreme years.
00:53:33
>> Yeah, that's what I'm trying to get at is kind of almost the upper bound on
00:53:36
what you'd ever want to give the max or you know, type of thing. >> How it depends on what you think of one
00:53:41
versus four. What's one versus four? >> Yeah, I mean they catch up pretty quick
00:53:45
those they start sacking up pretty quick. So there's not as much obviously not as much of a spread as you go. So,
00:53:50
but so I'm gonna answer Shane's directly by saying I don't know 35%.
00:53:55
>> Okay. >> That's again why I think 29 is way too high. >> Yeah.
00:53:59
>> But Eric's talking me out. >> So Ohio State is twice as dominant in
00:54:02
your mind as Alabama was back in the day >> because you you you had him down more
00:54:06
like 17% or something. >> You mean Alabama's twice as dominant? >> Yeah. D Yeah. Half as dominant. Yeah.
00:54:11
>> Yeah. that the this the talent that was stacked up by the even Ohio State back
00:54:15
in the day, but especially Alabama and Georgia for those years. It was just I mean everybody talks about it's just it
00:54:20
was just >> And by the way, do the final four teams when when let's let's just pretend that
00:54:24
five, six, seven, eight all beat. Do one through four play on their home field? >> No. Um the first round is in the home
00:54:32
stadiums. >> So 5 through eight and 9 through 12 is home, but the next one are the bowl are
00:54:36
bowl games. >> Yeah. Yeah. And that's a some people think that's a knock on the system that
00:54:39
they don't they take away a home game from the teams that got the buy and they'd like another round of home
00:54:44
fields. >> I think I would too. >> I I think it's reasonable. >> Is it because of money? Did they lose
00:54:47
the home game or >> I think I mean I I feel like Exactly. Exactly. It's maybe an intermediary
00:54:54
state to kind of like keep the bowl legacy thing. >> They may lose it eventually. Um people
00:54:58
people loved the home field playoff games last year. People were euphoric about them. It's like a really big deal
00:55:04
these late season playoff games at a home state. I know friends who went in Austin and it's just a whole different
00:55:09
deal >> and I mean and you heard in the media as well just real quickly and then we'll do
00:55:14
maybe a real quick round. >> Okay. >> Um the questions whether the Big 10 can
00:55:18
get a fourth team in and hold off a fifth SEC team or whether SEC can pull in this fifth team and hold off
00:55:25
>> the four big there's Indiana Ohio State >> Oregon looking pretty good that win they
00:55:29
had a last minute win right after um yes Indiana's last minute win two back-to-back unbelievable Big 10 games.
00:55:34
So people are thinking Oregon's pretty good, but then they're like SC is still
00:55:38
kind of in the mix. If Michigan made a run, they're kind of in the mix. And then in Texas, in SEC, there's a few
00:55:44
teams buying for a fifth spot. Texas, for example, Oklahoma, for example. All right. Why don't we do in the last four
00:55:49
minutes, can you do it a really quick? What caught your eye? Just >> Okay, I'll just go quickly. Um, there's
00:55:54
been lots of stories out there that the Sixers are actually better without Joel Embiid. There's been similar stories
00:56:01
that the Lakers are intentionally sitting LeBron even though he's got a sciatic issue. So the question is, is it
00:56:06
possible now at this point in the career that the Sixers Lakers are the are a better team without it? Now I say in the
00:56:13
last 10 seconds I have for my one minute Embiid's plus minus on the court is
00:56:18
horrific. The team is negative with him on the court right now. So, I'm just
00:56:23
wondering, is it possible that at the end of careers, even superstar players who demand the ball, if you just used
00:56:29
him as a part-time player, but coaches won't do it? So, that caught my eye. >> Interesting, Adi.
00:56:35
>> Well, I have to say what caught my eye was the gambling in Major League
00:56:39
Baseball. >> Oh, yeah. Right. >> I mean, the idea that these multi-million dollar players would risk
00:56:44
their careers >> like 12,000 >> for just tens of thousands of dollars.
00:56:48
>> Baseball or basketball? Baseball? No, I'm talking about the baseball. They
00:56:51
were throwing the baseball announced that they're no longer going to that they don't want the the gambling
00:56:56
companies to and the gambling companies agreed not to allow bets in game on the outcome of a pitch.
00:57:02
>> Um because individual players found it too easy and too attractive to collude
00:57:07
with a gambler to throw a strike or to throw a ball when when certain part and and there were there were parlayies.
