Our NIT Probabilities Are Live

Our model’s probabilities are live for the NIT and the NCAA Tournament. They aren’t anything too special, but we’re unaware of other NIT probabilities out there, so perhaps they may be of use. Like most of our models, they work by simulating the remaining of each tournament 10,000 times. Here is how the model works, in full detail.

The probabilities are almost entirely kenpom. They start with the kenpom ratings. They then adjust those ratings in each simulation as the simulated tournament goes on, accounting for completed results. For example: Last year, when Fairleigh Dickinson beat Purdue, they naturally had a much better kenpom rating entering the second round than they did before the upset. In any scenario in which FDU reached the second round, they would be known to be better than they were thought to be entering the tournament. Our model accounts for this. However.

Our model does not run the simulations fully “hot.” It doesn’t adjust as much to each result as kenpom itself does. Instead, it runs them “lukewarm,” because present kenpom ratings tend to have stronger predictive power of future kenpom ratings than we get when we let the results go full bore. Also: We don’t account for other teams’ results the way kenpom does. We adjust it as an elo system, using his ratings as a starting point. This doesn’t create too significant of differences, but we are not fully reverse engineering kenpom over here. No college basketball genome project for us.

We’ll talk a little tomorrow about paths in the NCAA Tournament. Houston’s is better than UConn’s. That’s the high level. As for the NIT:

The favorites line up in kenpom order until we get to the seventh spot on the list, where Seton Hall jumps Iowa, Providence, Xavier, Virginia Tech, and UCF. Seton Hall is a team very much helped by where the bracket landed. Their likeliest first two opponents are two of the four worst teams, per kenpom, in the NIT. If North Texas wins in Baton Rouge, the path will get a little harder, but Seton Hall has a convenient road to the quarterfinals.

Iowa, contrarily, has a tough path. Kansas State was a team we wouldn’t have been surprised to see hosting a game. Playing at Utah is hard, and UC Irvine would be a competitive guest. Villanova’s the second-best team in the tournament on paper.

There are no home underdogs in the first round. Every home team is good enough for the home game to make the difference.

Only five teams are likelier than not to make it to the quarterfinals. Everyone else is likeliest to lose in the first or second round.

Cincinnati and Indiana State—the third and fourth-likeliest champions—are in the same region. Seton Hall’s region has none of the six likeliest champions.

Xavier is the likeliest unseeded team to make a run, followed by North Texas and Kansas State.

Butler’s home-court advantage in the Final Four would help enough that they are the likeliest team to win the NIT if they make the NIT Final Four. They check in around 35% in those scenarios. Wake’s at 33%. Butler will most likely have to play the second round and the quarterfinals on the road if they get there, but for what it’s worth, those would be within a few hours of Indianapolis as well.

Again, we’ll talk path a little bit tomorrow, and we’ll talk about I use all this to fill out a bracket. The nice thing, though? Using this doesn’t really help that much. It’s still chaos. That’s what makes it fun.

The links, again:

The archives (we’ll update the archive again after the Tuesday and Wednesday games):

