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Welcome, welcome to Wharton Moneyball.
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Welcome to a full hour of sports
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analytics here on the Wharton podcast
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network. This is Kade Massie hosting
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this week with the whole crew. I'm
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looking at all my longtime buddies and
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collaborators here on Wharton Moneyball.
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Shane Jensen is here from his living
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room. Not his living room, his office.
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Eric Bradlo from his home office. Audi
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Winer, the only one of us being a
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responsible Wharton faculty member on
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campus this afternoon. I'm coming. I'm
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coming to you meetings here all day.
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That's
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>> good. Good for you, Odd. Good work. Good
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work.
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>> Appreciate you sliding in here.
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Everybody's sliding in here late in the
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afternoon on Tuesday as we usually are.
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The show will go up first thing on
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Wednesday. We're going to flip it today.
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We're usually guest in the first half
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hour. This week, we're going to go open
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lines in the first half hour. And all
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goes according to plan. and we'll have a
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guest slide in here about halfway
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through the hour. Gentlemen, uh a lively
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lively moment in the sports calendar, I
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would say. We've got base basketball and
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hockey wrapping up about to kick over to
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the postseason. I mean, right now we're
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in transition. We just came through the
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best golf event of the year, at least in
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non-Riter Cup years.
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Um Audi has excuses to think about
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nothing but the Yankees 23 and a half
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hours a day. So full full-blown um why
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don't we just open it up for why don't
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we first start with the Masters. Let's
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give the Masters its due. Um it's one of
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the majors, but it's kind of the major.
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Um it feels like the official It is the
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official kickoff to the major season in
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golf. Um we had a pretty good go this
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weekend. Observations coming out of
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Augusta.
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>> Couple things. Um, first I was a little
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surprised that first let's start with
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the first 36 holes. I was surprised
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actually that Rory Maroyy's six shot
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lead was the highest ever after 36
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holes. I just would have thought that
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somebody would have gone out and shot,
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you know, low 60s in maybe both rounds.
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Maybe there would have been a larger
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lead. So that was the first thing that
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surprised me. Um, for the last two
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rounds, something happened. Forget that.
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We'll get to the winner in a second,
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which was Mroy. Um, Scotty Sheffller was
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the first person in 84 years to not have
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a bogey on the weekend of the Masters.
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>> Isn't that amazing?
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>> Which was incredible, which is partly
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why he caught up 11 strokes. He needed
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to catch up 12.
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>> Yeah.
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>> But he caught up 11 strokes over the
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weekend.
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>> Um, so that's pretty impressive as well.
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Um, that's actually kind of cool that we
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now have kind of an empirical measure
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for like how much you can that's that
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you can like move that far just playing
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bogey free golf specifically.
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>> Well, he also had 11 birdies obviously,
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but no eagles, but I'm just saying
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>> the 11 birdies help as well. Um, but
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yes, that was impressive.
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>> But the thing I thought about and this
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is what I put in the rundown.
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So, we look, I can't take back what I
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said in history. There was probably no
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athlete I've been more critical over the
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last 10 or 11 years for his
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accomplishments
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between majors in this case. I mean, I
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just could not believe it. And Roy Rory
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Maroy won something like 20 something
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tournaments,
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including the players multiple times,
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which is, you know, the fifth major they
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like to call it, player of the year
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honors, and hadn't won a major in 11
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years. Now,
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everything about his career narrative
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has to change. I mean, let's start with
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the fact that he's only the fourth
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player ever to win backto back at the
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Masters. Nicholas, then Faldo, then
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Tiger. It's not bad company. Number two,
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last year, of course, he completed the
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career grand slam. Very few people have
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completed this the career grand slam. I
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think it's I mean Nicholas obviously
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Woods player I forget if it's Sneeed or
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Sarzen somebody like that but I mean
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name a lot Tom Watson doesn't have a
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career grand slam lot of players don't
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have career grand slams. Um he now has
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six majors which ties him for the most
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by any European player ever. That's Nick
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Faldo. Faldo has three masters and three
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British. Um it ties him with Phil
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Mickelson, Lee Trobino. So, I'm starting
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to ask myself like whose career would
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you take right now? Would you take Mroy
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or Faldos or Mickelson or Trovos?
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And if he wins one more, he'll have the
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same as Arnold Palmer. That's not too
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bad. Um, he'll have the same Well, Bobby
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Jones didn't play a full career, but I'm
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just commenting that, you know, he's
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starting to get, you have to call him
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now in one of the top 10 maybe golfers
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of all time. And if he wins two more,
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then he'll pass all the seven people.
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He'll tie Tom Watson. And but Tom Watson
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doesn't have the career grand slam
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either. I don't know. He's getting up
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there. That's
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>> And then I want I have a separate you
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guys, which I I put some thoughts in the
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rundown, but
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>> Well, hold on, Eric. Hold on. Stop there
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for a second because there's a lot to
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you've given us a lot to react to. Um on
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the on the small, I was a little
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surprised that only four guys have
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repeated as champions. is that that
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there must be a statistical property
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there that I don't have a good intuition
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for because and they're and they're
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pretty well spaced as well. I mean
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Nicholas in the 70s, Faldo in the '90s,
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Tiger was pretty quick after Faldo, but
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it's been 25 years since anybody or 24
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or something like that. So, it's really
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more rare than I would have expected.
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Well, so that I love the question
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because you know Audi could probably
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speak about this better than any of us
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or Shane, which would be you know what
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are the statistical properties of
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performance that would lead to that. So
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one is obviously not huge mean
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differences or mean differences that
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don't persist over time.
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>> You mean between player between golfers?
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>> Yeah, for one single player or between
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players. Second is that um there's a
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huge amount of variation and so there
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could be mean differences but you know
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randomness over 72 holes dominates and
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so it's pretty hard to be good in two
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consecutive years. A third is that a
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year is a long time frame in golf that
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would be like if you played the Masters
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again next week if that was the way the
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Masters worked in successive weeks
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instead of successive years my guess is
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it wouldn't take 25 years at all to get
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a repeat champion. talked about this
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locked in factor. So, I love the
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question because it allows you to think
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about the properties of performance that
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would lead to something that on the
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surface seems how is that possible?
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>> That's great. That's great. I think you
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named three very important properties
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there. I know those things about golf.
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>> I would love to kind of norm it like by
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like just for tournaments in general
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golf tournaments. How many times do you
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see back-to back winners? I mean,
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thinking about like I feel like the
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Masters almost should have among among
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golf tournaments more backto back
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winners because it's a smaller field
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though a very competitive one. It's the
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same course every year. Yeah.
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>> So something like the British or US
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Open,
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>> especially the US Open, it moves around
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so much stylistically. I feel like year
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to year that would presumably induce
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like you like I could almost expect less
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backto-back winners of the US Open than
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the Masters. And I I don't know if we
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could kind of get more of a sense of
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what that distribution of back-to-back
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winners looks like in golf in general
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from looking at other tournaments. I
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feel like the Masters should be kind of
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on the higher backtoback side of
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>> I want a second second ch I think S's
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exactly right in these two qualities.
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Well, it's the smallest field. One of
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the things one of the for years one of
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the reasons we thought that the PGA got
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fewer famous champions was because they
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have the biggest field and the Masters
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has the smallest field of the major. So
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that's just matters more than you might
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than you might think.
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>> Shane, I'll give you your answer right
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here. So the Masters we know the last
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time was Tiger in 2001 2002.
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>> In the PGA it was Brooks Kepka 2018 and
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19. The US Open it was Curtis Strange in
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88 and 89.
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>> And in the Open Championship, I could
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give you guys a million guesses and you
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wouldn't get this one. That means it
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predates
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>> Patrick Harington in 2007 and 2008.
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>> Oh, look at that. Yeah. Yeah.
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>> I probably wouldn't have guessed that,
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but I had some that that that would have
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been a candidate. Yeah. Interesting. Um,
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>> so I think Shane's really good with the
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US Open explanation. I mean, look, these
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are small samples.
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>> 40 years almost.
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>> I like that. I mean, that's right. Yeah.
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No, I I Right. I guess and I would you
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guys agree? I mean, the British Open
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does move course to course, but I think
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stylistically doesn't
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>> it's tighter than it does change, but it
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doesn't change as much as the US Open.
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That's fair. That's fair. I want to make
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one other Oh, Audi's trying to get it.
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>> Yeah. I mean, I just have one thing to
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contribute on this discussion um about
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backtoback. One of the facts that I do
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know about golf because I did the
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research on it. We've talked about it
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here before is that putting is the most
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most uh significant component of the
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game and to predicting your win in a
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tournament, but it's the least important
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when predicting future tournaments. It's
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I love this fact. It's just a great
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>> So be careful. I think you misused the
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term predicting the first time you used
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it. So when I if I want to know who won
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the tournament, the single most
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important factor is who put it better
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than than they're expected to.
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>> Fact. So descriptive. I would say
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describe who won the tournament.
