Operations research is noted for the strong tools it provides decision makers.
In the NCAA tournament, there are a staggering 9.22 billion billion possible tournament outcomes, Professor Kaplan explains. Yet if one filled out a slate of predictions completely at random subject only to a consistency in prediction constraint, one could expect to predict the winners correctly about a third of the time. Professor Kaplan and Deputy Dean Garstka explain that the object in an office pool is to maximize total pool points, where different points are awarded for different correct winning predictions. Their model studies the structure of single elimination tournaments and shows how to efficiently calculate the mean and variance of the number of correctly predicted wins or, more generally, the total points earned in an office pool for a given slate of predicted winners. They then show how to determine optimal office pool predictions that maximize the expected number of points earned in the pool.