Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy.

Loading...

From the course by University of Houston System

Math behind Moneyball

24 ratings

University of Houston System

24 ratings

Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy.

From the lesson

Module 10

You will learn how Kelly Growth can optimize your sports betting, how regression to the mean explains the SI cover jinx and how to optimize a daily fantasy sports lineup. We close with a discussion of golf analytics.

- Professor Wayne WinstonVisiting Professor

Bauer College of Business

Okay, let's apply the Kelly Growth criteria to NFL points [INAUDIBLE] so let's suppose you're really good against the points. So you can pick 60% against the point spread,

Okay, and so what fraction of your bank roll should you bet on each bet? What fraction of your bankroll

should you bet on each game if this is the case? So we'll use Kelly Growth here so we can pick the fraction. Let's start with 10%.

Okay. Now basically, okay, so if you win what would you end up with? And if you lose, what would you end up with? And the probability of winning again we've given you is 0.6. Losing is 0.4 Okay, so if you win okay, let's figure what you'd end up with. And then we can take the log utility over here.

Okay, so if you win basically you would take this fraction, okay, and basically, you just add that, suppose you start with a so you'd have let's say, let's suppose you win, you win a dollar, you lose, you lose a dollar too.

Okay so you would have 89 cents. Okay, because you lose the 11 cents. So, the log of where you'd end up would be the log of this.

We could do some product, we'll take 0.6 times this log plus one minus, well plus 0.4 times this log. We want to maximize this.

So you want to choose the yellow to maximize the right. Okay, and it's going to turn out about 14%. You see, if we put this at 14%, I think that number goes up a little bit. Let's start with the point. So we go data, solver, maximize the expected log return.

Change the fraction a bit, and I think it will work without saying it's between zero and, well, let's just make sure, we'll say the fraction bet's between 0.01 and 0.09. You don't really need this, but I worry sometimes I'll get a negative number if I let lots go negative. Or the changing negative. So it should be able to get this to. And the answer is 14.5%. Bet 14.5% of bankroll on each bet.

So your capital would grow at about, well subtract one. Your capital would grow about 1% per bet. So in other words, after 100 bets on the average, where would you be?

You'd be one plus this to the 100th power. Okay, you would've tripled after 100 bets if you do this. You should on the average have tripled your money, okay, which isn't bad. Of course, you might not triple your money. And of course, the hard thing is picking against the spread. Again, break even against the spread. If you have probability p of winning a bet, p you win $10, plus one minus p you'd lose 11. And you'd get p equals 11 over 21. Right here.

Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online.