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Welcome, welcome to Wharton Moneyball here on the Wharton podcast network. This is Eric Bradler, professor of
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marketing, statistics, and data science here at the Wharton School. And some combination of four of us today. We have
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Shane Jensen, professor of statistics and data science. AI Winer, professor of statistics, and data science, the three
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of us, and Cade Massie, some of us are here every week here on Wharton Moneyball. Uh, as always, guys, uh, we
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always have an open line segment, which we'll do first. As you know, we're
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working out some technical issues with our guest today, and we'll see if we have one, but there's a lot going on in
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sports that can easily take our listeners through a full hour of sports and analytics here on Morton Moneyball.
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So guys, why don't we start with, you know, we always like to start with what
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caught our eye, Shane, since you're on my left and I reread from left to right.
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Shane, what caught your eye in sports this week? And there could be a lot. >> Yeah, I mean, I'm sure we'll talk about
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baseball, so I'll wait on that. But um what caught my eye obviously is the Patriots uh and potentially having a
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real quarterback again, a franchise quarterback. I don't want to get too hyped up too early. We're still kind of
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he's only in his second season, but Drake May was absolutely incredible. Has
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been incredible so far this season. He's, you know, I mean, again, it's early to discuss MVP, but he would be in
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that conversation if we were to have that conversation at this point. Uh so I guess I'm just really excited about the
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Patriots. They they're looking like a playoff team. >> Yeah. What kind of credit do you give
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honestly Mike Vrabel very successful coach just took over as coach. Um remind me their offensive coordinator Josh
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McDaniel right is back as their offensive coordinator. So I hate to look I'm not taking anything away from Drake
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May but you've got an established head coach that's a winner. >> You've got an established offensive
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coordinator that's a winner. Well, winner Mike Fable. I mean, when you say winner, uh, uh, Mike Fable is a head
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coach. I mean, not not not his overall Tennessee record. You're not pointing
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to, right? You're not pointing to the fact that he's led a team to the playoffs before.
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>> Yeah. And I'm not trying to take anything away from him. I mean, it's
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obviously an impossible tell. I mean, we had like, you know, 15 seasons of Belch
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and Brady co-observed and people were still arguing about whether it was Brady or Belich. I don't think we're going to
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ever, you know, it's going to be hard to keep kind of deconvolve those, you know, certainly early on in his
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career. >> Look, we all believe in, you know, uncertainty, right? And I think for 15
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seasons for Bellich and Brady, there was obviously a very strong confound. Are you Mr. Patriot, Mr. I love both Bellich
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and Brady. Are is there any are you starting to at least put a small probability
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given what Bellich did at New England in his last few seasons, what you're now
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seeing at North Carolina, is there even a small part of you that's starting to give more credit to Tom
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Brady? >> I've always given a lot of credit to Tom Brady. I mean, that's that's a softball.
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Yeah. I mean, all the credit in the universe goes to Tron R. But but I mean, again, let let me stop short. I don't
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want to take any I I what what the Patriots did, which no other team has ever done kind of for the the length of
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time that they did it, was a collab, a a successful collab between one of the great the greatest quarterback of all
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time and one of the greatest coaches of all time. You know, I I do think Belch has done more in the post collab period
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to kind of take away from I guess his leg whatever, but I still think Belch's
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legacy is is is kind of set in stone based on what what he did with the Patriots. Would I still hire him as a
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head coach? No. But I mean, Audi, you want to jump in on this or on Well, you if you want to jump in on this, please
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do and then you'll get your own topic. I >> I do want to jump in on this. I don't
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think that that it's important to recognize that as a football outsider for all these years who was trying to
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build my knowledge base. One thing I have learned it's it's almost impossible
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to be successful as a coach without a great quarterback. So the fact that that Bich hasn't been so successful in the
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post Brady years is not necessarily that particularly damning of Bichc's talents
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over the years. >> How do you define success, Audi? For example, I'm just making up some names.
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So for example, someone won a Super Bowl with Brad Johnson. Someone won a Super Bowl with Joe Flacco. Someone won a
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Super I mean there are I'm not saying you get Brady's level of success. Let's
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not I'm not trying to compare. >> Audi said great coaches. So I think there's got to be some kind of sustained
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success built into that. I don't want to speak for you Audi though. >> Audi, go ahead.
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>> No, I mean I mean my question is is it what what is it? What is the information? Think of it from a from a
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posterior updating. We saw years and years of of Bellichic with Brady. Fantastic. Right. And we said, by the
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way, remember we saw years I you may I know you know this audi we saw years of Bellich prey too and it wasn't that
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great >> right? But the thing is is that there must have been more to just Brady to
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years and years of all that success with the with the >> Yeah. I know. And I mean, again, again,
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we we kind of I think um Eric, you talked I mean, or we we we think back probably most recently to their kind of
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end end dynasty kind of run where Brady was in god mode and in the early kind of
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dynastic year, you know, when they were winning very successfully in kind of Brady's very early career.
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>> Yeah. Brady was kind of the game manager. He did he was kind of wore what
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we regard as an adequate quarterback that was fine that and it was a world-class defense which Bich basically
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won those championships. So I I I mean it's kind of I I do think we kind of in
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in retrospect want to kind I I certainly give Bichc a very big part of you know that that success especially in the
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early years. >> The other thing to think about and this is uh something very very much a feature
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I think of football. the game changes. >> Um, and it does go through all kinds of
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shifts and non-stationarities in the way the way it's played and that in some
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level >> you may have been a fantastic co coach because you've mastered the skills and
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in the environment of a certain era and then if that if you just continue in that that you slide into your old age
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doing that same thing, you may not have it anymore. in which case it's not to
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that reflects badly on the past Bellich check but this current Bellich check is not going to do it in today's game.
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>> Well, first you guys have brought up two parts and I want to get to what caught
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your eye but I would two parts. One is I completely agree with Shane's part which
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is you have to give Belichc at worst if you wanted to be critical of him which there's no reason to be but if you
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wanted to be you have to give him credit for those first few championships where
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Brady was not the Tom Brady of age 30 to 40 or even 30 to 45. Um the defense was
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amazing. His numbers were they were good. >> He was pretty clutch in the playoffs. I
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mean he did win a couple but like but yes I mean I think it was definitely that was a team known for its
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defense. would have been, >> you know, kind of guess Russell Wilson and with Seattle type scenario, but also
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a your point about the non-station of the game I think is also it's another reason. It's not like I don't think
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Bichc has the energy or the mind or the you know it's age doesn't matter to me.