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>> Describe who won. You want to know how
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how did this tournament play out? When
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they say putt for for dough, they mean
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it, right? It it really means it's a
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it's it's
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>> it's a driver of the result, but it's
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not consistent,
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>> but it doesn't predict the future.
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meaning the actual skill variation.
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There's a little bit of variation, but
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it's absolutely minuscule compared to
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the skill variation and the standard
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deviation on a on a on a on a on a
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stroke level for the other components
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for the approach shots and and T- shots.
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>> Let's just name the analoges to that
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across sports. The most obvious one is
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goalending and hockey. It seems to me
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it's almost exactly analogous.
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>> No, that is a great analogy. I feel like
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in both those properties cons lack of
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consistency as well as kind of driving
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driving the route but only kind of
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retrospectively
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>> turnovers in football,
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>> right?
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>> I would I agree, Eric, but that one
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doesn't seem like it should be
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skill-based. That's the one that we
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Yeah, some coaches act like it is and
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and somebody probably tell us it it can
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be trained, but mostly people recognize
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the way the ball bounces is kind of
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chance event. Let me just I want I want
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just to comment about the the we just
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finished our our high school um data
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science competition which was on hockey
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which Shane and I judged yesterday. The
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final um presentations were terrific,
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the top five. Um but the the
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interesting kind of twist that we did
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was we made goalending a very big and
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significant factor and they had to
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discover that. um we didn't actually
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just we didn't show them um we gave them
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goals we gave them expected goals and
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they had to create some metric metric on
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their own and the winners did that um
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but so many of the submissions didn't
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but then the question that came and then
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we had some we had some judges who were
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were with uh professional hockey teams
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and of course Shane and I haven't done
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the research on this so it's clear that
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goalending is similar to putting in in
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so far as it um it really describes what
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happened um but it's not nearly as
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useful as predicting what will But I
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think it's a little stickier than than
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putting. But then this is a question I
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don't know the answer. In other words,
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within a season goalies I think they get
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hot and they kind of stay hot, but then
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they don't really it doesn't go to the
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future. But I'm that's a hypothesis. So
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I'm not going to stand by that as say
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that's truth. Um but uh but but and
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that's a question I really like to get
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an answer to. Uh Shane, do you know an
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answer to that?
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>> Well, I mean I think it's my my not not
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an empirical answer. My intuition is
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it's sticky in the kind of shortterm
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game to game sense that Eric would be
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very tempted to call it momentum at any
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like instantaneous point in time. Right.
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>> But but I think like you know once you
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start expanding out to like oh this
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goaliey's hot this season that's not a
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guarantee they're hot in the playoffs
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you know type of like like I don't think
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it's kind of like you know they're they
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are kind of I I wouldn't want I wouldn't
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necessarily predict for example goalie
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performance in the playoffs based on
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their regular season performance even or
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very strongly. I mean, you're sort
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you've already selected out maybe
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there's a
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>> actually something that I want to
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research um because it's something that
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I think could really be similar exactly
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the same as the putting uh which you've
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really thoroughly investigated or it
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could be something similar to the
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pubbing maybe a little little stronger
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um individual variation. It'd be fun to
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put next to your research on putting
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Audi. That'd be great. Um,
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>> yeah, I can just tell you what. I mean,
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this is the kind of thing, like it or
00:12:50
not, this kind of thing you can type in
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the chat GPT. So, I'll just tell you
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what it says. It says that golf putting
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has higher serial correlation across
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rounds than hockey goalending has
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across. Now, it's looking at across
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seasons. I If you give me 10 seconds, I
00:13:08
can I
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>> So, hold on. I'm Hold on. Let's let's
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stop let's stop it there because I've
00:13:12
been working enough just in the last
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week with these kinds of analyses to not
00:13:17
trust it until we go much deeper and
00:13:19
let's not go hold on let's not go much
00:13:20
deeper at this moment.
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>> It's but this is an immediate response
00:13:24
and this is relative to to golf. Cut it
00:13:26
measure how many strokes as opposed to
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strokes gained very correlated because
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players have a huge important impact on
00:13:33
where they land on the green. um right
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effects. And so if you just look at like
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putting it that's correlated, but it's
00:13:41
it's broken that matters.
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>> Okay. And we're going to stop that one
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right there and we'll we can take that
00:13:48
up offline if we want to. I do want to
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say one more thing about Rory because
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when you look at that list of uh
00:13:55
all-time major leaders in golf, he is at
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six. when you move into which is a great
00:14:00
place to be phenomenal obviously but you
00:14:02
move into seven you move into legend
00:14:04
legend territory that's the Arnold
00:14:06
Palmer Sam Sneed um
00:14:11
uh Bobby Jones you mentioned Bobby Jones
00:14:14
somebody else is in there it's like
00:14:15
>> Palmer
00:14:16
>> yeah Palmer's in there and you know so
00:14:18
he one more and he's in solid legend
00:14:21
territory but guys he's young and
00:14:24
playing pretty good I want to ask a
00:14:25
question we always ask on this show
00:14:27
which is what's your forecast for
00:14:30
lifetime majors for Rory. If you if I
00:14:33
set it at if I set it at Well, I if I
00:14:37
set it at seven and a half,
00:14:40
what are you going to do? Over under.
00:14:43
>> Can you remind me of Rory's age?
00:14:45
>> He's 36.
00:14:46
>> 36. 36. Wow. Okay.
00:14:50
>> But remember, like guys are winning
00:14:53
majors. Let's just say I don't call it
00:14:56
his prime. Maybe this is his prime.
00:14:57
probably not, but let's say it was. He
00:14:59
certainly has six to eight more years of
00:15:02
being heavily competitive in majors just
00:15:04
based on age curves in golf. And that
00:15:06
doesn't mean, by the way, Phil Mickelson
00:15:08
won one at 50. And let's remember Tom
00:15:11
Watson was a six-footer away from
00:15:13
winning one at age 59.
00:15:14
>> Yeah. But but I I but I do think those
00:15:16
age curves have changed how we view like
00:15:19
back back in time. Like Nick, when
00:15:21
Nicholas won at like 45, that was like a
00:15:25
legendary moment. Now a 45 year old
00:15:28
would still be I think over the you know
00:15:30
would be still unusual but not that kind
00:15:33
of crazy moment like I think players are
00:15:36
playing longer at at higher levels
00:15:38
>> for for sure. I mean we don't have to
00:15:40
look past this past weekend Justin Rose
00:15:42
could have won the tournament.
00:15:43
>> Absolutely.
00:15:44
>> He's 40 45 years old.
00:15:45
>> Strokes to go. Seven holes to go.
00:15:48
>> Okay. So I'm giving you seven and a half
00:15:51
>> over.
00:15:53
>> I think I'd have to take over given his
00:15:55
age as well. Yeah.
00:15:57
>> Yeah.
00:15:57
>> I mean, I'm just thinking let's say
00:15:59
>> only two more. I'm two more.
00:16:01
>> I'll just say he's got I'm making the
00:16:03
number up. Set conservatively 30 more
00:16:06
majors.
00:16:08
>> Well, no. No. He's going to play more
00:16:09
than that. But let's say
00:16:11
>> competitively
00:16:12
>> competitively 30 more. Can he win, you
00:16:16
know, 7% of those one every two and a
00:16:18
half years? I mean, let's say he plays
00:16:20
Major for another seven, eight years.
00:16:22
Eight, let's say eight years, round it
00:16:24
and say eight years competitively. Can
00:16:25
he win one major every four years? I
00:16:28
think he can.
00:16:30
>> Yeah. Yeah.
00:16:31
>> By the way, just so you know, he, you
00:16:34
know, he's the second favorite for the
00:16:36
next probably I'm making it up five
00:16:38
years, but I'm going to say this. Over
00:16:39
the next five years, he's probably the
00:16:41
second favorite in every major after
00:16:43
Scotty Sheffler. I mean, they've already
00:16:44
done four casts for the next four. And
00:16:47
Sheffller's won, and Maro is very close
00:16:49
at number two.
00:16:51
>> Sure. I'd love to get the denominator on
00:16:53
the number of times we could have had
00:16:54
this conversation though like that
00:16:57
somebody's gotten to this level like
00:16:59
like
00:17:00
>> I mean it's
00:17:02
>> Brooks Kepka Kepka's most recent if we
00:17:04
if we after he got his fifth if we got
00:17:06
his fifth what would we have said we
00:17:08
have said oh
00:17:09
>> seven seven eight
00:17:10
>> he's got five
00:17:13
I'm sticking with my over don't get me
00:17:14
wrong I just you know I feel like
00:17:16
there's some cautionary tales somewhere
00:17:17
in the background there
00:17:19
>> by the way just you know kept of
00:17:20
comparable age. I might let's assume for
00:17:22
the moment that maybe one of them's a
00:17:24
year older. I don't know. Let's assume
00:17:25
they're of comparable age. So Kepka's
00:17:27
got five and Maroyy's got six. We have
00:17:29
no trouble potentially saying Maroy is
00:17:32
going over seven and a half. What if I
00:17:33
said six and a half for Kepka? I don't
00:17:35
think anybody here's taking the over.
