The NCAA men's basketball tournament is considered one of theleading wastes of time in American business, so it should come asno surprise that your friendly blogger would search high and low tofind a way to mix his love of college hoops with a little thing hisbosses like to call “work.”

It seems a trio of college professors has been employingpredictive analytics to predict the at-large teams that make up theNCAA tournament for the last 20 years. Using the analytics softwarefrom SAS, the professors have enjoyed a 94 percent success rate inputting together what they call their Dance Card. Two years ago,the professors were correct on 33 of the 34 at large bids (the restof the field is made up of teams that earn guaranteed bids throughtheir league championship tournaments.

“SAS analyzes huge amounts of information, pulls out what'simportant and ignores what's not. SAS predicts what's coming in thefuture, as opposed to simply describing what happened in the past,”says Jay Coleman, an operations management professor attheUniversityofNorth Florida.

Coleman explains the Dance Card reflects the trend in analyticstoward more prediction and less description.

“Predictability is a key part of business analytics that helpscompanies move from information to a decision, from the descriptiveto the predictive,” says Coleman. “With forecasting, data mining,optimization and other advanced predictive software from SAS,businesses can go beyond simply reporting on what has alreadyhappened and instead understand what will happen and where to gonext.”

So how did the profs do this year? About average. For 2012, theNCAA men's tournament has 31 automatic bids and 37 at-large bids.The Dance Card correctly picked 35 of the 37 for a 95 percentsuccess rate.

The analytics predictedtheUniversityofWashingtonandDrexelUniversitywould make the field.Instead, the selection committee choseColoradoStateandtheUniversityofSouthern Florida.ColoradoStatewas the team closestto the Dance Card bubble, but USF jumped over seven other schoolsto earn their spot in the tournament.

We've been writing a lot about predictive analytics lately andwe're helping our friends at Robert E. Nolan Co. distribute asurvey on how insurers are using these tools. The survey resultswill be shared in a Webinar on March 28, and in a whitepaper, whichwill be presented after the Webinar.

In the meantime, I need to get my hands on some good modelswhich will help me predict the winners in the tournament when thegames start this week so I can make a little money on this. Anyonewho has rolled out some analytics on who will win all the games isadvised to send their predictions my way.

Be warned, though. I will judge the quality of your picks bywhether or not you predict my Xavier Musketeers will defeat NotreDame in their game on Friday night. After all, emotion usuallyoverrules cold hard facts. Isn't that why the house alwayswins?