YouSaid · the spoken record

Jeff Ma

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58

first

2019-12-10

most recent

2019-12-10

sittings or episodes

1

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podcast

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1. “At the core, what you're talking about is people would say, Oh, how do you predict wins? But what are the real, and it's always scoring, so scoring at some level is, and then what are the things that really are the most predictive for scoring? And I guess I'll go back to baseball again because there's this concept even in baseball. If you do a bottoms-up model, meaning trying to predict hits or trying to predict each at bat, even if you have, let's say three hits in a row in one inning and then no hits in the next two versus three hits in one inning, it's just this idea of cluster luck is what they call it. And so I think what I would say is that there continues to be really great opportunities to evaluate sports as you break down what you're saying, trying to change outcome variables.”

   2019-12-10 · Invest Like the Best · Jeff Ma – Making Decisions with Data - [Invest Like the Best, EP.151] · IDENTIFIED FROM THE TRANSCRIPT · source

2. “Yards. He's never looked at a spreadsheet or anything, but he completely had it all in his mind. And I met with Jerry West at the same time. And Jerry West, the first thing he said to me is, boy, I flew to Memphis to sit with him. And he said, boy, I got one thing to tell you first. And I said, what? He goes, I hate statistics. And I was like, oh, okay, this is going to be great. This would be a great time to hang out in Memphis. But what he meant was that he hated the way people used statistics in basketball. And he even said, he said, I hate that people think Alan Iverson's a great basketball player, even though he needs 35 shots to score 30 points. He hated the way. And so it was clear that there is in these geniuses, and I'm sure you guys see this in its world, there are geniuses that don't need models, that just somehow have this inane ability to sort of look at situations and then extract value from them. But the rest of us need models. The rest of us need data. And so the key is almost unlocking what's in their mind via...”

   2019-12-10 · Invest Like the Best · Jeff Ma – Making Decisions with Data - [Invest Like the Best, EP.151] · IDENTIFIED FROM THE TRANSCRIPT · source

3. “I sat down with him in his office, and I remember I was specifically were trying to build out a model to evaluate the process, to evaluate plays, a six-yard run means success on first down, but a six-yard run on third and 20 is not successful or second and 12 or something like that is probably not successful. So you have to evaluate on any given play how many yards do I need to make it successful. And so we had done some numbers basically looking at building a model of all the different plays and what yardage gains would actually put you in a better position in terms of winning. So that's how we evaluated it. And what we found was that it was for first intent, it was something like a little over four yards, so four and a half yards was meant success. And so I just sat down and asked Bill Walsh. And you guys are here. I got my Excel spreadsheet out and all this kind of stuff. And I'm like, Coach Walsh, on first and 10, what do you? He was, oh, probably a little over four years. Like he thought for a minute and they said a little over four.”

   2019-12-10 · Invest Like the Best · Jeff Ma – Making Decisions with Data - [Invest Like the Best, EP.151] · IDENTIFIED FROM THE TRANSCRIPT · source

4. “I think the first wave was always player personnel. It's like, how do we make our player personnel decisions? And specifically a sport like football where you see a team like the 49ers becoming very aggressive and different in terms of how they do contracts and things like that. So that's sort of an inefficiency, which is to understand, can you structure contracts in a way that are better for the team in terms of guaranteed money, in terms of how it hits the cap, in terms of all those things? So that's, I think, an area of huge opportunity or gain. I think that generally on field strategies in places like football and understanding game theory around run past mix around play calling that's a huge area for opportunity to understand like the key to analytics and so when we're working on pro trade the sports company bill walsh was an investor and bill walsh was this sort of legendary coach for the 49ers won four super bowls and pioneer”

   2019-12-10 · Invest Like the Best · Jeff Ma – Making Decisions with Data - [Invest Like the Best, EP.151] · IDENTIFIED FROM THE TRANSCRIPT · source

5. “I mean, that's definitely a good way to look at it. The challenge with that, both the value and the challenge with that is that you're talking about almost having somewhat of a qualitative judgment. And so I think that's an interesting thing that sports is going towards, which is this idea of, and you see it in machine learning or anything like human evaluation. How do you actually get humans to help interpret data at scale that helps you create a better data set to use to train models and things like that?”

   2019-12-10 · Invest Like the Best · Jeff Ma – Making Decisions with Data - [Invest Like the Best, EP.151] · IDENTIFIED FROM THE TRANSCRIPT · source

6. “Capture there was a pitch and then there was a single. A single could be a ground ball that just happened to find a hole or it could be a rocket that just landed short of in Fanway Park. It could be a rocket that hits off the wall and should have been a home run at any other ballpark, but someone basically hit it right directly into the wall and the defender made a great play.”

   2019-12-10 · Invest Like the Best · Jeff Ma – Making Decisions with Data - [Invest Like the Best, EP.151] · IDENTIFIED FROM THE TRANSCRIPT · source

7. “Analytics paradigm, which is that you can't have any strong analytical system unless you have good data. For a long time, sports data has been pretty bad. Generally, the data that's captured is the data that's easy to capture. It's the data that describes what's happening in the game. It's not what is ultimately the best thing to build out an analytical system to predict what's going on with things like player tracking and with computer vision and all these different types of things. We're getting much better data to understand how to predict games, specifically in baseball. Originally, you would have very, very, very old data that wasn't useful. But now they literally have cameras that are capturing launch angle and spin rates of the ball and velocity and exit velocity of a hit that allows you to build better bottoms up models to predict what would happen in a game because think about baseball.”

   2019-12-10 · Invest Like the Best · Jeff Ma – Making Decisions with Data - [Invest Like the Best, EP.151] · IDENTIFIED FROM THE TRANSCRIPT · source

8. “I would say at the sports level, not the sports betting level, but the sports level, like the Billy Bean level, the way that it's evolved the most is just acceptance. People believe in this. So in basketball, there are analytical strategies that you see on the court. I don't know if you know, but three is worth more than two. So teams that shoot more three pointers, they're more analytically driven, especially certain three pointers. The corner three, which is much closer, it's closer than the rest of the three. So people shoot it at a higher percentage. That's why you see so many people trying to shoot corner threes and you see the best defensive teams trying to take away the corner three because it's a highly efficient shot. And across sports, I would say there is much more of an acceptance that you need some form of analytics to basically compete now, both from a player personnel standpoint and then an on-field strategy standpoint. I think the more interesting thing or the evolution as sports is going forward is going to be around data and that's sort of like the classic.”

   2019-12-10 · Invest Like the Best · Jeff Ma – Making Decisions with Data - [Invest Like the Best, EP.151] · IDENTIFIED FROM THE TRANSCRIPT · source