.......not of fools--them Markov chains, of course. And yes, this is about sports.
http://www.rdmag.com/ShowPR.aspx?PUBCODE=014&ACCT=1400000100&ISSUE=0804&RELTYPE=SOFT&PRODCODE=0000000&PRODLETT=BE&CommonCount=0Sports 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, the LRMC method has now identified 30 of the last 36 Final Four participants (83% 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 (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.
“As fans, we only get to see most tournament teams two or three times at most during the season, so our gut feelings about a team are really colored by how well or poorly they played the few times we've been watching,” says Sokol. “On the other hand, our system objectively measures each team’s performance in every game it plays, and mathematically balances all of those outcomes to determine an overall ranking.”