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It's not like I think he's lost his ability to coach people, but I think the
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point is is that the game has changed in a way that he would need to significantly change the style in which
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he coaches to be successful today. And that's just hard to do. That's hard of
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anybody. It's not. And also, it's hard to do for someone that won six NFL
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championships. And I'm not even counting the ones he won as the Giants defensive
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coordinator. And how many Super Bowls the man has been to? Like, I don't know,
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half of them in the last 35 years. I don't know what the number is, but it's
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some big number. But Audi, what caught your eye besides the Patriots? By the way, I watched a lot of the Patriots
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game sh game. Drake May is for real, but Audi, what are your thoughts? >> Okay, so of course the last time we were
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together, the Yankees and the Phillies were still in it and now both have been eliminated. Um so big questions going
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ahead um of course is particularly with the Yankees and I think the general question the analytics revolution if you
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if you want to condense it today and into its biggest impact factors would be the hitting revolution that has led
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towards the large numbers of strikeouts um and and the kind of three true outcome hitting or whatever you know
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>> they call that all that kind of crap >> the three two outcomes hitting, but it's
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essentially, it's interesting because it it it's plays off the idea that a strike
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out is no worse than a regular out, which conditional on an out is true. Conditional on an out. That's true. And
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in fact, >> no, that's true. >> Well, it's tricky because a strikeout
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obviously does not move the runner over and is generally a sacrifice, but it's
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al also not a double play. So for and from someone who watched a lot of Stanton grounders into double plays, I'm
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thinking why couldn't just strike out? I do think there's kind of there's an
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analog push against almost like against balls in play, you know, more than anything. And and and I think certain
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certain teams have kind of I think there's almost a counter push on that half.
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>> Well, so it's interesting. You look through the Yankees who with the
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exception of Aaron Judge, which I'll get back to in a moment, which is basically
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awful at the plate and massive numbers of strikeouts. No two two strikes approach. I mean, I want to pick on
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Trey. >> High slugging, high slugging, low batting average. >> Well, that's during the season, during
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during the playoffs. No, no, I mean, okay, right. Um, so very low batting average, but also very high strikeout
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rates. And one one of the things you noticed quite vividly in the playoffs is no two strike approach, right? So,
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particularly with runners on, I mean, Trent Gisham is swinging for that porch with everything he has.
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>> What is Vulpi like doing like >> and Vulpi is the same way, right? So,
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Vulpi's hits nearly, you know, about 20 home runs. >> Let me let me ask you a question. Let me
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ask a question. It's not like these hitters just became who they became. It's also to Shane's other point, it's
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not like whe you know whether it's Cashman or Boone can't see, huh, these
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guys bat 180 against really good pitching. Huh, maybe a good player in the playoffs. They can see the data. I I
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do I do think playoffs are mostly coin flip, but I'm starting to kind of deviate away from that and that I do
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think this kind of three true outcome it works well over very large samples. You
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hit a lot of bombs, etc. Uh but I do think in in the in the playoffs when you're only facing good pitchers and you
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have to kind of do stuff in high leverage kind of situations or or like you know the little things seem to
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matter or would get magnified. I don't even know. But but anyway, that that's when a sort
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of a like kind of hitting to contact like putting balls in play actually an ability to do that as a team is really
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helpful. I see Toronto and Milwaukee doing it >> for sure. >> Absolutely. I mean, one of the things we
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noticed about Toronto is that they were just an impossible out. They were I mean, eight, nine pitches, fouling
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things off and often striking out. Yes. But but tiring the pitcher, putting the ball in play. But I will say um so one
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of the things about so two things that caught my eye specifically in the thought around the game first of all is
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how unbelievably awesome Aaron Judge is. Let's get that out there. Um and I just
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noticed he's about the two to one favorite in the betting markets to win the MVP. Um although one of my insiders
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suggested that no Raleigh is going to win it and and it's you can make a strong case for either. I think um
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>> let me ask you a question Audi. Do they do something for the MVP like they do
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for the Hall of Fame or No, there is no pre-bound. It just gets announced. There
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is no >> well there's no prevalence. It just gets announced. That's
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>> just gets announced. Okay. >> And I don't think anybody tells you who
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their vote is. Um but I'm not sure about that. But so it's you know you know
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Judge had a season for the ages, right? So he'll he had a probably about a 10
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war. Um but just a batting line would just which is absurd. >> Feel like we talk about his MVP
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candidacy a lot on this show. It's not worry about it guys. He's your guys'
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regular season champion. Don't worry. >> No no but he had an incredible post. He
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had an incredible postseason and one of the things that we did see was that possibly one of the most
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unbelievably impressive home run I've ever seen hit 100 mph fast ball 4 in inside.
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>> Yeah, that was uh very few very few people could have done what he did there
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for sure >> just to have that kind of strength and speed to bring that bat around and keep
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the ball in in fair uh in such a circumstance. But here's something that I just toss up to you guys. I was
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thinking like what is it? I was thinking to look to see um teams that are explosive in their in their in their
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offense. Maybe that's a strike against them to have to just have this sort of
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large variance in awesome in in offense. So I thought I would rank the teams by their explosiveness which I counted as a
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number of either six or six runs games or more or seven run games or more. I tried both. And then I ranked every team
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one to 30. >> Number of times they scored that many. >> Yes. Right. So it's and and one of the
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things that was struck me as unbelievable this single counting statistic listed the top eight teams.
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I've never seen that that the top eight the eight teams that are currently in
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the playoffs are the eight teams that line up with the statistics with one exception depending on whether you do
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six or seven the Arizona Diamondbacks. Now they have a great part for hitting they were they bounce around the
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Detroit. I mean I'm trying to think like I mean we're not just selecting for high
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scoring team like I I I feel like it's kind of explosive you'd want is are you
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looking at the variance or just like the me like >> just a number just something triviously
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as simple so I would have expected that the eight teams would be in the top all in the top half but they're all in the
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row right here they are clear the way just to follow up on Shane's question what I think you're describing is is
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that let's say the average number of runs per game in the MLB is four and a half or something like that
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>> and so what you're describing is teams that seem to have a lot of games above
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the average amount of scoring and therefore by that definition they're explosive. You don't mean another No,
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I'm saying another way you could define explosive meaning, you know, it's how
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much variance is there in their in their runs per game. What sometimes they're an
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11 run team, sometimes they're a three-run team that averages to seven. Like I when I when I think of the
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Yankees or this kind of like the bad variance that comes with like the three outcome approach is like 3-2 outcome
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approach. It's like you you you know you you you hit an average of like three
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runs a game but it's like zero and seven zero and seven zero and seven zero and
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seven type of thing. And the zeros really don't work well in the playoffs type. So that's so you know
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>> in the regular season that's not it because the Yankees have the fewest
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numbers of two runs or more uh or fewer and they also have the most number of six or sevens. They really had the best
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offense. But I was surprised that by ranking just on an off simple offensive statistic, I I thought that maybe the
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Padres's would be up there or you know other teams that were competitive all
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season long, the Cubs, they um um they just teams that were eliminated top eight.