00:57:14
eight. One of the guys had bet eight successive um balls and one of the accused pitchers, I can't remember which
00:57:22
of the two, throwing it in the dirt and then finally he throws the eighth one again in the dirt. Pitcher hit her swung
00:57:29
at it. >> That's great. >> That's hilarious. >> Amazing.
00:57:37
>> That's why I call it gambling. >> Yeah. No, that's that's downright
00:57:40
charming right there. >> And this is I mean this is tragic. I mean, because it seems, you have to
00:57:45
argue that the reason why the protection, the integrity of the game is protected based on the fact that they're
00:57:50
already rich and to scale up to a to size that would make a money that matters to them would be noticeable.
00:57:58
>> You know, these little $50,000 bets here and there are okay, people shouldn't you
00:58:02
can pull them off without noticing, but they shouldn't care about them. Look,
00:58:06
there's a general thing here about gambling, getting away from these in-game individual plays like the and so
00:58:12
it's possible that we get away from that alto together. Shane, >> well, I'll just mention I I just saw the
00:58:17
uh it's probably going to they're probably going to get back on top, but
00:58:20
the Oilers are playing terribly right now. And I'll just point out that they
00:58:23
just lost 91 to the Avalanche a couple nights ago. And the kind of unique thing about this particular game, 9-1, they
00:58:30
lost one. >> Four guys scored two goals. >> Four guys go. Not only that, the
00:58:33
Avalanche went 0 for seven on the power play despite scoring nine goals. >> Is that amaz I don't know. I don't know
00:58:41
if you know the headline that four guys had scored two goals which is quite rare
00:58:45
apparently in hockey. >> Absurd. I mean how many minutes do they have a regular
00:58:50
wonder like how did it even >> Why is that that rare? If if the other team's if I'm really down I'm going to
00:58:55
start taking it out on the other team. Once I'm down 617 I'm going to start
00:58:58
hacking the other team. Just Yeah, why not? >> Jeez. Wow. >> I'm already going to lose the game.
00:59:02
Yeah, but I mean if you're already giving up goals at that rate, why how are you suddenly like not doing it on
00:59:06
power? Like Yeah, it's >> just remind me what what fraction of goals are on power play.
00:59:10
>> Oh, like maybe a third or something like that. >> Is there any argument changes quickly
00:59:14
for 10 more seconds on your topic that you're ahead by so much that you just
00:59:18
kill time on the power play? In other words, if you're up seven to one, what
00:59:21
do you need to >> Yeah. No, I mean, it's true. You don't kind of get a sense of the load
00:59:25
management that probably went in the second half of this game. Like I mean certainly they took out the Edmonton
00:59:30
took out their goalender after like four or five you that that we can assume but
00:59:34
like otherwise the load management of what the Avalanche were doing and what the Oilers were doing in the second half
00:59:38
that's that would merit further study. >> Why would they take out their goalender?
00:59:41
>> Well well I mean well he let in four goals and like 13 shots like that. When
00:59:46
you look at a score like 91 you're like well there was definitely a goalender
00:59:49
replacement probably somewhere in there but how much they took out their other we need to curve probability of scoring
00:59:54
on the power play versus goal differential. And what we're going to see is maybe in the far right tail teams
00:59:59
don't even try to score. >> They're just resting, hanging out. >> But but let's not
01:00:04
>> because the other opponent can't score on you pretty much. >> Don't bury the lead. The Oilers suck
01:00:07
apparently >> for now. For now, let's enjoy it for now. You know, come play. Yeah, I mean
01:00:12
the Flames are even more. >> They're my adopted NHL team. >> They're going to build momentum.
01:00:16
>> What happened to Canada? I thought they used to be able to play uh to hockey.
01:00:18
>> They would they focus on baseball now. >> And they got so close. >> They got so close.
01:00:27
Why don't we leave it there? That's a perfect way to end. Why don't we wrap it
01:00:30
up for the whole team here? This has been Kate Massie, Shane Jensen, Audi Winer, and Eric Bradlo coming to you in
01:00:36
person in the Wharton studios. Thank you for being here. Big shout out thanks to
01:00:39
D Patel and the whole team. It does take a whole team and we appreciate it. Dion
01:00:43
Sipkins in particular in the house back where he belongs with us over the last 11 plus years. Thank you guys for
01:00:49
listening. Come back and join us next time. Between now and then, enjoy your sports.