Obviously, each of those coin flips isn’t 50/50; they’re more like 1 out of 140 for the 16 versus 1s, for instance. If you’re looking at a 16 seed beating a 1 seed, I think that’s happened once out of 140 games. I’m more of a probabilist than anything else, a mathematician. But a statistician would say, “Oh, maximum likelihood, the parameter to fit for that coin flip would be P, the probability of a heads is 1 out of 140.”

A couple of things I’m interested in research-wise is looking at team formation. My background is in quantitative finance and mathematical finance specifically, so we’re interested in valuation. What’s this thing worth? What’s this call option worth? What’s this annuity worth? What are the risks underneath it? And so for valuation, it’s swapping random play for a fixed contract.

Ars Technica: So what should one look at in a basketball team?

Albert Cohen: I think it’s similar to soccer. In soccer, you see passing networks within, and you see that evolve over time. I think that you’re going to see that centrality in a basketball team. You’re going to see these leaders pop up, like Oakland last year, or St. Peter’s. These teams are the underdogs, but if you paid attention, you’d maybe see some of those seeds were already there. So those are the numbers I’m interested in. How many people have gotten a perfect first-round bracket? I think that folks focus on the extremes, but getting 32 coin flips right—it’s happened. I’m interested in these derivative events. I think sports is ripe for this kind of thinking.

If a team is undervalued, they might be more likely to take risks because they have nothing to lose in a one-and-done situation like the NCAA tournament. If you’ve got a team that’s bold, understands each other, is willing to take risks but also holds each other accountable, I think that’s a dangerous team.

https://arstechnica.com/science/2025/03/march-madness-a-few-statistical-tips-could-give-you-an-edge/