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>> The Cubs were last Cubs were in it. They were in it, but the the other teams that
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were not um the ones that were eliminated, Cincinnati, Red Sox. Um >> you're not talking about playoff teams,
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though. Yeah. Yeah. Yeah. So they were >> No. I mean, I thought maybe these guys
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would would be Yeah, of course. But other teams, but eight right right there in order. It was just this odd oddity
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that that that I mean it's probably just randomness. But I've been looking for
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some explanation for what leads you to the playoffs. And now secondarily, what allows you to win in the playoffs and I
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think those are different phenomenon. Um getting to the playoffs is almost certainly unbelievable offense. Winning
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in the playoffs, I'm not sure. I think you have to be more Yeah, I think playoffs have to be more kind of a situ
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You you have to have an adaptive situational approach and I guess >> swinging for the fences every pitch is
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that that they're kind of trained to do over the 162 game season. That's I think
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what what I guess goes falls apart maybe for the Yankees specifically or for the
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kind of these three true outcome teams more generally. I mean the Yankees also have defensive pro ongoing defensive
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problems that are >> absolutely well humorous from my side but need to be taken care of. Jeez,
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guys. Since we're talking about baseball, we're going to do a 153015 today where we've been talking open
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lines here uh for about 15 plus minutes. Um we do have a guest today. Unfortunately, he's only audio only, but
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for many of our listeners, um they're doing audio on us anyway, but we're
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honored to be joined by Dan Savorski today. Dan has been on the show before. Dan is a senior writer at something I
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look at quite a bit, which is fan graphs. He's also developer of the Zips projection system. Uh Dan, welcome back
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to Wharton Moneyball. >> Hey guys, how's it going? >> It's going great. Well, not for us
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Yankees and Phillies fans, but in general, it's going great. Um so what before we get into what's even going on
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today in the playoffs. Um could you just tell us Well, I was going to start with
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Zips, but let's forget that for a second. What do you do at Fan Graphs? cuz there's so many of our listeners
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that, you know, want to know continuous time win probabilities, uh, projections.
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What do you do? What do you specifically do at Fan Graphs? >> Well, if if you ask people on social
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media, I ruin baseball with math. That's that that's what I do at Fan Graphs. Uh,
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but but seriously, I do I I've developed the ZIPS projection system, which I've
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used uh for the last 20 years. Uh, I did it while I was at ESPN at Fang Graphs. That that's obviously a big part of what
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I do. and I just generally write coverage from an analytical standpoint. I am a statner nerd and I have been
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since the 80s. Uh and and that's that's pretty much what I do. >> Well, what is why don't you tell us what
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is the uh ZIP's projection system? >> Well, ZIPS is a set of predict predictive algorithms. Uh on broad
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terms, it kind of works a little like weather forecasting tools in a way. The idea of it is to get kind of an idea of
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where a player is and where they're going. uh the uncertainty around the future because the future is very
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uncertain as I can tell you from very very many wrong projections in the past. Uh if you've ever seen like a hurricane
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forecast where they show the little image of the hurricane on the graphic and that cone of ignorance that comes
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out beyond it, that's kind of the same thing that I do, just not quite as sciency as meteorology.
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>> So, can you give us a sense like what are some of the things the ZIPS projection system predicts? Forget
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what's under the hood. forget the actual algorithm itself. Like if I was to go on
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to fan graphs or I don't know, maybe there's a website just for the ZIP's
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projection system, would you be predicting the number of wins of a team? Would you be predicting who's going to
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win tomorrow's game? Would you be predicting who's going to win a series?
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What are the things that you predict with the system? >> Well, generally speaking, the the player
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season aligns uh also in season. There's a a simpler inseason update that can uh
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be run every morning uh by the Fanraft system itself. Uh so what you see if you go into fan graphs you see the
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projection that's kind of the median line. Uh I do when I do the team by team
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rundowns or I write an article uh I get you know the percentiles that things the
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the error the uncertainty uh because there's quite a lot of that uh uh and the idea is just to kind of peer through
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the fog a bit. Uh I also simulate uh teams during the season. Uh that requires a little little more work. I
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simulate the season a million times. uh there's a little bit of linear algebra
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involved when I do a generalized model of injuries to kind of capture that better than our kind of naive depth
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chart projections do. Uh so really if it's something I can logically model then I try to do it. Uh and you know
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it's it's more work than any sort of brilliance on my part. It was mostly
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effort and time. >> AI please. >> All right. Well, let's talk about
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projections and and and also reflections. Um Trent Gisham probably was the biggest surprise of of the
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Yankees year. Um never hit many many home runs in his history and hit 34 this year. And uh so what what did your Zips
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think and what does it think in the future for this guy? It's funny, my editor, one of my editors just wrote an
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article about the Yankees and he asked for the the the the percentile projection that Gisham's season was
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overall and I believe it was the 87th percentile projection. Zips has always kind of liked him quite a bit. Uh when
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we talk about OPS plus that's kind of what we were talking about. Uh but when
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you look at Zip's projection, uh I can slowly open it up and run. >> Wait, hold on a minute. You're saying
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that before the season that his this year's performance would have been in the 87th percentile. This is a guy
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probably never hit more than one home run every 50 at bats. Well, that was for OPS plus generally generally speaking,
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not for home runs specifically, but I am opening it and I'll tell you in a minute
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>> because I mean I I have to say one of the calculations that we did on our show
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early on, I just did a simple binomial, you know, uh p value for his rate of hitting home runs mid-season and it was
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in the it was in the upper tail of the of the distribution, maybe one. And >> you're saying if you used his rate as
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just a P and said, what's the probability under that with I'll make up 300 at bats. you have 22 home runs or
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whatever the number >> it was at least one in a 100 and now it's way in the 1,000s. I mean cuz the
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guy never hit more than just a a handful of home runs a season and I hit 34. I mean wow
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sorry go ahead. >> Oh but one thing to remember of course is we don't actually know the underlying
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probability. This is more of a beta binomial thing than a pure binomial thing. We don't actually know the
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underlying probability of what it is. We only know where he's been. We don't
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actually know how predictive that is as a as a recurring probability of that he hits a home run at any given year.
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>> Yeah. So then the right. So then the question is you know how much weight do
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you put on the you know beta distribution which is you know the prior which you could use just the raw number
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of at bats he has and that as a rate then you could use the current one. So the question is
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>> well no the the question I was doing is just looking at a a t test for the
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difference right is this is he different than last year? You're just using P hat.
