The NCAA Division I men's basketball tournament is big business and March Madness is exciting, but is the selection process fair?
Using the SAS Analytics-powered "Dance Card" formula developed by Jay Coleman of the University of North Florida, Mike DuMond of Charles River Associates, and Allen Lynch of Mercer University, these professors uncovered selection committee bias in favor of particular conferences, as well as bias in favor of the teams with some representation on the NCAA men’s basketball selection committee itself. Bias in the seeding process appears to be even more pronounced than bias in the at-large selections.
Although many have surmised over the years that these types of biases exist, no study before this one has comprehensively examined the range of biases in both processes. With SAS analytics, the evidence is speaking for itself.
Check out the Dance Card rankings of all NCAA Division I men's basketball teams. Applying SAS analytics software, the professors have long predicted, with great accuracy, the "at-large" teams – those teams that did not get automatic bids to the tournaments.
In classes, these three professors use these predictive models as a way to illustrate the surging business analytics trend to their business school students. Right after showing students the Dance Card application, the professors show them six or seven business applications that use the same type of model. These students are getting real world experience with the power of analytics so they can embrace, influence and prepare for what will be, what can be, and what should be.