TeamSecond RoundQuarterfinalsSemifinalsChampionshipChampion
Wake Forest77.0%58.1%40.7%25.7%13.8%
Villanova76.2%55.3%37.2%19.9%11.8%
Cincinnati73.7%54.0%29.9%16.3%9.3%
Indiana State72.9%52.0%33.8%17.3%9.2%
Ohio State79.4%54.2%26.0%15.5%7.8%
Utah71.4%46.4%23.2%11.8%6.4%
Seton Hall72.6%49.2%30.4%13.0%5.5%
Princeton65.0%38.9%20.4%9.1%4.0%
Providence68.2%34.6%19.2%8.5%3.9%
Iowa65.8%29.7%14.3%7.0%3.5%
Butler66.9%25.6%9.9%5.8%3.5%
Virginia Tech70.5%29.7%13.5%7.5%3.3%
UCF69.4%26.4%11.3%5.0%2.5%
Bradley69.3%25.7%11.9%5.1%2.4%
Xavier49.0%17.9%7.1%3.8%1.9%
LSU55.4%21.6%8.0%2.9%1.2%
North Texas44.6%18.5%7.0%2.8%1.1%
Kansas State34.2%13.3%4.8%2.2%1.1%
SMU27.1%11.4%4.2%1.8%0.9%
UNLV35.0%13.8%6.0%2.4%0.9%
San Francisco26.3%11.7%4.3%1.8%0.8%
Georgia51.0%14.4%4.7%2.2%0.8%
Boston College31.8%12.6%5.5%2.1%0.7%
Minnesota33.1%10.9%3.4%1.7%0.7%
UC Irvine28.7%10.6%3.4%1.4%0.6%
Appalachian State23.0%9.7%3.1%1.4%0.5%
Richmond29.5%9.8%3.1%1.4%0.5%
VCU23.8%9.5%3.3%1.2%0.4%
South Florida30.6%8.8%2.7%0.9%0.4%
Loyola (IL)30.7%8.7%2.6%0.9%0.4%
Saint Joseph’s27.4%10.7%3.6%1.1%0.4%
Cornell20.7%6.4%1.8%0.8%0.2%
TeamFirst RoundSecond RoundSweet 16Elite 8Final 4ChampionshipChampion
Houston100.0%97.5%79.2%57.1%43.9%28.3%16.9%
UConn100.0%99.0%83.1%54.1%37.0%26.0%16.7%
Purdue100.0%98.6%78.2%56.7%36.8%20.6%11.4%
Auburn100.0%89.2%66.8%32.0%19.9%13.0%7.3%
Arizona100.0%95.5%67.9%43.9%26.8%12.3%6.0%
Iowa State100.0%93.4%70.4%42.8%19.0%11.5%6.0%
Tennessee100.0%96.4%67.5%42.8%22.0%11.4%5.6%
North Carolina100.0%98.1%61.3%36.7%19.3%7.9%3.6%
Duke100.0%87.1%56.7%23.0%14.3%7.1%3.4%
Creighton100.0%88.1%62.9%31.7%14.6%6.4%2.8%
Illinois100.0%88.5%55.6%29.1%11.3%6.0%2.7%
Marquette100.0%89.6%54.5%32.7%12.1%5.8%2.5%
Baylor100.0%90.0%53.9%25.5%13.0%4.7%1.9%
Alabama100.0%82.8%50.2%24.7%12.8%4.9%1.8%
Gonzaga100.0%71.6%44.1%17.5%8.5%3.5%1.4%
Kentucky100.0%86.2%49.6%24.0%7.6%3.1%1.1%
BYU100.0%77.4%36.4%16.1%4.9%2.2%0.9%
Michigan State100.0%55.6%22.8%11.5%5.1%1.8%0.8%
Wisconsin100.0%69.3%31.2%9.5%5.2%2.2%0.8%
Saint Mary’s100.0%65.1%32.5%14.5%6.3%2.2%0.7%
Kansas100.0%72.4%36.1%12.3%5.2%1.9%0.6%
San Diego State100.0%80.7%27.1%8.0%3.5%1.5%0.5%
Texas Tech100.0%63.5%33.0%14.8%4.6%1.6%0.5%
New Mexico100.0%54.8%25.5%10.1%4.3%1.3%0.4%
Florida100.0%49.4%21.8%11.2%3.5%1.3%0.4%
Texas100.0%57.9%20.2%9.9%3.8%1.5%0.4%
Mississippi State100.0%44.4%15.8%7.5%2.8%0.9%0.4%
Colorado55.6%29.3%13.0%7.1%2.2%0.8%0.3%
Nebraska100.0%55.2%12.0%5.0%2.3%0.9%0.3%
Clemson100.0%45.2%19.0%6.6%2.7%0.8%0.3%
Dayton100.0%51.2%16.2%7.1%2.9%0.7%0.2%
TCU100.0%56.5%13.1%6.2%2.4%0.7%0.2%
Nevada100.0%48.8%15.2%6.7%2.6%0.6%0.2%
South Carolina100.0%55.2%19.7%6.0%1.8%0.5%0.2%
Florida Atlantic100.0%51.0%8.5%2.8%0.9%0.4%0.1%
Northwestern100.0%49.0%8.2%2.4%0.7%0.3%0.1%
Texas A&M100.0%44.8%8.5%3.2%1.3%0.4%0.1%
Boise State44.5%21.3%8.8%4.3%1.2%0.3%0.1%
Washington State100.0%53.2%15.4%6.0%1.6%0.5%0.1%
Utah State100.0%43.5%8.6%3.5%1.2%0.3%0.1%
Colorado State61.3%28.3%8.7%3.9%1.3%0.4%0.1%
NC State100.0%36.5%14.7%5.2%1.2%0.4%0.1%
Oregon100.0%44.8%14.2%4.0%0.9%0.2%0.1%
Drake100.0%46.8%12.5%4.2%0.7%0.2%0.1%
Grand Canyon100.0%34.9%12.8%4.3%1.1%0.2%0.1%
McNeese100.0%28.4%12.0%2.6%0.8%0.2%0.0%
James Madison100.0%30.7%8.9%1.8%0.5%0.1%0.0%
Virginia38.7%13.7%3.2%1.2%0.3%0.1%0.0%
Duquesne100.0%22.6%5.1%1.2%0.1%0.0%0.0%
College of Charleston100.0%17.2%4.5%0.9%0.2%0.0%0.0%
Yale100.0%10.8%3.9%0.4%0.1%0.0%0.0%
Samford100.0%27.6%7.8%1.3%0.3%0.0%0.0%
UAB100.0%19.4%2.2%0.3%0.1%0.0%0.0%
Vermont100.0%12.9%3.2%0.4%0.1%0.0%0.0%
Morehead State100.0%11.5%2.9%0.5%0.1%0.0%0.0%
Akron100.0%11.9%3.3%0.4%0.0%0.0%0.0%
Oakland100.0%13.8%2.7%0.4%0.0%0.0%0.0%
South Dakota State100.0%6.6%1.7%0.2%0.0%0.0%0.0%
Western Kentucky100.0%10.4%1.9%0.3%0.0%0.0%0.0%
Colgate100.0%10.0%1.6%0.2%0.0%0.0%0.0%
Longwood100.0%2.5%0.4%0.1%0.0%0.0%0.0%
Long Beach State100.0%4.6%0.6%0.1%0.0%0.0%0.0%
Saint Peter’s100.0%3.6%0.4%0.1%0.0%0.0%0.0%
Wagner44.9%0.8%0.0%0.0%0.0%0.0%0.0%
Stetson100.0%1.1%0.2%0.0%0.0%0.0%0.0%
Montana State58.6%1.0%0.1%0.0%0.0%0.0%0.0%
Howard55.1%1.1%0.1%0.0%0.0%0.0%0.0%
Grambling State41.5%0.4%0.0%0.0%0.0%0.0%0.0%
The Barking Crow's resident numbers man. Was asked to do NIT Bracketology in 2018 and never looked back. Fields inquiries on Twitter: @joestunardi.
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