The goal of every team in the NCAA tournament is to survive and advance. And, if you want to win your March Madness pool, your goal should be to predict which teams will do just that.
Most prediction systems view the NCAA tournament as an extension of the regular season. While that may be the best way to pick the most games in the tournament correctly, I do not believe it is the way to predict the most important games correctly. Correctly selecting a team to make the Championship Game can more than make up for a relatively poor first round.
That is why, building off of Ken Pomeroy’s great work, for the past two years I have been publishing a model of the NCAA tournament based on Survival Analysis. Academic researchers use Survival Analysis to determine whether new pharmaceutical drugs or treatments are effective. I co-opted the framework to try to discover something truly important: the path to bragging rights over your friends.
The precise details are contained in last year’s post, but the general idea is that the best way to win an office pool is to empirically determine which teams have the traits that best predict their survival to the Final Four, Championship Game, and eventual National Championship. Using Survival Analysis is a natural fit.
Does it work? Over the last six NCAA tournaments, using out of sample testing, the model has outperformed the RPI, BPI (unfortunately the BPI’s performance is behind ESPN Insider’s paywall), and Pomeroy rankings:
The 2013 Model
My model this year is almost exactly the same as last year–I log-transformed the experience variable, but that was the only change–but I have added predicted probabilities for every potential NCAA tournament matchup.
A brief diversion or those of you interested in the math (skip ahead a section if you are not): the Cox Proportional Hazards model yields the predicted probability of any team “dying” or losing at a given time. If we know that two teams meet and one must lose, we can calculate the probability of Team A defeating Team B as:
I used this formula and the predicted Hazard Rates to predict all possible paths for a team. For instance, if Indiana makes the Sweet 16, they could play any one of UNLV, California, Syracuse, or Montana. The odds of the Hoosiers advancing to the Elite Eight by beating UNLV is the probability that Indiana beats UNLV times the probability that Indiana plays UNLV. Summing those probabilities for all four potential opponents, we get the overall odds that Indiana would reach the Elite Eight.
The Model Predictions
Without further ado, I present the full predicted tables for each region. Some quick notes: similar to the Upset Model, this Survival Model does not do well with very low probability events. Thus it overrates the chances of the 15 and 16 seeds pulling upsets. If you believe the true chances of a 16 pulling an upset are around two percent, you should adjust the Final Four and Championship probabilities for the 1 seeds up about one percentage point each.
Additionally, the model is fairly chalky this year and is similar to Ken’s final rankings. Despite incorporating experience and regular season wins over NCAA tournament teams, the model still picks Florida to win it all. The Gators, however, are essentially a tossup (51.5 percent) against Louisville in a potential Championship Game matchup.
Louisville is the clear favorite here, with a predicted 34.5 percent chance of advancing to Atlanta. Six seed Memphis looks vulnerable to either St. Mary’s or MTSU, who are rated almost identically by the model. Also note that if Creighton is able to beat Duke, they have the potential to also beat Michigan State (47 percent chance).
Gonzaga remains the slight favorite here, but has a very tough potential matchup with Pitt in the Round of 32. If you are looking for a surprise in the first round, Boise State may be a good pick. The model predicts Kansas State to lose to Wisconsin, so if you believe the Badgers are that good, picking the Broncos may be a good risk-reward at 41 percent odds to win.
As many pundits have pointed out, Indiana appears to have been gifted a weak region. Miami and Marquette are by far the weakest two and three seeds. Bucknell has the best odds of any double-digit seed of reaching either a Sweet 16 or an Elite Eight. Davidson, too, has great odds of pulling an upset for a 14 seed.
What do you do with a problem like the Gators? The “eye test” says that Florida cannot win close games and will lose early. Most tempo-free based rankings put the Gators up top. My predictions have Florida not winning the NCAA’s 84 percent of the time, but they are still the overall favorite.
Look out for Michigan in this bracket. Of all the teams in the field, the Wolverines have the highest variance of prediction (i.e., my model predicts the widest distribution of outcomes around the most likely one). This could mean an early exit to Nate Wolters and South Dakota State, or a run to the Elite Eight with a win over Kansas.
Picking straight down the line of predicted probabilities on these picks may not be the best strategy for your pool. If you are in a very large pool, you should pursue a riskier strategy than chalk in order to maximize your expected value. Regardless of your pool size, I believe the Survival Analysis predictions here can help you increase your chances of winning bragging rights over your friends.
(Ed. note: another version of this analysis appears on Sports Illustrated’s website.)