00:17:37
>> No, but they're playing at a very
00:17:39
different level and have been for a
00:17:40
while.
00:17:41
>> Yeah. So, so I mean Roy is number two in
00:17:44
the world according to I think anybody's
00:17:47
my kind of my belief for them to win
00:17:49
compared like win win win majors like
00:17:51
goes up like super linearly with the
00:17:54
number they win win win or something
00:17:55
like that
00:17:58
>> M I'll give it to you Mr. Texas. Our boy
00:18:01
Scotty's got four.
00:18:03
>> Yeah.
00:18:04
>> Over seven and a half right now.
00:18:06
>> Yeah. So, what do you do with that? Just
00:18:07
let help me think think it through.
00:18:09
Definitely. He's he's a little
00:18:11
>> 29.
00:18:12
>> I want to say he's off his heater, but
00:18:14
he was still right there, man. He was
00:18:16
just right there. And he's he hasn't
00:18:18
been playing as well lately. So, despite
00:18:20
not having his played as well lately, he
00:18:22
was one stroke away. Um, let's just go
00:18:26
walk through the same logic. Let's give
00:18:27
him 15 years. So that's 60 more.
00:18:30
>> I'm going to give him a few outs for
00:18:32
injury. Let's call it in the low 50s or
00:18:34
so. Uh Tiger at his best hit 25%, but
00:18:38
that wasn't for very many years. Let's
00:18:40
give him I mean 10% still a very high
00:18:43
number. 8%.
00:18:45
>> We're talking about four more over.
00:18:48
>> Um if so, so if you had to pick a number
00:18:51
for Scotty with four already in the bank
00:18:54
at 29.
00:18:55
>> Well, who would you rather be? How about
00:18:56
this one comparison? Would you rather be
00:18:58
Sheffler at 29 with four or Macroy with
00:19:00
six at 36?
00:19:01
>> There you go. There. Now we have an
00:19:03
interesting horse race. That's like the
00:19:04
thing they do at baseball games where
00:19:06
they put they let the kid run the the
00:19:08
outfield wall and they start they start
00:19:10
him out and they they have a fast guy
00:19:11
wait for him to get halfway there and
00:19:13
then the fast guy catches him. Um, who
00:19:16
do you want, Scotty or Rory?
00:19:17
>> I think I would take Scotty.
00:19:19
>> I think he got to seven years to get
00:19:21
two. Seven years to get two. though Rory
00:19:24
is really playing well. So he Scotty
00:19:26
might not arrive at 36 playing as well
00:19:28
as Rory's playing right now. But Rory
00:19:30
went through a 10-year drought, you
00:19:32
know. So I think he I think he takes
00:19:34
Scotty, but now we're talking about
00:19:36
Scotty at like now we're going to put
00:19:38
him up in the he's going to pass Palmer.
00:19:40
We all think he's going to pass Palmer.
00:19:41
That's pretty strong.
00:19:42
>> Wait, so Rory went through 10 years
00:19:43
without without
00:19:45
>> That's unbelievable. Went from age 24,
00:19:47
Audi, to 35 without winning a major. And
00:19:50
>> now he's won two.
00:19:51
>> Correct. The Masters two years in a row.
00:19:53
>> Yeah.
00:19:54
Okay, guys. We should stop golf. Got to
00:19:56
throw out anything. What do I chop liver
00:19:58
here?
00:19:59
>> Well, you went I didn't know I thought
00:20:00
you kind of timed out on the golf thing.
00:20:02
>> I did. I want I'm going with Sheffler.
00:20:05
There you go. No, no. Uh, no. No
00:20:07
questions asked.
00:20:08
>> No questions asked.
00:20:09
>> Hey, can I ask my other question about
00:20:10
who's changed their arc of their career
00:20:12
as much in a one-year period as Mroy now
00:20:16
has? Cuz remember like two years ago or
00:20:19
sorry 370 days ago
00:20:23
Rory Maroy was the great prodigy who
00:20:25
burned out at age 24 and now we're
00:20:29
talking about him potentially passing
00:20:30
Arnold Palmer and Ben Hogan or Sneed or
00:20:33
whoever these you know all these guys
00:20:35
was seven. Well, you know I put some
00:20:38
names down there but I don't know you
00:20:40
know I remember the time when Jordan
00:20:42
couldn't win the title. you know, he
00:20:44
came into the league in ' 84, 85, didn't
00:20:46
win a title till 91,92.
00:20:48
So, I mean, you know, I remember that. I
00:20:50
remember when Yvon Lendle couldn't win a
00:20:52
major. He ended up with eight, but he
00:20:54
lost his first four.
00:20:56
>> I remember when Chamberlain couldn't win
00:20:58
the title. Seven straight losses to
00:21:00
start. No, I'm just saying I don't
00:21:01
remember Chamberlain. Okay. Looking at
00:21:04
this, I remember when the Red Sox and
00:21:06
Big Poppy, I mean, he won. He won, but
00:21:08
he won his seventh year. Okay. I got I
00:21:10
got I got one. I got one.
00:21:12
>> Titles change the arc of their the way
00:21:14
they're perceived.
00:21:15
>> I got one. I think that's better than
00:21:16
all those.
00:21:17
>> Okay.
00:21:18
>> Elway.
00:21:20
>> Elway is pretty good.
00:21:21
>> He didn't have a Super Bowl until he was
00:21:23
about 53 and then he got a couple there
00:21:25
at the very end the last two seasons he
00:21:27
played. So he came in number one draft
00:21:29
pick in 1983. I don't think he won a
00:21:31
Super Bowl until the mid 90s. And people
00:21:34
he was always Yeah. I mean, man, Manning
00:21:37
kind of had a similar sort of arc, but I
00:21:40
guess Manning won like his first at
00:21:42
least had success a little like more
00:21:44
mid-career as opposed to like like
00:21:46
you're Elway was really quite close to
00:21:48
the end that he completely turned around
00:21:50
the narrative, right?
00:21:52
>> Totally. Totally. Totally. But that's a
00:21:54
great it's a great question and I mean
00:21:55
Eric Eric is kind of confessing as well
00:21:58
because this he's been a poster boy
00:22:01
to Rory has been a poster boy for Eric.
00:22:03
It's like I don't know. I think he can't
00:22:05
do it. like the more he doesn't do it
00:22:07
despite having the talent, the more I
00:22:08
think he's choking to the pressure,
00:22:09
which is a reasonable question to ask.
00:22:12
Um, but it's it's nice that he got it
00:22:14
off. Got
00:22:16
>> one last one on golf. Next year's
00:22:18
Masters, who do you favor, Mroy or
00:22:21
Sheffller?
00:22:24
>> I'll go I'll go Scotty. I'll go age. A
00:22:26
year out, I'm going to go age now. But
00:22:28
one thing that's true, guys, is that I
00:22:30
don't know if you've seen the story or
00:22:31
how much they talked about it when you
00:22:33
were watching, but Rory flew back and
00:22:35
forth from home to Georgia for like the
00:22:38
last three weeks and just didn't play
00:22:40
anywhere else. Three to four weeks,
00:22:41
didn't play anywhere else, completely
00:22:43
focused on Augusta prep. Played a
00:22:45
million times. He got this tip from
00:22:47
Nicholas that Nicholas said, "Before
00:22:49
majors, I used to play in my practice
00:22:51
rounds. I don't know how often he did
00:22:52
this, but he said, "I used to play
00:22:53
practice rounds with one ball and kept
00:22:55
score." Which is not the way guys play
00:22:57
practice rounds. But guys play practice
00:22:58
rounds, play all kinds of balls, all
00:23:00
kinds of places.
00:23:02
>> Nicholas said, "I wanted to try to feel
00:23:03
like the major." And so Rory before this
00:23:05
played at least one round with one ball.
00:23:08
Um, so I mean, if he's going to take it
00:23:10
that seriously and what he did and how
00:23:13
he prepared for that tournament might
00:23:14
have changed the way other guys think
00:23:16
about preparing, not only for that one,
00:23:17
but for other majors. It's possible. You
00:23:20
know, we might get some insight into
00:23:21
that from someone who knows a little bit
00:23:22
more about golf than we do, someone who
00:23:25
just joined us. So, why don't we change
00:23:27
gears? We tried fans, listeners, we
00:23:30
tried to talk about something other than
00:23:32
golf. We did not succeed. And now we're
00:23:34
going to talk more about golf because
00:23:36
our guest just joined us. Ji Lee just
00:23:39
joined us. Ji,
00:23:40
>> hi everybody.
00:23:41
>> Is thanks for making time for us.
00:23:43
Appreciate it.
00:23:44
>> Thanks for having me on.