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>> Yeah. Is he a different ball player and and uh and that's I mean it just he
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seems to be too inconsistent from what he's seen in the past to be to be to unless it would have to be very use I'm
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going to use my acting as host today and move away from this dreadful Yankee discussion. Dan, let me just let me just
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ask you a general question. It involves the Yankees sort of, but like are you surprised at all if you had
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used your pre-season projections? Are you surprised that the four remaining teams are the Brewers, the Dodgers, the
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Mariners, and the Tigers? And if yes, >> Blue Jays. >> Sorry. Blue Jays.
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>> Yeah, you just >> Blue Jays. >> Blue Jays. >> You had it right for the Blue Yeah. Blue
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Jays over the Blue Jays over the Tigers >> and the Brewers. >> It's the Blue Jays against the Mariners.
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>> Blue Jays. Mariners. Sorry. Yeah, Blue Jays. Sorry. The Mariners beat the
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Tigers. Blue Jays, Mariners, Brewers, Dodgers. Would you be surprised that those were the four teams? And if Well,
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certainly there's probably low probably any sim would have maybe given almost
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zero probability that those were the exact four teams, but what has surprised you about what we're seeing right now? I
00:23:06
guess if you ask from a projection standpoint, Zips is moderately surprised by the exact four teams because like
00:23:14
like most systems and most people, it picked the Dodgers uh to win the NL West, though I should know with a lot
00:23:20
less certainty than most people did uh or projection systems. Zips only projected the Dodgers to have a 73%
00:23:26
chance of winning the division, which is probably lower than most people would have gauged coming into the season. Uh
00:23:31
it projected the Mariners to be second behind the Astros. uh it projected the Blue Jays fourth, but there was a lot of
00:23:38
uncertainty in the AL East projections. There was only uh six wins separating uh
00:23:43
the teams in in the AL East. Uh when you when you talk about the win projections,
00:23:47
it was really really uncertain about what was going on. So, it did think the Blue Jays would bounce back, but it had
00:23:54
him at a 40% chance of making the playoffs. It wasn't going to be the f they weren't going to be the favorite
00:23:59
team to make the ALCS. >> So, Dan, is it fair to say the following? Um, since we're a stats show
00:24:04
here on Wharton Moneyball here on the Wharton Podcast Network, um, since we are a stats show, I can say you're not
00:24:10
saying that the top these four teams, the Brewers, the Dodgers, the Blue Jays, and the Mariners, you're not saying that
00:24:18
it has a high probability of that four tuple. You're just saying it's not that
00:24:23
surprising given the width and the uncertainty of the distribution. Yeah, I think when you look at it, no one team
00:24:31
being where they are is surprising. Uh it's just that these weren't necessarily
00:24:35
the most likely teams. If you asked Zips what the most likely teams uh would have
00:24:40
been, it would have been the Houston Astros. Now, I would have been surprised because the Baltimore Orioles did not
00:24:45
come anywhere close. Uh that is one of the larger projection misses from preseason. Uh the other one, of course,
00:24:51
is the Atlanta Braves. Zips would have guessed that the most likely NLCS would have been Braves versus Dodgers or
00:24:58
Phillies versus Dodgers. Uh, so nothing crazy happened, but a lot of these events were at least moderately
00:25:08
unlikely. >> Let me ask you a question. When you think about, you know, we all try to
00:25:11
measure success of our forecasts. um when you tend to think about the whether it's the you know the zips forecasting
00:25:18
system or more generally what's done at fan graphs like you could say well you
00:25:22
know uh we got the Braves wrong or we got the you know as the Braves didn't even make the playoffs so like do you
00:25:30
think about the mag like as you're thinking about developing your system do you literally think 01 loss like you
00:25:36
know wrong's wrong or do you think wow the Orioles wrong is really wrong >> yeah and actually just to follow up on
00:25:42
that because I was thinking of very similar thing to Eric I think like are there particular teams or like sort of
00:25:47
circumstances like I mean obviously the system's going to miss every year so
00:25:51
it's got to miss something but like you know are there kind of either teams or
00:25:54
types of teams or like is it errorprone in some way that you guys haven't been
00:25:58
able to kind of get at yet? >> We the the the problems tend to be less bias and more accuracy. Uh accuracy of
00:26:06
course is the hardest thing to pin down. Once you've had so much experience projecting things, you kind of can get a
00:26:13
pretty good idea of if there's certain aspects that you're that teams are
00:26:18
systemically being overrated or underrated. For example, if if teams with a high percentage of fast players
00:26:26
is being uh uh consistently underrated, then you kind of have an idea and from the data uh however you choose to do
00:26:32
that any kind of, you know, dimensionality reduction of any kind of model. Uh so there isn't really a most
00:26:39
of these easier lowhanging fruit things have been picked which is why you see most good projection systems tend to
00:26:46
cluster around each other pretty well with accuracy uh because the easy stuff is done and now we're kind of in very
00:26:54
very small difference territory. >> I have a question about but Shane I saw
00:26:57
your hand up please. Well, I guess just to kind of follow up on that cuz I mean I I totally I get what you're saying.
00:27:02
Like I I guess what's burned my question is I I I wouldn't mind your thoughts
00:27:05
from somebody who like looks at the data quite a bit. How are the Brewers doing what they're doing as like, you know,
00:27:10
kind of a bottom payroll team, you know, is like do is there something kind of like that that is it how are
00:27:19
they doing what they're doing? I it's funny that one of the things I because
00:27:24
people ask about this with the Brewers because they're actually the team that's
00:27:26
had the least accurate projections over the last five years uh is that if you look at the team if you look at the
00:27:33
player projections they actually aren't systemically missing uh low on the Brewers but the team projections are.
00:27:41
Uh, and what I deduced, uh, is that the biggest problem with projecting team standings with the Brewers, at least for
00:27:48
Zips, I can't speak for any other projection system, which has had the same problem, is that I am doing a poor
00:27:54
job projecting who the Brewers will actually use. Uh, for example, Zips gave a very positive projection for Joey
00:28:01
Ortiz in his rookie year, but I wasn't convinced that they were going to go allin with him last year. Isaac Collins
00:28:07
had a decent projection this year and I was very conservative about how many how
00:28:11
many play appearances I gave him in the majors. It seems that I'm underrating
00:28:15
the Braves more than the projections are. And that's kind of a problem when you're doing something like team
00:28:20
standings because a a model such as this is not going to be able to really do a great job
00:28:27
figuring out who will play. >> Yeah. I mean, you could have known Andrew Vaughn would go there and do
00:28:32
whatever he's been doing as well. >> Yeah. I mean, perhaps someone can more
00:28:36
accurately model decisions that general managers and coaches are making with with setting
00:28:42
uh the lineups, but that's not something that's in my skill set. At least I have
00:28:46
figured out how to cross those problems with any meaningful way. But Dan, let me
00:28:50
ask you a question that I'm channeling my inner Shane Jensen here, even though
00:28:54
Shane is here. >> So, this is, by the way, the odds I'm about to tell you are before last
00:28:59
night's game. I before last night's game. So, my understanding is the if I
00:29:03
got this right, I even got the team draw. Seattle beat Toronto last night, right? Yeah. Yes. Yeah, they beat him.
