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ATLANTA (April 8, 2008) -- Sports professionals and fans get pretty emotional about their picks for the NCAA basketball tournament each year, and that emotion often clouds their judgment.

But three engineering professors at the Georgia Institute of Technology have created a computer ranking system, called LRMC, that consistently predicts NCAA basketball rankings more accurately than the AP poll of sportswriters and the ESPN/USA Today poll of coaches, formulas (the Ratings Percentage Index), other computer models (the Massey ratings and the Sagarin ratings), and even the tournament seeds themselves.

After correctly picking all four of this year’s finalists (and Kansas as this year’s champion), the LRMC method has now identified 30 of the last 36 Final Four participants (83 percent accuracy over the past nine years of NCAA tournaments) as one of the top two teams in their region. Over the same nine-year stretch, the seedings and polls have correctly identified only 23, and the RPI indentified 21.

LRMC predicted Kansas as champion, despite UNC, UCLA and Memphis being the top three ranked teams by most systems.

(Note: Kansas won 2008 NCAA championship in overtime).

LRMC (Logistic Regression Markov Chain) is a college basketball rankings system designed to use only basic scoreboard data, including which teams played, which team had home court advantage and the margin of victory. It was originally designed by Joel Sokol and Paul Kvam and has been maintained and improved by Sokol and George Nemhauser, all three optimization and statistics professors in the Stewart School of Industrial and Systems Engineering at Georgia Tech.

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Georgia Tech researchers have also been able to show that very close games are often "toss-ups," meaning the better team barely wins more than half the time. So, they determined that winning a close game shouldn’t be worth as much as winning easily, and losing a close game shouldn’t hurt a team’s ranking as much as losing badly. LRMC’s ranking methodology takes this into account.

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