00:23:46
>> Ji is somewhere in transit from Augusta,
00:23:48
Georgia to her next destination. And we
00:23:50
make we appreciate you making time for
00:23:52
us. Ji has been down there for the
00:23:55
Masters. Let me give you just a quick
00:23:57
rundown on Ji's background and let you
00:24:00
know a little bit about why we brought
00:24:02
her on the show. She just announced in
00:24:05
the last month um her startup, I want to
00:24:09
call it a startup even though it's been
00:24:10
going for years. Her her company
00:24:13
Sportbox was bought by Bryson D Shambo,
00:24:16
brought into his platform and he kept
00:24:18
Gi. She will run the golf operation
00:24:21
among other things as a part of that
00:24:23
platform. Ji
00:24:26
is went to Yale originally, played golf
00:24:28
on the LPGA for three years. She came to
00:24:30
Wharton for an NBA. She left Wharton to
00:24:32
work for Topgolf, I think Topgolf in
00:24:34
Dallas, which is not a very typical NBA
00:24:37
job coming out of Wharton. It was fun to
00:24:39
see her do that. Was there for a few
00:24:41
years, did some strategy work for them,
00:24:43
and then started her own company. And
00:24:45
it's golf technology, and it's very
00:24:46
cutting edge golf technology. And so we
00:24:49
thought we'd take a chance to find out
00:24:51
what is the frontier of technology in
00:24:53
golf while we got caught up with Ji on
00:24:56
this new venture with Bryson. So that's
00:24:59
where we're coming from. Ji, how are you
00:25:01
feeling? How was the time? How was the
00:25:03
time in Augusta? And I'm sorry that it
00:25:05
wasn't any happier for your business
00:25:07
partner.
00:25:09
>> Yeah, it was uh a mix of highs and lows
00:25:11
for sure. Uh it started off with a an
00:25:14
extreme high. We announced that the
00:25:18
deal, you know, the acquisition deal on
00:25:19
Tuesday morning. Uh there was, you know,
00:25:22
the deal literally got signed on Monday
00:25:24
evening. So,
00:25:26
>> oh my,
00:25:26
>> you know, I signed I headed over to the
00:25:28
house where Bryson was staying. You
00:25:30
know, we hugged it out. It was a lot of
00:25:31
rah rah speech and uh a lot of uh a lot
00:25:35
of joy and celebration. Um, and
00:25:37
honestly, he was hitting it so good and
00:25:40
felt so prepared for the week. And um,
00:25:44
yeah, and I think he just had too high
00:25:46
of a maybe had too too big of
00:25:49
expectations going into the week to
00:25:51
actually perform, but um, but yeah, it
00:25:54
was highs and lows as a typical week of
00:25:56
golf.
00:25:58
>> Can you give us just real quick aside on
00:25:59
what you just said? As a former
00:26:01
professional golfer, can you talk about
00:26:03
the tension between expecting yourself
00:26:05
to play well and having expectations
00:26:07
that are too high? You just said you
00:26:08
thought Bryson might have had
00:26:09
expectations too high, but what's how do
00:26:11
you strike the right balance in that
00:26:13
>> and also whether hitting it well during
00:26:14
the week actually predicts whether
00:26:16
you're going to hit it well during the
00:26:17
tournament, but that would be helpful,
00:26:18
too.
00:26:19
>> Yeah, I mean, there's a lot to unpack
00:26:23
there. Obviously, you want to feel your
00:26:26
best going into your week. uh but at the
00:26:29
same time if you get your uh
00:26:32
expectations too high or get too excited
00:26:35
and you get kind of tripped up over
00:26:37
those expectations. So a really good
00:26:39
examp count counter example to that was
00:26:41
counter Colin Morawa who was injured
00:26:44
pretty severely like he had really bad
00:26:47
back pains going into it. He pulled out
00:26:49
of the players championship. We didn't
00:26:51
know whether he was going to play last
00:26:53
week. And if you saw if you caught any
00:26:56
of his um his action throughout the
00:26:59
week, he was, you know, barely finishing
00:27:01
his swing. Um his average driving
00:27:04
distance for the season is like 304. And
00:27:07
on the range, his max driving distance
00:27:10
at the Masters range was 285 or
00:27:13
something like that.
00:27:14
>> So, he really was like just kind of like
00:27:17
>> flinging at it. Um, and yet he finished
00:27:19
top 10 cuz he had probably very low
00:27:21
expectations about how he was going to
00:27:24
perform and just probably played super
00:27:26
conservative, fairways and greens,
00:27:28
nothing adventurous, never going forward
00:27:30
in two
00:27:32
>> and sometimes that kind of works out for
00:27:34
you. So
00:27:35
>> interesting. Very interesting.
00:27:36
>> Never uh yeah, you never control golf.
00:27:39
You just kind of have to go with what
00:27:42
what you get for that week.
00:27:45
>> Question. If a player wanted to, let's
00:27:48
say they weren't, now obviously they
00:27:49
want to win the tournament, but I just
00:27:50
want Jihei, I want to build on what you
00:27:53
just said. Suppose Bryson Dashambo, he
00:27:56
would never do this, but suppose he
00:27:57
said, "My goal is to make the top 10.
00:28:00
That's it. I'm just going to play
00:28:02
conservative, play to the center, play
00:28:04
to the fairways, you know, throttle back
00:28:06
my whatever 190 ball swing speed to 175,
00:28:10
and you know what? I'm probably not
00:28:11
going to win, but I'm going to end up in
00:28:13
the top 10." Could a pro do that of his
00:28:16
quality?
00:28:18
>> I think that's reasonable. But I think
00:28:20
what how most of these guys and girls
00:28:23
think is I have every every chance at
00:28:27
winning this championship. I'm every bit
00:28:29
as skilled and talented and, you know,
00:28:31
prepared as the other person. I have a
00:28:33
chance at winning this, but at the end
00:28:35
of the day, it's one shot at a time and
00:28:37
one day at a time. So, I'm just going to
00:28:40
focus on that and put myself into
00:28:42
position to win. Like, you don't win the
00:28:45
tournament on first day, right? You
00:28:47
don't win the tournament on the second
00:28:48
day. As we saw, Leroy was winning by
00:28:50
leading by six and lost all of that lead
00:28:53
as actually trailing going into the back
00:28:56
of the final 18 and he still managed to
00:28:58
win, but he put himself in that
00:29:00
position, right? So, that's all you can
00:29:03
do. Um, but I can guarantee you every
00:29:05
single one of these guys at the Masters
00:29:09
think they have a chance to win.
00:29:11
>> So, let's do one more question from AD
00:29:13
and then I want to dive into the her
00:29:14
technology. So, Audi.
00:29:16
>> Yeah. So, my question is um yeah, it's
00:29:19
different to ask the question, does
00:29:21
everyone want to win and and then you
00:29:22
can sort of play for top 10? But the
00:29:25
real question is do you have to in order
00:29:27
to win do you have to be aggressive and
00:29:30
and is that necessary and even at the
00:29:32
highest level? So, we understand that if
00:29:34
you're not in the top 10 ranked player
00:29:37
and you want to have a chance to win,
00:29:38
you're going to have to take chances.
00:29:40
And this is true across sports. To win,
00:29:42
you have to be aggressive, which means
00:29:43
you're more likely to lose by a lot, but
00:29:45
it'll give you a chance to to to to be
00:29:48
competitive. And so, um, that might be
00:29:50
something that that people think about.
00:29:52
I mean, I don't know. I haven't actually
00:29:53
ever This is I'm going to admit this
00:29:54
right here. I've never even played a
00:29:55
round of golf, but I've written lots of
00:29:57
articles about it. Um and uh and and
00:29:59
Mark Brody's talked about this
00:30:01
extensively that because in every sport
00:30:03
aggression is basically valued and that
00:30:06
even in golf it's valued. You you hit it
00:30:08
harder even if you is just is and
00:30:10
further even if you think you're losing
00:30:13
um control it turns out that that's
00:30:15
actually better and it may play into
00:30:17
this that that that riskiness we the
00:30:19
winning a tournament is so even for the
00:30:21
very best is still a long shot. Um even
00:30:24
for Tiger Tiger Woods at his greatest
00:30:25
was you know three to one against um so
00:30:28
which suggests that you have to take
00:30:30
chances. Um which is not quite the
00:30:32
question that you were asking is which
00:30:34
is can you scroll you know can stroll
00:30:36
into the top you know 10th by not taking
00:30:38
chances which is sort of similar to the
00:30:40
the poker tournament. I remember um if
00:30:42
you if you're playing poker if you are
00:30:44
too often um making the cut you're not
00:30:46
playing well that doesn't that's
00:30:49
strategy right. Yeah, I I think that
00:30:53
really depends on the golf course. So,
00:30:56
>> how you define aggressive or aggression
00:30:59
in your approach to the tournament, um
00:31:04
it it can be defined a few different
00:31:06
ways, but for example, at a US Open golf
00:31:09
course where it's super long, the rough
00:31:10
is long, and the greens are playing, you
00:31:13
know, the surface is really hard.