00:29:09
Okay. But this was before last night's game. How can you explain any team Shane can jump in after you? The Dodgers
00:29:19
were plus 120. Now, let's all be clear. There's four teams left. That essentially gives them double the
00:29:26
probability of the average team left. How would you explain that? Like does that Dan maybe that seems normal to you?
00:29:34
And the Brewers by the way are plus 850 which gives them like you know 1/8 of probability or 1 nth of probability
00:29:40
which is you know a quarter what they should have roughly or you know how would you explain that and do you think
00:29:46
there's enough precision or is that just way too out of line? Well, of course,
00:29:50
one of the fundamental things is that book makers are also seeking to maximize how much money they earn. And there's
00:29:56
obviously going to be a great deal of correlation between the one true underlying probability, the wisdom of
00:30:01
crowds and and where they set these things. Uh, but all I could do, I mean, is is my work. Zips at least is less
00:30:10
sanguin about the Dodgers. >> But what does it have the Dodgers win probability at right now? Uh right now
00:30:15
it has the Dodgers uh to just to just to get past this round. It only has the Dodgers as 5446
00:30:24
>> uh over that's very different. Pretend like Shane's not here. Shane would agree
00:30:29
with that. >> So they can't have and then the Winter World Series. I don't know. Let's even
00:30:35
give him 54 again. >> Yeah. Actually, Dan, since since you're talking about that 5446 and you've been
00:30:41
doing this obviously for many seasons, is that kind of is that even unusual? Because, you know, you would I think
00:30:46
most people would kind of naively look at the Dodgers Brewers as kind of a mis, you know, just based on persona like a
00:30:52
real kind of mismatch. 5446. Is that about as much as you stretch away from 5050 for like once you get to something
00:30:59
like the conference series or like historically after you've done this, is that like a big spread? I'm working from
00:31:06
memory here simply because I don't have one easy to access spreadsheet but I
00:31:10
don't believe that any of the championship series have been >> at least 6040 or or or if they are it's
00:31:17
been very close like maybe 6139 I generally speaking I mean teams in baseball are very very close it's not
00:31:24
like the NBA uh I can't think of the paper right now who the three analysts who
00:31:31
analyzed best of seven series and the NBA and estimated that for MLB to have the same record of better team advancing
00:31:41
as the NBA did that they would have to play something like best of 76 series. >> I think that was Michael Lopez who did
00:31:48
that. >> Yes, that's it. I couldn't remember. >> He he basically said I mean he's listen
00:31:52
because there's so much more spread in the NBA you have uh you don't need that
00:31:56
many games to resolve who's better but because the the differences in quality
00:32:00
in in any given game in MLB are much more compact. you need way way more more games to to
00:32:06
>> or not even any I mean certainly the spread I mean in any given game I don't
00:32:11
know you'd probably go above 6040 but by the time you get to the conference series
00:32:15
>> selecting for teams where I doubt I mean I'm I'm not surprised to hear 6040 is
00:32:19
kind of the limit of what you kind of differ from the coin flip of course I wouldn't go beyond 40 55 45
00:32:26
>> I'm going to play the game with you Dan that I always do with Audi and Shane so
00:32:30
Dan let me do it with Shane and Audi and and you just listen on and then I'll get
00:32:33
your comments. So guys, we just heard 5446. I'm going to give you another piece of information and you tell me how
00:32:40
this would move things if at all. The Brewers were the best team in baseball. They were. And they had a better wreck
00:32:48
than the Dodgers. That move your probabilities at all? No. All right. How about this?
00:32:52
>> Over over an even schedule? >> No. >> Okay. How about the following?
00:32:57
The Brewers were 6 and0 this year against the Dodgers. No. Audi, is that worth anything to you?
00:33:08
>> Yeah, I think that's worth a little bit. Tiny bit, but a little bit. I mean, the
00:33:12
real question, Shane, is it nothing or is it is it I think it's worth a percentage point.
00:33:16
>> Yeah, I guess. You know, again, when I think about Dan, I want to hear actually
00:33:21
I want to hear what Dan has to say first. >> Dan, what's your thought? Is that worth
00:33:24
any like in the I'm not saying it should. You heard Audi and Shane say if it has something, it's tiny. Is there
00:33:29
somewhere in the zip system that has the fact that the Brewers are 6 and0 this year against the Dodgers?
00:33:36
>> Well, directly no. But that's not necessarily right. That's just something that it's
00:33:42
probably too small for me to model in a meaningful sense because Zips is trying to get the underlying reasons why a team
00:33:48
might be better. But I can't say it doesn't really move it at all because
00:33:51
Thomas Baes will will come back and come out of the grave and and punch me in the
00:33:56
face. >> Right. Of course, it has to move it a little some way. The question is by how
00:34:00
much. I mean, listen, I to Toronto was a beast against the Yankees all season and
00:34:05
they beat them in the playoffs. And I I mean, sometimes that the teams are I mean, we we have a hard time putting our
00:34:11
finger on exactly what it is, but there are different there are archetypes of players and pitchers and game styles and
00:34:18
>> yeah, I guess >> it must matter a little bit and we have some revealed information.
00:34:22
>> If I told you if I told you again, I'm let me frame it a different way.
00:34:28
If I told you that team A was 6 and0 against team B, I'm not going to tell you who the teams are. Team A had a
00:34:35
better record in the regular season than team B. Team A and team B are part of the last
00:34:40
four teams remaining. Team A and team B are playing each other. And team A is plus 850 and team B is
00:34:51
plus 120. You'd be like, there's some to do here. I mean, somebody would say
00:34:57
something about something seems miscalibrated. Dan, let me give you the first comment on this on my simplistic
00:35:04
analysis. I'm stripping off the names of the teams. I'm just giving you the data
00:35:08
from this season. It must be because, and told us this before, if you correlate payroll with winning, it's
00:35:16
very correlated. If you if you look at priors, obviously the Dodgers had a much stronger prior than the Brewers. Is
00:35:23
there some other explanation I'm missing? >> Not necessarily. At least one that I
00:35:29
think that a model can actually meaningfully address. Uh because these generalized models are are very useful,
00:35:36
but again, we're we're talking about all models are wrong, but some models are
00:35:39
useful. Uh and there might be something that let's say there's a particular
00:35:45
style issue that causes the Brewers to have a better record against the Dodgers. Even if we on some level can
00:35:51
feel that, I'm not sure we can necessarily isolate it because it's it's
00:35:55
hard to isolate these reasons for things, it's what I always tell people coming into the season about a
00:36:01
projection is that if a player hits 300 or I project a player to hit 300 and they actually hit 300, I still don't
00:36:07
actually know if I was right. I still don't really know if they were truly that was the underlying probability in
00:36:12
any given atbat was 30%. or if they were actually truly a 27% hit guy who got lucky or a 33% guy who who who showed
00:36:21
real decline. So, you never really know the real answer in a way. I mean, there's lots of
00:36:26
tools to to, you know, evaluate our conditional probabilities, but I don't necessarily think that
00:36:33
it's it's in the gut. I hate to use the word gut, but there's just some little
00:36:39
nudge here and there that models necessarily can't really pick up super well. Let me let me ask you one last
00:36:44
question then we'll uh kind of let you go here. Um what do you see happening?
