Why Soccer Analytics Works Like Volatility Arbitrage Trading
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What is the main topic discussed in this episode?
This week on Leaders, with me, Francine Lacqua. I speak to tennis legend Rafa Nadal about how he stayed competitive despite injury.
I was able to enjoy the victories probably more than if I will not have this issue.
One iconic match.
In my mind was, I am almost dead.
And whether he misses playing.
I don't miss tennis because there was nothing else to offer.
Listen and watch Leaders with me, Francine Lacroix, on Bloomberg Television or wherever you get your podcasts.
Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal.
And I'm Tracy Alloway.
Tracy, I have a question. I know you spent a lot of your youth overseas. My youth. Did you ever go to many baseball games as a kid?
Yeah, so I was in Chicago for a few years, so I went to the Cubs games, and then I was in Japan, and the baseball scene in Japan is amazing. Like, the best vibes of a live sports event that I've ever, ever witnessed or encountered.
I was just talking to someone about this last night. I've always wanted to go to a Japanese baseball game.
Highly recommend.
That's actually, like... If we ever do a live show in Tokyo, let's try to schedule it during baseball season because that is like I sort of think that's a bucket list thing. But anyway, the reason I ask this question is I have this really vague memory as a child going to see Detroit Tigers games with my grandfather, like probably when I was like maybe these memories are probably from when I was younger than like six or five. But there used to be a non-trivial number of people who would go to the games and they would keep score and they would write down every single at bat and the outcome of every single one.
I'm pretty sure I've seen that, not in person, but like maybe in movies or something like that.
It doesn't really happen anymore. Like I never see it. There may be a few like old timers who still as a hobby or habit do that. But it was like a non-insignificant number of people. And it's interesting to me, you know, I've been to a couple of soccer games this year. There is no equivalent way you could do that. Right. Because it's like baseball is filled with all of these discrete events. The pitcher. Who is the pitcher? Who is the batter? Hit. Not a hit. Single. Not a strikeout. Walk, etc. Like what would even be the equivalent in soccer?
So this has been a long running debate in soccer. And I remember when Moneyball came out and sports analytics became a big thing, especially for baseball, because as you point out, it's these sort of discrete events that have a lot of statistics embedded in them. A lot of people were saying that soccer, you could never use data analytics in the same way for soccer. Like it's too chaotic. It's too fluid. There's too many variables. There's not enough goals. That complaint comes up a lot whenever we talk about
How did soccer analytics evolve from 'too chaotic' to data-driven models?
Are we going to say soccer or football, by the way?
You know what? Let's just say soccer.
Okay. All right. I'll try.
We can say football. I actually don't feel strongly about this one.
But that said, we do see soccer analytics on the rise, right? Like now we get all these stories about like tiny clubs that are using data to source, you know, specific players in very Moneyball style ways. We obviously have prediction markets where people are doing a lot of sports. And so all the analytics seem to be like becoming more important. And I will just say I've read this crazy stat right before we came on from the law firm Morgan Lewis. And they were saying in the 2026 FIFA World Cup, match based data is going to be something like so it's 104 matches generating more than 90 petabytes of data.
Yeah.
which is a 45-fold increase over the volume produced in the last World Cup in 2022. That's stunning.
So this raises a question, and I know we're going to get to this in the conversation, and it almost is like a philosophical question, which is, OK, we see the game of soccer is like very fluid, right? There's no we just said there's fewer discrete events. Like in theory is something that's fluid, a series of like microscopic discrete events.
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Chapters
4 chapters
1
What is the main topic discussed in this episode?
0:00–2:57
2
How did soccer analytics evolve from 'too chaotic' to data-driven models?
2:57–34:49
3
How are volatility arbitrage trading skills applicable to soccer analytics?
34:49–42:18
4
What are the primary goals of soccer analytics for teams, bettors, and fans?
42:18–51:32
Speakers
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