00:31:16
Um, I was talking to Chris Como, who is
00:31:19
a very, you know, he's actually number
00:31:20
one or two golf coach in the world, was
00:31:22
teaching Bryson at the time when he won
00:31:25
his US Open, first US Open in back in
00:31:27
2020. They were playing a winged foot,
00:31:29
which was playing very long, really
00:31:31
tough with the rough out to here. If you
00:31:33
missed the fairway, you literally just
00:31:36
had to hack it out of there, whether you
00:31:37
had 200 yards to the green or 50 yards
00:31:39
to the green. And so he was like, you
00:31:41
know, in an extreme case, if it was a
00:31:44
oneyard fairway and out of off of that
00:31:47
one yard fairway was just rough,
00:31:50
wouldn't you just want to hit it as far
00:31:52
as possible, get it as close as possible
00:31:55
to the green versus like playing
00:31:57
conservative to try to hit the hit the
00:31:59
fairway, right? So the quoteunquote bomb
00:32:02
and gouge methodology like hit it as far
00:32:05
as possible. If you're going to have to
00:32:07
hack it out anyway most of the time, why
00:32:10
don't we just get it as close to the
00:32:12
green as possible? That strategy works
00:32:14
for certain golf courses like a US Open
00:32:16
golf course.
00:32:18
>> Augusta National is just not one of
00:32:20
those golf courses.
00:32:22
Absolutely. It helps you if you have a
00:32:24
shorter club and you can get the ball
00:32:26
super high in the air and then land it
00:32:27
soft,
00:32:29
but um there are just so many
00:32:31
intricacies around the golf course. Um
00:32:35
the bends and turns and the shape of the
00:32:37
fairway where you're standing versus the
00:32:39
ball like all of it um makes it such
00:32:42
that just hitting it as far as possible
00:32:45
is not the best strategy.
00:32:48
So it's interesting that you asked a
00:32:50
question about to jihei because her
00:32:53
partner is famously you know the bomber.
00:32:56
So it there was some talk before the
00:32:57
tournament that he was that he had
00:32:59
learned that he needed to ratchet it
00:33:01
back some. So we this we don't need to
00:33:03
go too far into Bryson stuff and I don't
00:33:05
how much you want to talk about it but
00:33:06
he's an example of is it true that he's
00:33:09
learned that he had to ratchet it back
00:33:11
and he tried to ratchet it back more
00:33:13
than he has in the past?
00:33:15
>> I don't think so. I don't think I don't
00:33:17
think he's I mean every time he plays
00:33:19
it, every time any player plays that
00:33:21
golf course, they learn something,
00:33:23
right? I think Freddy Couples who's
00:33:25
played it I don't even know how many
00:33:27
times, like 40 times. He's probably
00:33:28
still learning every time he plays it,
00:33:30
right? Um I don't think Bryson's
00:33:33
approach was let's try to be
00:33:35
conservative. He still hit plenty of
00:33:38
drivers. Um, but you know, it's learning
00:33:41
how the the shots land, how to, you
00:33:43
know, distance control around the
00:33:45
fairways and um, and I think this week
00:33:50
the difference was a little bit of kind
00:33:52
of that distance control with his irons
00:33:54
and then um, I mean, if you look at
00:33:57
Rory's stats, too, he didn't have a
00:34:00
stellar driving week.
00:34:01
>> No, he bet. Right. No.
00:34:04
Um, but his scrambling was exceptional
00:34:09
right over the greens. And so you just
00:34:11
kind of you learn each time and I think
00:34:14
Bryson learned something this week. So,
00:34:16
>> all right. Well, let's let's dive into
00:34:19
the company that you built and have just
00:34:21
sold and you're staying on to help run,
00:34:23
but you've built you built this company
00:34:24
over a number of years around technology
00:34:27
and go golf was, you know, arguably
00:34:30
maybe the first major sport into this
00:34:32
kind of tracking technology.
00:34:34
Um, so where is it now? Like what what
00:34:37
was the original impetus that you built
00:34:38
the company around? And then how did it
00:34:40
advance to where it is now? and and so
00:34:42
we we'd like to use you to kind of catch
00:34:44
up on what what is the cutting edge of
00:34:47
technology and understanding golf
00:34:49
performance.
00:34:50
>> Yeah. So I started the company with a
00:34:52
co-founder Sam Menker who had spent 20
00:34:56
years a couple decades in AI and uh he
00:34:59
when I met him he was working on this
00:35:01
technology that can transform a video
00:35:04
just a simple video taken on your phone
00:35:06
or wherever into
00:35:09
pretty intricate detailed motion data 3D
00:35:12
motion data and when I say the motion
00:35:14
data it's you know how your body parts
00:35:16
are moving so you know your head side to
00:35:19
side um your torso round and round, you
00:35:22
know, up and down. How are your wrists
00:35:25
moving throughout the swing? Um it was
00:35:27
able to get all of that detail in uh 3D
00:35:31
accuracy that was on par with the
00:35:33
markered system out there that required,
00:35:36
you know, 45 minutes to get suited up
00:35:38
and like 12 cameras around you in a lab
00:35:41
setting. So for me,
00:35:44
>> how long ago? Hey, this was how long
00:35:46
ago?
00:35:46
>> This is in 2020. So just uh over five
00:35:49
and a half years ago and um I the aha
00:35:54
kind of the light bulb moment for me
00:35:56
when I understood what the technology
00:35:58
was capable of was you know I'd spent
00:36:02
years you know decades trying to perfect
00:36:04
my golf swing hit quite literally a
00:36:08
couple million golf shots in my life and
00:36:11
um still you go through stretches of
00:36:13
time when you're hitting it great and
00:36:15
then the next day you stand up on the
00:36:17
range you feel like you have no idea
00:36:18
what you're doing or you hit some crazy
00:36:21
bad shots. You're like, "Well, I feel
00:36:22
like I'm doing the exact same thing with
00:36:24
my swing, but clearly I'm doing
00:36:27
something different because the shot was
00:36:29
going straight yesterday. It's not going
00:36:31
straight today." And you know, you would
00:36:34
agonize over what's different? Why do I
00:36:37
feel different today? What is it? What
00:36:39
is it? What is the difference that is
00:36:41
producing such different outcome? Um,
00:36:44
and I saw the ability to produce data
00:36:47
quickly just using your phone
00:36:51
was that was the holy grail. It could
00:36:52
tell you exactly in inches and degrees
00:36:55
what the difference in your swing is
00:36:56
when you hit it good versus you hit it
00:36:58
bad. Um, and so that was the goal. We
00:37:01
wanted to create a product that allowed
00:37:03
everybody who plays golf, who teaches
00:37:05
golf to be able to see that data and
00:37:07
learn from it.
00:37:09
>> Can I ask a question? Maybe this is my
00:37:11
question. Maybe because you were a
00:37:14
professional golfer, you chose golf. But
00:37:16
couldn't you call talk about this like
00:37:19
why not sell it for baseball use and why
00:37:21
not for quarterbacks throwing the ball
00:37:24
except for your if it hadn't been your
00:37:26
personal interest if you had been a
00:37:27
professional women's basketball player
00:37:29
or a tennis player? Would you have
00:37:30
applied it to one of those sports and
00:37:32
maybe you'd be talking to I don't know
00:37:34
uh Yannik Sinner today and he'd be your
00:37:36
business partner.
00:37:38
>> Absolutely. Um, we actually started on
00:37:41
baseball a couple years ago and we do
00:37:44
have a baseball product that the LA
00:37:47
Dodgers have been using for their
00:37:49
international scouting. So, um,
00:37:52
obviously, you know, when they're in LA
00:37:54
in their training centers, they've got
00:37:56
millions of dollars worth of gear that
00:37:58
allows you to do motion capture with
00:38:00
their players, but when they're going
00:38:01
out to different markets where they're
00:38:04
scouting for the next big talent, they
00:38:06
want to be able to base their
00:38:08
million-doll bets on something real. And
00:38:11
they're using Sports Box now to measure
00:38:14
these, you know, 15, 16 year old kids
00:38:16
swings and pitching motion to see how
00:38:19
they compared against one another. and
00:38:20
versus the player the to the
00:38:23
professionals.
00:38:25
>> Well, real real quickly does and I want
00:38:28
to come back to the technology, but on
00:38:30
this topic,
00:38:31
Bryson bought you as part of a broader
00:38:34
platform. What is the goal for this
00:38:36
technology? I know there's goals within
00:38:38
golf, but is there are there goals
00:38:39
outside of golf for the technology and
00:38:41
what you're doing?
