LRMC Information Page

What is LRMC?

LRMC is a college basketball ranking system designed to use only basic scoreboard data (which two teams played, whose court they played on, and (in the "pure" version) what the margin of victory was). LRMC was created by Dr. Joel Sokol and Dr. Paul Kvam, and is now maintained, updated, and improved by Dr. Joel Sokol and Dr. George Nemhauser. Drs. Sokol, Kvam, and Nemhauser are all professors at Georgia Tech's H. Milton Stewart School of Industrial and Systems Engineering.

How good is LRMC?

The original research paper on LRMC (Kvam, P. and J.S. Sokol, "A logistic regression/Markov chain model for NCAA basketball", Naval Research Logistics 53, pp. 788-803) gives a mathematical description of the method, and reports statistical testing showing that LRMC is better than other standard methods at predicting NCAA tournament outcomes.

A more-recent non-mathematical summary of LRMC and its powerpoint-style equivalent points out three important highlights:

• LRMC is right more often: When LRMC and other NCAA tournament ranking methods disagree, the team LRMC ranks higher wins significantly more often than the other method's team.
• LRMC is particularly effective at sorting out the top teams, as measured by the last three rounds of the NCAA tournament, and it is more successful at identifying "surprise" Final Four teams. (We're not perfect, though--LRMC didn't expect George Mason's run in 2006!)
• LRMC is more effective at picking potential bubble teams; the teams it ranks in the "last-teams-in" bubble range tend to win more games than the teams that other methods rank in that area.

How is LRMC different from other methods?

In non-mathematical terms, LRMC differs from many other ranking systems most clearly in its treatment of home court advantage and win/loss outcomes.

• When determining the value of home court advantage, LRMC considers how much playing at home helps a team win, rather than how many "points" playing on a home court is worth.
• Our research shows that very close games are often "toss-ups"; the better team barely wins more than half the time. So, 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. In fact, a close loss to a top-tier team often shows more about a team's quality than a blowout win over a weak team; LRMC's ranking methodology takes this into account.

What does LRMC have in common with other methods?

LRMC is composed of the same two basic components that most ranking methods use:

• the quality of each team's results, and
• the strength of each team's schedule.

What rankings are available on this web site?

We currently calculate three different versions of LRMC:

• Pure LRMC is the most accurate predictor of NCAA tournament results, and uses exact margin of victory in its calculations.
• Capped LRMC uses a cap on the maximum margin of victory used in calculations. As the cap decreases, this version gets slightly less accurate than Pure LRMC, but still does well compared to other methods. The Capped LRMC pages use a limit of 15 points.
• LRMC(0) does not use margin of victory data at all in its calculations. It is somewhat less accurate than Pure LRMC, but is still competitive with many other methods, even ones that do use margin of victory.

Acknowledgements

In addition to Drs. Sokol, Kvam, and Nemhauser, Georgia Tech undergraduate students Kristine Johnson, Pete Kriengsiri, Dara Thach, Holly Matera, Jared Norton, Katie Whitehead, and Blake Pierce all assisted in various stages of data collection, analysis, and validation.