00:36:48
There's a lot that could be going on in the off season, but like is there any
00:36:52
player when you look at their prior on what fan graphs or the zip system might project for them and now you look at
00:36:59
their posterior cuz the 2025 season, let's forget the playoffs just for a second. The 2025 season is over. What
00:37:06
players if any have moved the most between your prior and posterior? like who like and possibly who may cash in on
00:37:14
that in free agency. They could be those could be independent questions, but I'm
00:37:18
just wondering who have you updated the most. Peter Lonzo has actually improved quite a bit when you look at the he's
00:37:24
kind of arrested a a gradual decline. Uh but it's interesting in a way because I
00:37:30
still don't really have a real good feel. I mean, I've talked to agents on
00:37:34
this issue of just how much his market has recovered. Uh because last year Zips was actually pretty close on the
00:37:40
contract he eventually got with the Mets and I was really really surprised by that. I thought, oh, Zips is going to
00:37:46
miss by like $70 million on him. Uh and it didn't. And I was a little confused
00:37:51
by that because there's certain things you expect to be wrong about when there's the vibes. Uh and I think he's
00:37:58
going to get a bigger contract than he did last year. Also, there's there's no
00:38:01
free agent compensation attached. But when he's talking a seven-year deal as
00:38:06
he has initially, I don't know if it's recovered that much. So, I'm really
00:38:11
fascinated uh to to see what actually happens with his contract this off season. He'll do better, but I would be
00:38:17
really surprised if he got seven years, but I've been surprised before just maybe actually while we have you might
00:38:24
as well get Do you have any, you know, stated projection, maybe you've made it
00:38:28
already on how you see the uh playoffs going? >> Uh yes. Uh, Zips actually likes the
00:38:34
Mariners before before the game. Obviously, it likes it them better now. Uh, right now Zips has them at SE as
00:38:42
Mariners at 7228 over the Blue Jays. Uh, and then the Brew the Dodgers 5446 over
00:38:49
the Brewers. Uh, it has depending on what the matchup is. Uh, if we just look at Blue Jays Dodgers, uh, Dodgers go up
00:38:58
5545. Uh, Zips actually likes the Brewers a little more than the Blue Jays. Uh, but you know, there's a lot
00:39:04
that could go wrong for a team in that 45%. >> Well, Dan, we'd like to thank you for
00:39:10
joining us here on Morton Moneyball. We've been talking to Dan Sorski. Dan is
00:39:14
a senior writer at Fan Graphs, the developer of the ZIPS projection system. Dan, as always, thanks for your insights
00:39:20
and thank you for joining us here on Wharton Moneyball. >> Always fun. Thanks for having me.
00:39:25
>> Welcome back. Welcome back to Wharton Moneyball, the Wharton podcast network
00:39:28
edition. Today's been an interesting show in the way we've taped it. We had
00:39:32
15 minutes of open segments of which Shane was going on appropriately about potential of Drake May and the New
00:39:40
England Patriots. Ai was lamenting as he has a right to about the Yankees and the
00:39:46
high volatility and a little bit about Trent Gisham. And then of course for the last 25 or 30 minutes or so we've had
00:39:51
Dan Sorski on. Dan is a senior writer at Fan Graphs, the uh developer of the ZIP
00:39:57
system. So now we're going to go back for the last 15 or 20 minutes to the open line segment here on Wharton
00:40:02
Moneyball. Um I'll go next. So um I'm going to go to tennis because everybody
00:40:09
knows I love tennis and um this was crazy what happened in tennis. So, just to remind all of our listeners
00:40:19
here on Morton Moneyball, there are multiple levels of tournaments in professional te tennis. Everybody of
00:40:26
course knows the majors, right? There's Wimbledon, US Open, French Open, Australian Open. You might as well call
00:40:32
those 2,000 level events. The reason I'm call I'm not I'm using the number 2,000
00:40:37
is if you win them, you get 2,000 points. Then there's the one that's just below
00:40:43
that of which there's about eight or nine in a year and those are called masters 10,000 events. Notice it's half
00:40:48
but a thousand points is a lot in tennis. Then there's what's called the
00:40:53
ATP 500 events. Then there's even 250 events. Notice I'm having there are 125
00:40:59
events but the major players don't really play in them. Those are the major level events. So, there are players that
00:41:05
you guys know, many players that you guys know that have never won a Masters 1000 event. It's actually quite hard,
00:41:14
especially now, like for 20 years, you are going to have to beat at least one if not more of the big three because
00:41:21
they're all and I'll include Andy Murray and Stan Roinka and other guys because
00:41:25
they're playing all playing the Masters 1000 events. And now, of course, you
00:41:29
have Alcarz and S. And so, that's not going to be easy. and Jookovic is still
00:41:33
playing. So, you're going to have to beat one of those guys. Well, I don't
00:41:37
know, AI, if you saw this. I did not. Okay. What would be I know Shane has. What would be a surprising
00:41:45
ranking? Like, how low a ranking do you think you could get for someone to win a
00:41:51
mass 10,000? Let me just give you a piece of information. Alcarz chose not to play in this one, so
00:41:58
that helps. He did not play in it. He had won just in China. and he won a 500 event in China. Tweaked his ankle a
00:42:04
little bit, decide not to play in this Masters 1000. Dinner played but had to retire in the
00:42:10
second round injured. Bookovich played in the event, but like what ranking do you think someone who could win the
00:42:19
event might be? 20, 30, 50. What do you think? >> All right. So, we actually discussed
00:42:24
this um um not too long ago with one of our tennis guests. Okay. And my hypothesis was that um there's still a
00:42:32
lot of dominance um outside of the top three um relative to the bottom of the a half of the top 20. But the our experts
00:42:41
seem to think that that wasn't the case that you really get um tremendous dominance at the upper top and then it
00:42:47
and then it and then it's it's it levels out. >> So I think probably 20 in a masters
00:42:54
event I would say. Yeah, the number is 204. Oh my god. The guy that just won, Valentine Vashro,
00:43:03
was ranked number 204 in the world. He beat Holgaruna, who's number six. You
00:43:10
may have heard of him. He beat NovakJokovic. You may have heard Yeah, you may have heard of him. And then,
00:43:17
interestingly, he played his first cousin who's ranked about 50 in the world, this guy Render Kanesh. They're
00:43:26
literally first cousins. They're sisters or mothers. They're they played each
00:43:29
other in the finals. Render Kesh had beaten five seated players to get to the finals, but a person ranked 204
00:43:40
won a Mast's 1000 event. Now, let me just say he's now ranked number 40 in
00:43:45
the world, just to show you how much a thousand will get you. And of course, I say this is life-changing, not just
00:43:51
because of the $1.2 million he gets. That's it's twice the amount he had won
00:43:56
in his entire career. The guy's 26. He's not 18. It's 26. It's twice the amount
00:44:01
he had won. But he now gets into every event. So, he gets into every major. He gets into every mast's 1000. He gets
00:44:10
into any 500 event he wants. He doesn't have to go through qualifying, which by
00:44:13
the way, he wasn't even in qualifying for this. Just let me remind you guys for a 128 person event like this they
00:44:22
let usually like 110 people in based on rankings and the last 18 have to play their way in. He was an alternate. He
00:44:30
wasn't even in the list of people that could play their way in if somebody dropped out. They just had some local
00:44:37
guy who was kind of around. >> This would be like a Would this be like an amateur winning the US Open?