00:38:43
>> Absolutely. Uh we want to first like
00:38:46
really really win in golf, right? We've
00:38:49
created a great product, great
00:38:51
technology that can
00:38:53
have a a position to play in not just
00:38:57
instruction, but equipment fitting. For
00:38:59
example, we we get data on matching you
00:39:02
your swing, the the the idiosyncrasies
00:39:05
of your swing to certain shaft profiles
00:39:08
with your with the equipment that you're
00:39:11
playing to produce the best outcome. Um,
00:39:14
so much more there. We want to win in
00:39:16
this market but uh we definitely intend
00:39:18
to go out and build systems and products
00:39:21
and businesses and other sports as well.
00:39:23
I think baseball is a really obvious
00:39:25
example like I mentioned, but um you
00:39:28
know tennis and uh cricket is a very
00:39:32
common request. There are people in my
00:39:34
DMs on LinkedIn asking about all sorts
00:39:37
of sports including bowling and um
00:39:41
darts. I have gotten um there's there's
00:39:44
a lot there. So
00:39:46
>> that's hilarious. Gi, can you tell the
00:39:49
story of when Bryson got convinced about
00:39:52
your technology? This was a US Open, was
00:39:54
it not?
00:39:55
>> Yeah. So this takes us back to 2024
00:39:58
um when he was preparing for the US Open
00:40:02
and his coach Dana Dulquist has been a
00:40:06
sports box user and ambassador for a
00:40:09
while. um you know, a few years going
00:40:11
back and he and Bryson were trying to
00:40:14
troubleshoot a swing as always. You
00:40:17
know, he felt like he didn't quite have
00:40:19
it. Um he was he seeing more shots go to
00:40:23
the right than he would like. Uh because
00:40:26
he's a draw player. He wants to shape
00:40:28
the shot from right to left every single
00:40:30
time he hits the ball. And he just
00:40:32
wasn't seeing that happen as often as he
00:40:35
would like. and he came to us asking
00:40:38
look you know there are lots of great
00:40:40
people Dana Dawquist and whoever else
00:40:44
they have
00:40:46
uh a lot of experience and they can
00:40:48
offer opinions but can you tell me in
00:40:51
data right like I want to see data on
00:40:53
what makes me hit it to the right versus
00:40:56
when I hit it great and so we went down
00:40:59
to Dallas to his home course and
00:41:01
collected a bunch of data on his swing
00:41:03
every club on the golf course on the
00:41:06
ring change and we paired it with um a
00:41:09
launch monitor data. So he was using a
00:41:11
foresight device that can capture the
00:41:14
data around how the ball was shaped. So
00:41:16
we knew exactly where the ball was
00:41:18
going, which direction it was going and
00:41:21
we paired that with corresponding swing
00:41:23
data that we captured. And so based on
00:41:26
that data set, we were able to do pretty
00:41:28
simple linear regression analysis on
00:41:32
on getting the highest correlated motion
00:41:35
data items.
00:41:38
What was highest correlated with that
00:41:40
bad or good outcome that he was looking
00:41:41
for, right?
00:41:43
>> And it was so clear to us once we did
00:41:45
this analysis that it was like three
00:41:48
things at the top of his back swing. he
00:41:50
was getting too stacked, you know, and
00:41:52
he had no room, felt stuck, and then he
00:41:54
had to kind of like get his club face
00:41:56
open. And so
00:41:59
I delivered this information to him to
00:42:02
Bryson on Tuesday of US Open week at
00:42:06
Piner.
00:42:08
And imagine like me like being like,
00:42:10
"Hey Bryson,
00:42:14
this is what we're going to do with your
00:42:15
golf swing." um which is still to me the
00:42:18
most insane thing I've ever experienced
00:42:21
and obviously we were working with his
00:42:23
coach to make sure that it was kind of
00:42:25
filtered for through him his lens but
00:42:28
because we are we were armed with
00:42:30
science right we had data
00:42:33
I felt like I was in the right place
00:42:35
like I had a right to say this to him
00:42:38
and he was very receptive and he worked
00:42:41
on getting his his back swing data in
00:42:44
the right range for him to draw it. And
00:42:47
of course, he wins the US Open that
00:42:50
week.
00:42:53
And it was the craziest week of my life,
00:42:57
going from um telling a guy, a world
00:43:01
class athlete, what to do with his golf
00:43:03
swing to having him win and mentioning
00:43:06
Sports Box on his winter, you know,
00:43:08
press conference is the craziest week of
00:43:10
our lives.
00:43:12
>> That's That's good. That's good work.
00:43:14
That's good work. GA. Um, and good fun.
00:43:17
Um, Eric in the middle of that story
00:43:18
came up with a question. Eric,
00:43:20
>> well, I just want to know, do you have
00:43:22
now that let's assume that you guys are
00:43:24
doing the state-of-the-art in data
00:43:26
capture. I got a little nervous, maybe
00:43:28
my stat colleagues did too when you
00:43:30
talked about using a linear regression
00:43:32
to try to relate these things. Um, do
00:43:35
you have a team of data scientists now
00:43:37
that work for you that are building more
00:43:39
sophisticated models than linear
00:43:41
regression? And if not like I'm sure
00:43:44
Wharton the company that a naughty run
00:43:47
the Wharton Sports Analytics Business
00:43:49
Initiative would have many many
00:43:51
extraordinarily well-trained students
00:43:53
that would love to work with you.
00:43:55
>> I actually like the linear regression
00:43:57
models. So if you're using those that's
00:43:58
actually completely fine by me.
00:44:01
>> You MBA you learn your you learn your
00:44:03
regression.
00:44:04
>> I I I was hoping this is where the
00:44:08
conversation would go. Absolutely. I we
00:44:11
do have a data science team. Team is a
00:44:14
is a bit of a stretch. We've got a few
00:44:17
data science um team members who are
00:44:19
crunching the data, but would love would
00:44:23
love to collaborate on some of these
00:44:25
projects. There's a lot of data really
00:44:27
really cool data sets that we're working
00:44:29
with and we're trying to figure out like
00:44:31
what makes somebody play their best
00:44:33
golf, right? Yeah, that's the open
00:44:36
question. Let me let me uh jump in
00:44:38
because I think it's kind of relevant.
00:44:40
So what you're doing is if I understand
00:44:42
correctly is you have all these
00:44:43
measurements and then you have a your X
00:44:46
side of the linear regression and then
00:44:48
the Y side is some metric that you
00:44:51
calculate which measures how good the
00:44:53
shot is. Um and then you build a a
00:44:56
function that connects the two. That's a
00:44:58
far cry from an interventionist model
00:45:01
which would say we're now going to tell
00:45:03
you, you know, Ryson, you're going to do
00:45:07
this and what does that change? Um and
00:45:10
and then you can see that in the X side
00:45:12
and then and then on the Y side. Those
00:45:15
are very different um statistical kind
00:45:18
of structures. One is purely
00:45:21
correlational and the other is almost
00:45:23
cause causal. Right? We're going to see
00:45:25
we're going to take you going to tell
00:45:26
you
00:45:27
>> experiment and it's experiment and
00:45:29
that's the and so I mean it's in some
00:45:31
level you were very fortunate because
00:45:33
your first uh I guess you went to him
00:45:36
and said we we're seeing this uh do this
00:45:38
and and then he won right
00:45:40
>> first experiment worked
00:45:41
>> yeah first experiment but uh and so now
00:45:43
you want to really see um uh how to turn
00:45:46
that and that's kind of like um not it's
00:45:48
not going to be the the data analyst who
00:45:50
can do that it's the it's the it's the
00:45:52
design of an experiment you're gonna
00:45:53
have to go in
00:45:54
with golfers, with the devices, and then
00:45:58
and with coaches, and then try to do
00:46:01
control comparisons, which is really
00:46:03
what an experiment is. And that would be
00:46:05
that would be mind-blowing.
00:46:07
>> That would be very cool. And we've
00:46:08
talked about almost creating a sim of
00:46:11
like when you change this in early part
00:46:13
of the swing, what happens to the rest
00:46:14
of the golf swing? Like multivaried
00:46:16
approach. And um I mean that's I I think
00:46:20
that biomechanical sim is a possibility.
00:46:23
That's that's been done before. We we
00:46:26
should we should explore that. But also
00:46:29
we've now we're now deploying our LLM
00:46:33
layer on top of all the data sets. So um
00:46:37
we're using Gemini. We're a Google
00:46:39
partner and we have created something
00:46:41
called Sammy Sportsbox AI motion
00:46:44
intelligence
00:46:46
uh chatbot that can understand our data.
00:46:49
So what what it means when we say hey
00:46:51
the pelvis sway is too high in the back
00:46:53
swing like what does that mean in the
00:46:55
context of a golf swing? But you know
00:46:57
instead of our data scientist going and
00:46:59
like crunching the data we can just ask
00:47:01
Sammy hey you know that last swing I hit
00:47:05
it really bad. How does that compare to
00:47:07
my US Open swing? Oh okay that impact
00:47:11
position was like this. Okay well why am
00:47:13
I doing that? What happens earlier in my
00:47:15
swing that makes me do this at impact?
