Predicting Predictive Modeling

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I grew up in the predictive modeling world. I was very lucky to take a class with Jeff Hinton and Michael Jordan, which to this day I'm like, I wish I'd saved the binder from it. The predicting predictive modeling idea as far as I can tell is here's a giant bucket of data, maybe a times dream or a series of many, what's going to happen next? Right? What's the most efficient way of saying what happens next? A very tricky and intellectually fascinating problem as it turns out. And so if you don't tune your models to look for players who have a lot of upside, you'll get something that's good at predicting just a slightly

You might think that human beings, exhausted by competing for resources and rewards in the real world, would take it easy and stick to cooperation in their spare time. But no; we are fascinated by competition, and invent games and sports to create artificial competition just for fun. These competitions turn out to be wonderful laboratories for exploring concepts like optimization, resource allocation, strategy, and human psychology. Today’s guest, Daryl Morey, is a world leader in thinking analytically about sports, as well as the relationship between impersonal data and the vagaries of human behavior. He’s currently an executive in charge of the Philadelphia 76ers, but I promise you don’t need to be a fan of the Sixers or of basketball or of sports in general to enjoy this wide-ranging conversation.

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Daryl Morey received a bachelor’s in computer science from Northwestern University, and an MBA from the MIT Sloan School of Management. He served as general manager for the Houston Rockets from 2007 to 2020, and since November 2020 has been the President for Basketball Operations for the Philadelphia 76ers. He is founder and co-chair of the annual MIT Sloan Sports Analytics Conference. He was voted NBA Executive of the Year in 2018.

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