00:44:44
like like the analogy like yeah in yeah in golf I'm trying to kind of give an
00:44:48
analogy to like you know because that's something at least we've seen amateurs
00:44:51
come on and >> do well you know like you know I kind of feel like >> I you know I don't know if that's the
00:44:58
right analog or if it's even more rare what just happened is even more rare than
00:45:02
>> you should know Audi no masters events been around for about 30 40 years this
00:45:05
is the lowest rank to ever win >> right so I I have two remarks first of all golf has more variance way more
00:45:10
variance than tennis there's I mean you have the putting randomness which is unbelievable uh and
00:45:16
and can make a huge difference. So um I would have imagined that amateurs have won made professional tournaments in
00:45:22
golf every rarely but every now and last amate there >> this is the US Open though.
00:45:27
>> Yeah there have been amateurs that have won professional golf events but I don't
00:45:32
think if an amateur's ever well Bobby Jones in 1920s won the major >> No. Yeah. I mean I more recently I feel
00:45:37
I feel like every every few years there's an amateur that like I mean of course the amateurs aren't going to be
00:45:42
playing in the Masters or whatever. It's kind of you know it's the conditions for
00:45:46
this to happen are >> the person that wins the person that wins there is an amateur championship
00:45:51
>> that person automatically gets to play the Masters. So actually there are and
00:45:55
there's like a couple others like I'll make it up the South American amateur
00:45:58
champion. There are three or four people that amateurs that do get to play the Masters every year. So the real question
00:46:05
about about this is what as a post let's be bas what's my posterior I would
00:46:11
imagine that something we misranked him in some way. >> Yeah. Well that's that's I was going to
00:46:15
ask like what was his trajectory before he got to 204. I don't know how far the
00:46:19
but if this guy was just on crazy ascent or something. >> So he'd been playing for years and yet
00:46:24
he's still I mean this doesn't make sense. Tennis is a game with lots of
00:46:28
ladders of of levels of of quality. 204 is nothing like a 50 usually nothing like and 50 isn't like 10. So that's a
00:46:42
lot of ladders to jump. And so >> I tell you I'm reading it right. This is
00:46:46
look it's we I know you guys have some skepticism of AI which you should but
00:46:50
let me just here's some data from AI. So um he's increased steadily in January of
00:46:56
2022 he was in the top 500 in the world. Then in January of 2024, he was in the top 200 in the world. And then by May of
00:47:05
2024, he had reached 116. That was the highest he had ever gotten. Then he slipped back down to 204 because of
00:47:12
injuries. So that's it. That's his That's his entire All right. Well, at least he had been
00:47:20
one 116 and he had a pretty strong improving trajectory which was set back by injuries. So you
00:47:26
>> Yeah. Maybe maybe he just had like a long-term kind of crime like some kind
00:47:29
of injury like we're looking at him post some like correction that really made a
00:47:34
huge difference. >> I know you're doing something that a good basian would do which is that look
00:47:38
we can't refute the data. He won. Now the question is what's an explanation
00:47:43
for it? You've given a couple. One is the distribution of talent is really really flat. We don't really believe
00:47:48
that but that is one possibility right? Another possibility is his true ranking is not 204 and that you know had he not
00:47:57
been injured for part of 2025 maybe he would have been 50 or 60 in the row. Now that still would have been unlikely but
00:48:03
not the four sigma unlikely or more we might be talking about here and this is what scientists do. You you you you come
00:48:10
up with alternative hypotheses some of which are more plausible than another. And this one seems quite plausible. Can
00:48:17
I can I ask a sample size question in tennis, Eric, cuz you know these ranking systems better. Like how many now
00:48:23
tournaments in a row of like first place like first first round exits would he have to pile up? You said he's now at 40
00:48:30
or somebody said he's like at 40 in the world now >> to get to to knock him back down to 200.
00:48:35
How many bad performances does he like how how much was this performance worth and kind of like and sort of in the
00:48:41
almost like I guess the inertia of the ranking system? >> Well, I'll tell you I'll give you an
00:48:45
example right now. That's a great great question. Here's what I can tell you
00:48:48
with certainty. He cannot go below for the next year. Let's assume that the number of points are fairly stable
00:48:57
across the different rankings, right? So, um he pretty much can't go below about 50 in the world or 55 because
00:49:08
that,020 points he has stays on for a year. So even if he gets zero zero zero zero zero zero and remember he's going
00:49:18
to have he's not going to play 51 weeks but he's going to have that many weeks
00:49:23
of opportunity to get I mean cuz he's in every tournament he wants to play. So it
00:49:29
would take a long time now for him to drop cuz that it just happened and it stays on for a year. He's gonna he's
00:49:37
he's changed. That's what I meant when I said he's changed his career. Like even
00:49:40
if he has a bad year, he's probably going to stay in the top 100, which will
00:49:45
also get him into tournaments for another year. And I hate to say it, the guy's 26, he ain't 18. You know, maybe
00:49:51
he's not. Yeah. Everyone says, "Well, Jookovic plays till he's 38." Yeah,
00:49:55
right. Okay. Well, Pete Sampas played till he's 31. Most players are done by
00:49:58
27, 28. This guy has changed the last three or four years of his career, for sure.