00:47:17
So kind of that type of uh interaction
00:47:20
is possible with AI.
00:47:22
>> Yeah. And and Audi, this is something
00:47:24
you would know if you if you played more
00:47:26
golf. And that this is the
00:47:28
>> I'm not playing more golf, Kate.
00:47:30
>> Well, I and I and and and we can do
00:47:32
something about that.
00:47:34
>> But this is the kind of conversation
00:47:35
that happens on the golf course with
00:47:37
your buddies if you're a professional.
00:47:39
Happens with your coach. But guys are
00:47:40
always like, "What am I doing? What am I
00:47:42
doing?" And and some guys are really
00:47:43
good at saying, "Well, you're a little
00:47:44
bit, you know, you're moving. you're
00:47:46
moving your head, you got your back
00:47:47
swing off or your tempos off or
00:47:49
whatever, you're you're forever losing
00:47:51
your swing and you're forever asking for
00:47:53
outside perspective on what's happened
00:47:54
to your swing. And Gihei has gone out
00:47:56
and created a way to tell very precisely
00:47:58
and it doesn't mean you're going to
00:48:00
necessarily be able to fix it, but it
00:48:02
does give you accurate information. Um,
00:48:04
GA, talk a little bit about this mission
00:48:07
that you guys have in terms of
00:48:09
identifying young golfers. And I think
00:48:12
this is something that will be
00:48:13
intriguing to the whole crowd here. But,
00:48:16
um, there's a premise, I suppose, that
00:48:20
you're you have the ability to identify
00:48:22
natural talent in the swing or the
00:48:23
potential the potential in a swing. You
00:48:25
can identify with your technology.
00:48:27
That's a that's a premise. But if that's
00:48:30
true, there might be golfers out there
00:48:34
off the radar, maybe socioeconomically
00:48:36
disadvantaged folks who if they were
00:48:39
seen to have the potential they actually
00:48:41
have would have a very different future.
00:48:43
Is do am I capturing that right? And and
00:48:46
to and how are you all pursuing that
00:48:47
idea?
00:48:48
>> And then of course are you pursuing a
00:48:50
either a private equity or hedge fund to
00:48:52
invest with you in that because of
00:48:54
course there's an economic play there. I
00:48:56
I have to say it's Sher Wharton MBA. I
00:48:58
you have to be thinking about the
00:49:00
monetization. I you want I understand
00:49:02
it's democratization. It's good for
00:49:03
society, but someone would want to
00:49:05
create a couch or something for
00:49:07
investing in young golfers.
00:49:09
>> Hey, Shane and I are communists and so
00:49:11
if you don't want to skip the capitalist
00:49:12
side, you can go with just improving the
00:49:14
world. That that's okay.
00:49:15
>> Okay. Okay.
00:49:17
>> Um well, I mean going back to the
00:49:21
premise, you know, I was I went through
00:49:23
the college recruiting process. I was
00:49:25
very fortunate to have been recruited at
00:49:27
Yale and played college golf. But um
00:49:30
that was all because I got to play a
00:49:32
certain amount of tournaments on a tour
00:49:35
called AJGA, American Junior Golf
00:49:37
Association, which is like the top level
00:49:39
junior golf tournament series where
00:49:42
college coaches know to recruit, right?
00:49:44
And if you play in those events, you get
00:49:46
ranked, you know, internationally on
00:49:48
like the junior golf rankings, which is
00:49:50
again a reference point for college
00:49:52
recruit uh college recruiters, right?
00:49:54
coaches looking at who should I, you
00:49:56
know, put place my bets on. But that
00:49:59
leaves out a whole like entire world of
00:50:03
golfers, junior golfers who may not be
00:50:05
able to travel to these events, may not
00:50:07
have the funds to play, you know, 30, 40
00:50:10
tournaments a year, which is insane,
00:50:13
right? It's like a full professional
00:50:15
schedule.
00:50:16
>> It's incredible.
00:50:17
>> Yeah. And if you're not on that rankings
00:50:20
list because you didn't play in these
00:50:21
events, like you're just kind of so if
00:50:24
you will, right? Like you're just not
00:50:25
visible, right? And so
00:50:29
um so that that was one part of it. And
00:50:32
then I asked college coaches like, "Hey,
00:50:34
when you are looking at talent, what are
00:50:36
you looking at?" And they're like,
00:50:37
"Well, you know, obviously the rankings,
00:50:39
but I sometimes go and like do my eye
00:50:42
test." And I'm like, "What's the eye
00:50:44
test?" They're like, "Oh, you know, some
00:50:46
some of them just look like athletes."
00:50:47
I'm like, what?
00:50:50
This in 2025, like this is what you're
00:50:54
relying on.
00:50:55
>> What are we selling? Jeans. That's the
00:50:57
great line for a money ball.
00:50:58
>> Exactly.
00:50:59
>> Exactly. And so we got curious about
00:51:02
like if you look at a golf swing and
00:51:05
you're able to break it like almost
00:51:07
tokenize it into data, like is there are
00:51:09
there telltale signs of what makes a
00:51:12
great athlete, right? And so we went
00:51:15
down the path of um creating a swing
00:51:18
score or set of scores that would define
00:51:22
how skilled of a golfer they are based
00:51:24
on their golf swing. Not looking at like
00:51:26
a short game or whatever. And we did
00:51:29
come up with a a scoring mechanism
00:51:31
that's really highly correlated with
00:51:34
somebody's handicap. So that was step
00:51:36
number one. But I think if we are able
00:51:39
to look at junior golfers over a period
00:51:41
of time and just keep measuring their
00:51:44
data, right, and how they're progressing
00:51:46
in their careers, maybe through a
00:51:49
college, you know, like a five-year
00:51:50
longitudinal study, I have high
00:51:54
confidence that we can come up with even
00:51:56
better metrics on what to look for for
00:51:59
junior golfers to indicate their current
00:52:00
and future success. That's kind of the
00:52:02
thesis.
00:52:04
>> Can I jump in? Um, one of the advantages
00:52:06
you have with golf is that it's uh
00:52:08
individual and um you measure strokes,
00:52:12
strokes gained. Um, you can really get
00:52:15
accurate information on how you played.
00:52:18
How do you think can you you think you
00:52:20
can
00:52:22
basically recover performance metric
00:52:25
with just looking at the swing?
00:52:27
No, I don't think it's going to be an
00:52:31
exact uh overlap versus their overall
00:52:36
performance because golf has a lot of
00:52:38
components like short game, putting your
00:52:41
ability to handle stress, you know, that
00:52:43
kind of stuff. But in terms of like we
00:52:46
know for a fact that um through Mark
00:52:49
Brody his his work like being able to
00:52:51
hit the ball especially with the driver
00:52:54
really far really well consistently is
00:52:57
one of the most if not the most
00:52:58
important aspect of what makes a golfer
00:53:01
successful. And so if we're able to
00:53:03
measure the golf swing to say yes, this
00:53:06
is a swing that can produce really high
00:53:08
ball speed really consistently
00:53:11
that I believe is worth betting on.
00:53:14
>> So on this this is exactly where I was
00:53:17
about to go and that is what are you
00:53:19
adding beyond ball speed since that's
00:53:22
actually the outcome that's kind of
00:53:24
>> measure that I mean we
00:53:26
>> we can measure that other ways and it
00:53:28
covers so much territory. What is added
00:53:31
by the biomechanics used to produce that
00:53:33
ball speed?
00:53:34
>> Yeah, so really good question. So we got
00:53:37
in our swing score, we have three
00:53:39
components currently and we we'll get to
00:53:40
the fourth. The first is speed. We we
00:53:44
have hand speed, we have club head
00:53:45
speed, we have shaft speed. Um those
00:53:48
speed metrics very very important to
00:53:51
producing a a speed score. Second is
00:53:54
efficiency. So how efficiently are you
00:53:57
producing that speed? Um and that's a
00:54:00
lot of the kinematic sequence data like
00:54:02
you know um are you starting from the
00:54:04
lower body to upper body to like you
00:54:06
know that whipping effect right
00:54:08
>> um that is incredibly important to
00:54:10
indicate somebody's skill level. Third
00:54:12
is consistency and you can think of that
00:54:15
as you know if you guys have been on a a
00:54:18
launch monitor for golf you see the shot
00:54:20
dispersion and that is almost like one
00:54:23
to one correlation to how good of a
00:54:24
golfer it is like the tighter the
00:54:26
dispersion the better the golfer they
00:54:27
are. we have movement dispersion, but if
00:54:30
you're not hitting good shots, even if
00:54:32
you're a good golfer, like you're
00:54:34
probably trying something different in
00:54:35
every swing. And that's going to show up
00:54:37
in our data. And for different skill
00:54:40
level golfers, if you're really highly
00:54:42
skilled like Bryson, that standard
00:54:45
deviation for everything we measure is
00:54:47
super tight versus not so skilled
00:54:50
golfer, they're they don't know what
00:54:51
they're doing with their bodies
00:54:53
essentially. Um, so those things are
00:54:56
super highly correlated to somebody's
00:54:58
skill level as a golfer. And then the
00:55:00
fourth that we're getting to um is
00:55:02
impact quality. So while we can't get
00:55:06
like the club head data at the moment of
00:55:09
impact, we have a lot of things that
00:55:12
we've studied that would correlate to
00:55:15
centerness of contact, low point, and a
00:55:19
um path, you know, neutral path, like
00:55:21
what in the golf movement would highly
00:55:25
correlate to that impact condition with
00:55:26
the club head delivery.
