Engineers have crafted an algorithm that appears to predict the outcome of the NCAA Men's Division I Basketball Championship better than the experts, the sports writers, the polls and other computer models can. Working from historical data, the algorithm posted an 83 percent accuracy rate over the last nine years of NCAA brackets. This year, it predicts a victory by Kansas. The algorithm is but one win away from being right. The professors attribute the accuracy of their algorithm to its impartial, emotionless consideration of game results as well as its novel approaches to the home court advantage and close-game scores. Instead of gut feelings, the Georgia Tech algorithm, called Logistic Regression Markov Chain (LRMC), uses only scoreboard data, home court advantage and margin of victory. When considering home court advantage, its novelty consists in ranking how much playing at home helps a team win, rather than how much playing at home helps a team score points. Other computer models weigh points on a home court differently from those scored away from home. The second novelty of the Georgia Tech algorithm is its handling of close games as toss-ups, since close scores involve more luck than skill and thus are a poor indicator of which team is better. Other computer models rank close games as wins of equal merit to blowouts. The Georgia Tech engineers, however, argue that losing a close game should not count against a team as much as losing by a landslide.
Text: http://www.eetimes.com/showArticle.jhtml?articleID=207100028