00:50:06
And that's amazing. Please. >> Uh yeah. Well, I was actually one of the
00:50:11
things we actually kind of touched on it a little bit. Um that the tennis ranking
00:50:15
systems in particular have a lot of uh sort of built-in randomness that are due to, you know, decisions to play certain
00:50:23
tournaments and not play them. They're not really what we would call power rankings. Um which
00:50:29
>> they have both. They have they have the live rankings which tend to have a
00:50:32
smaller window to them and then they have the one that I just described to Shane where the points stay on for a
00:50:38
certain period of time. >> Right. But I'm I'm curious to know what
00:50:42
like what >> like what an ELO system would do. >> Yeah, an ELO system or or or just
00:50:47
someone's power ranking a regression based uh forecast that says this is how
00:50:51
good we really think you are. And I would I would imagine that his 204 was quite probably quite different from what
00:50:57
his power ranking or ELO based or whatever system >> like what residual would that have in
00:51:01
like an ELO or something like that. Yeah. No, that's a great question. >> And this is actually interesting because
00:51:05
this is one of the problems with these systems is that um it it sometimes takes into account lack of play um or a new
00:51:14
player when he comes online, we don't know what to do with him, so we give them often a very low score. Well, here
00:51:18
I can tell you right now again this is not I I can't see the number based before this tournament but I just went
00:51:26
to the ATP rankings which is an ELO based system tennis abstract.com. I've talked about them before. Um it has
00:51:33
Vashiro this guy at number 43. Now that's not very far from his other ranking but how far that move Oh, let me
00:51:42
click on his name. Let me see if it has a time series and like like let's see
00:51:45
how far it probably does. Hold on a second here. Well, it I if I'm reading this right, I
00:51:54
may be reading this wrong. Fans here on Morton Moneyball. No, it had him at 204.
00:52:00
It had him like at 200. I assume. Oh, I don't know what. Let me I I don't know
00:52:04
what V rank is. So, maybe this is different. Maybe his rank was different before this. Oh, I see. So, it's
00:52:12
actually changing his ranking. Oh, this might be his opponent's rank. I think these are his opponent's ranks.
00:52:19
Yeah, no, no, sorry. That's just who he beat. Well, let me just tell you according to the ELO system in the round
00:52:24
of 64, right? He beat the 82nd player in the world, then 17, then 23, then 31, then 11, then five, and then 54.
00:52:37
>> That's not bad. Like what what again? Player A, player B. If one was at at 20
00:52:42
and one was at 200, what would you say the odds were for a single match? >> 95% at least.
00:52:50
>> First thing that came into my mind was 99%. I would say 2% chance that the
00:52:54
200th player in the world beats crazy. >> There's no way he was a he was a go into
00:52:59
that >> tour. But we we we've we've definitely the null hypothesis that he's a right
00:53:05
>> Well, that's what I was about to say, Shane. All for our listeners out there,
00:53:08
Audi's computing the P value under the null. Audi does not believe, as he said
00:53:12
many times in 11 and a half years, a one in a million events happen. And so there's no way the 200th ranked player
00:53:19
beats five, six players in the top 20. Not no way, but like with very very small odds. Therefore, you have to then
00:53:27
say maybe the null of him being 200 is just not true. >> Yeah. I mean the question is is it
00:53:34
should you have revised it in the middle of the tournament right I would have >> well that's well that's another thing
00:53:41
>> certainly advance after that first round or something like that also once he beat
00:53:45
Djokovic at that point you know I don't know I mean I understand Jookovic has
00:53:48
good days bad days but even the bad Jookovic is still pretty darn good and so >> you know so Eric let me ask you a
00:53:54
question because you go to a lot of tournaments and watch a lot of tennis um are you able to see with your eyes when
00:54:03
you're watching two players that one is substantially better skilled than the
00:54:08
other as opposed to just looking at the score. >> Yeah, it's a great question. Let me tell
00:54:13
you what you can tell. You can tell a lot about who's hitting the ball harder
00:54:18
because you a it's just the speed off the racket. You can also hear the difference. Like that's what I do, Audi.
00:54:24
Sometimes I'll close my eyes and I'll try to guess which side is hitting the
00:54:28
ball. You can see that. What you can also see and this is where I can see that Jookovic I understand now I look we
00:54:36
can get tennis experts at some point we're going to have Paul Anakone on he would answer this as well one thing I
00:54:41
know for a fact and the data would suggest this that Jookovic is doing worse is what they call getting out of
00:54:47
the corners which means player a different his opponent hits the ball deep into the corner historically
00:54:54
Jookovic would stretch hit the ball back and be back at the tea be back at the center he can't get out of the corners
00:55:01
now because for him to stretch out far enough to get to a ball. By the way, same is true for squash. The the best
00:55:08
players get pinned in the corners but come out of the corners fast. Jookovic just at his age now. It's movement. It's
00:55:16
not that he can't hit the ball hard and it's not conditional on him getting
00:55:20
there. He doesn't hit as good a shot. He does not get to the ball. He's a step
00:55:24
slower out of the corners and that means everything in the world of tennis. The answer is yeah. That's the wonderful
00:55:30
thing about tennis. There's things you can do that um at the live event, you
00:55:35
can tell who's hitting it harder, you can tell who's moving better, you can
00:55:38
tell who's able to recover from being in a defensive position more. All of that
00:55:43
is available and motion tracking data would be able to answer all of that. Well guys, it's been kind of an hour
00:55:50
here on Wharton Bunny Ball and the Wharton podcast network. Uh it's been a great show today with 15 minutes of open
00:55:56
segments. Um, I don't know how much baseball we're going to be talking about
00:55:59
now since we know the Reds >> Oh. Oh, yeah. Phillies knocked out. You're not going to be paying attention.
00:56:05
I'm going to be talking baseball for the next couple weeks. >> All right. Well, we we'll talk some
00:56:09
baseball, but I think we got to talk some NFL today. We got to talk about the Patriots. We didn't even get to talk
00:56:14
about the 5-1 Bucks who absolutely beat who have the best quarterback in the NFL, Baker Mayfield. Right now, we
00:56:19
didn't get to talk about that, but we got to talk with Dan Savorski about the
00:56:23
zip system and projections for the season. We got talked about tennis. So, lots of great stuff. So, on behalf of
00:56:28
myself, Eric Bradlo, on behalf of my co-host today, Shane Jensen and Aie Winer, on behalf of Kate Massie, who
00:56:34
will be back next week. Thanks for joining us here on the Wharton Podcast Network here on Wharton Moneyball.
00:56:40
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