Machine Learning for March Madness Is a Competition In Itself

This year, 47 million Americans will spend an estimated $8.5 billion betting on the outcome of the NCAA basketball championships, a cultural ritual appropriately known as March Madness. Before the tournament starts, anyone who wants to place a bet must fill out a bracket, which holds their predictions for each of the 63 championship games. The winner of a betting pool is the one whose bracket most closely mirrors the results of the championship. For most people, making a bracket is a way to flex their knowledge of collegiate basketball and maybe make a few bucks by outguessing their colleagues in the office betting pool. But for the mathematically inclined, accurately predicting March Madness brackets is a technical problem in search of a solution.