00:55:28
>> That is going to be the fourth score
00:55:30
that we're going to add to our overall
00:55:32
spin score. That's neat. So that's
00:55:34
that's the thing that determines along
00:55:36
with the speed and and the path. There's
00:55:38
a lot of things that determine it, but
00:55:39
the outcome of the shot. It sounds like
00:55:41
you're basically reconstructing what you
00:55:43
don't observe. You're modeling what you
00:55:45
don't observe so that you can then
00:55:47
basically simulate what happens with the
00:55:50
with the ball. That's super interesting.
00:55:51
I'm now I want to ask you the question
00:55:53
of if you had to bet because I love this
00:55:56
premise of we we think we can identify
00:55:59
talent with our technology.
00:56:03
If you had to bet these different four
00:56:04
components uh speed, uh efficiency,
00:56:09
um consistency, and then quality of the
00:56:12
impact. If you if you if you if you had
00:56:14
those ratings on a bunch of kids, you
00:56:17
know, in in in downtown Los Angeles from
00:56:20
the range and some were strong on one
00:56:22
and some were strong on the other, which
00:56:23
and you had to bet which is going to be
00:56:25
the better college golf coffer three
00:56:26
years from now
00:56:27
>> just on that alone.
00:56:28
>> I think and this is completely not based
00:56:32
on science. I understand.
00:56:34
>> My theory is that the younger they are,
00:56:37
the speed is going to be more important.
00:56:41
>> Okay. if at a younger age if you're able
00:56:43
to produce a lot of speed,
00:56:45
>> that is going to be like that's talent.
00:56:48
Um, and the older they get, you know,
00:56:50
they've grown into their bodies and
00:56:52
whatever, the the consistency is going
00:56:54
to matter the most.
00:56:56
>> Okay. Gi, do you know this thing that
00:56:57
Nicholas said? This is like a Golf
00:56:59
Digest thing from the 80s or something.
00:57:00
I've always remembered it from as a kid,
00:57:02
probably because I wasn't enough of a
00:57:03
long knock, but Nicholas said something
00:57:05
like, "People ask me, should I teach my
00:57:07
kid, should I teach my kid to hit it
00:57:09
long or hit it straight?" and he said,
00:57:11
"No question. Teach them to hit it long.
00:57:12
They can learn to hit it straight
00:57:13
later." And um that's basically what
00:57:16
you're asking.
00:57:17
>> That's exactly what's happened in
00:57:18
baseball. They they've said, "Should I
00:57:19
should I teach them to throw strikes or
00:57:21
throw hard?" And for years it was throw
00:57:23
strikes. And now it's throw hard.
00:57:26
>> Right. Right.
00:57:26
>> That's where I went wrong.
00:57:29
>> Nobody Nobody told me it was important
00:57:32
to swing hard. They told me to swing
00:57:33
pretty.
00:57:35
>> This is why I'm I'm doing what I'm doing
00:57:37
and not playing on the LPJ tour. So GA
00:57:40
when that's that raises is it when when
00:57:42
people what what would you say
00:57:44
correlates best with what people
00:57:46
perceive to be a pretty swing I assume
00:57:48
that's tempo and efficiency do you do
00:57:50
you have some sense of what that would
00:57:52
be
00:57:53
>> really good question I think it is a lot
00:57:56
to do with tempo
00:57:59
um because you know universally we
00:58:05
Rory's golf swing is is known as like
00:58:08
the most stunn stunning golf swing. Rory
00:58:10
and Nelly, right? Whenever sports box
00:58:13
account we post anything about Rory and
00:58:14
Nelly swing, like it just blows up
00:58:16
because people just love looking at
00:58:18
those swings.
00:58:19
>> Well, they're both beautiful people,
00:58:21
too. So, that's that's part of it, I
00:58:23
suspect. And Rory's is just so powerful.
00:58:26
>> Um, we're another another indulgent
00:58:28
question real quick. Cameron Young
00:58:30
pauses at the top of his backspring. It
00:58:32
makes me It makes me anxious when he
00:58:33
pauses. What is y'all's What is y'all's
00:58:36
take? I literally like to watch him
00:58:38
watch play golf less because of that
00:58:41
pause. What is y'all's take on whether
00:58:43
it's okay to pause or not?
00:58:45
>> I mean, clearly for him. Yeah.
00:58:48
>> Yeah. Clear. It's like Jim Furick had a
00:58:49
bad swing, so whatever. It doesn't
00:58:50
matter. You don't have a
00:58:51
>> I guess an empirical version of that
00:58:53
question is is is like a pause at the
00:58:55
top of your swing. Is that a particular
00:58:57
aspect that's hardest to keep
00:58:59
consistent? I I would think that that
00:59:00
would be I I I also it doesn't look
00:59:04
right to me just because I I would
00:59:06
struggle with that type of if I had
00:59:08
something like that in my golf swing, I
00:59:10
would struggle with being very
00:59:11
consistent about it. So, I don't know if
00:59:13
that I agree. Yeah.
00:59:15
>> Yeah. I mean, it's truly every swing is
00:59:19
so unique. It's hard for me to sit here
00:59:21
and say like, "Yeah, that's a um that's
00:59:24
a bad move or whatever because
00:59:28
>> you're saying we don't put everybody in
00:59:29
a model and say your swing is wrong
00:59:31
because we have the universal good
00:59:32
swing. We're going to look at your swing
00:59:33
relative to your other swings
00:59:35
essentially and we can tighten it up,
00:59:36
but mostly we're talk about how you're
00:59:38
you're deviating, especially these
00:59:39
professional golfers, how they're
00:59:40
deviating from something that has worked
00:59:41
for them."
00:59:42
>> Yeah, absolutely. And that's where the
00:59:44
data becomes more and more important.
00:59:47
>> Okay. Okay. So, tell us one last like
00:59:48
what are you most excited about now?
00:59:49
You've signed the deal. It's public.
00:59:51
You're off and running. What do you turn
00:59:54
your attention to next? Like what's in
00:59:56
the next couple weeks something that's
00:59:57
going to be a priority for you?
01:00:00
>> Honestly, it's the
01:00:03
business building. You know, we've got
01:00:05
this great megaphone, if you will,
01:00:08
through Black Bryson as our ambassador
01:00:11
and business partner. and we've got the
01:00:13
benefit of his platform to go out and
01:00:16
talk about the great work we're doing um
01:00:19
with Bryson and otherwise just have to
01:00:21
go and capitalize on it from a business
01:00:23
standpoint and with the additional
01:00:26
resources we will look at you know some
01:00:28
of the research that I've talked about
01:00:31
because I do think that you know what we
01:00:35
have to offer is the opportunity to
01:00:36
democratize access to great technology
01:00:39
for everybody um and access to
01:00:42
opportunities to play at a higher level.
01:00:45
So, and and Bryson is kind of the
01:00:48
accelerant that we wanted to go out and
01:00:51
do that effectively. So, that's what
01:00:53
we're really excited about.
01:00:55
>> Terrific. Well, Ji, we wish you the best
01:00:58
with it. Thank you again for pausing
01:00:59
with us and your travels and right on
01:01:01
the heels of this announcement, we're
01:01:02
excited for you and uh now we're a
01:01:05
little bit more up to date on the
01:01:06
cutting edge of Goth technology as well.
01:01:09
But, G Lee, thanks for making time for
01:01:10
us. Thank you everybody. It was really,
01:01:12
really nice talking to you.
01:01:14
>> Gi Haley, co-founder of Sportsbox, new
01:01:17
business partner to Bryson Dshambo in a
01:01:20
deal that was just announced last week,
01:01:21
fresh off of a trip down to Augusta.
01:01:24
That has been the full show, guys. It's
01:01:26
been the full hour here of Sports
01:01:27
Analytics on Wharton Podcast Network for
01:01:30
the team, all of whom have been here for
01:01:32
the whole ride. Shane Jensen, Audi
01:01:34
Winer, Eric Bradlo. Thank you guys for
01:01:36
listening. Big thanks to Dion Simpkins
01:01:38
for making this show happen. from
01:01:39
Marissa Raina, our producer, and Deep
01:01:41
Patel, the boss lady, keeping us all in
01:01:44
line. Appreciate it. Thank you guys for
01:01:46
listening. Come back and join us next
01:01:47
time between now and then. Enjoy your
01:01:49
sports.
