Our NIT Bracketology is updated, but fair warning: Our model gets the updated NET, SOR, and KPI rankings a day late, which can sometimes make it underreact or overreact to a game’s result. After a day with as many games as yesterday had, we expect there to be more shuffling tomorrow in our model’s bracketology and probabilities, even among teams who don’t play today.
Seed List(s)
Rather than describe the bubble situations ourselves, we’re going to list our model’s current view of the NIT picture. Below is each semi-possible NIT team, their NIT probability, their median NCAAT Selection Rank, their median NIT Selection Rank, and what position that leaves them in with our bracketologies. Again, we’ll have a full update tomorrow, and we’ll also have some thoughts below, but this should hopefully be a good, quick view of where our model tentatively sees the field.
As always, these are our model’s predictions for where the field will end up, not where the field currently stands. Also: By “Selection Rank,” we mean this is where each committee would have the team on a hypothetical master seed list, ordered by how strong they are in the relevant selection criteria, which is different from the relevant seeding criteria.
| Team | Median NCAAT Selection Rank | Median NIT Selection Rank | NIT Probability | Current Bracket Position |
| Boise State | 31 | 32 | 6.4% | NCAAT At-Large |
| Mississippi State | 32 | 32 | 7.6% | NCAAT At-Large |
| Texas Tech | 32 | 34 | 7.3% | NCAAT At-Large |
| Michigan State | 33 | 29 | 9.6% | NCAAT At-Large |
| Nebraska | 35 | 35 | 9.4% | NCAAT At-Large |
| Villanova | 35 | 39 | 19.3% | NCAAT At-Large |
| Nevada | 35 | 37 | 8.6% | NCAAT At-Large |
| Oklahoma | 37 | 41 | 24.9% | NCAAT At-Large |
| Florida Atlantic | 40 | 38 | 31.2% | NCAAT Auto |
| Saint Mary’s | 42 | 31 | 23.2% | NCAAT At-Large |
| Wake Forest | 42 | 39 | 40.5% | NCAAT At-Large |
| St. John’s | 42 | 44 | 31.6% | NCAAT At-Large |
| Indiana State | 42 | 37 | 28.8% | NCAAT Auto |
| TCU | 43 | 36 | 33.6% | NCAAT At-Large |
| Colorado | 43 | 36 | 40.7% | NCAAT At-Large |
| Virginia | 43 | 48 | 32.3% | NCAAT At-Large |
| New Mexico | 43 | 38 | 39.0% | Bid Thief Seat |
| Utah | 44 | 47 | 45.5% | Bid Thief Seat (NIT Auto) |
| Texas A&M | 48 | 57 | 57.9% | NIT 1-Seed (NIT Auto) |
| Seton Hall | 48 | 58 | 62.1% | NIT 1-Seed (NIT Auto) |
| Princeton | 59 | 48 | 56.2% | NCAAT Auto |
| Drake | 54 | 51 | 71.8% | NIT At-Large |
| Pitt | 61 | 51 | 91.9% | NIT Auto |
| Grand Canyon | 55 | 52 | 27.6% | NCAAT Auto |
| Iowa | 54 | 55 | 74.2% | NIT Auto |
| Cincinnati | 58 | 55 | 84.5% | NIT Auto |
| Mississippi | 54 | 57 | 84.2% | NIT Auto |
| Syracuse | 54 | 58 | 82.3% | NIT At-Large |
| Virginia Tech | 57 | 58 | 89.4% | NIT Auto |
| James Madison | 61 | 58 | 61.5% | NIT At-Large |
| Ohio State | 59 | 61 | 93.2% | NIT Auto |
| McNeese | 68 | 61 | 17.4% | NCAAT Auto |
| Providence | 55 | 62 | 83.3% | NIT At-Large |
| Memphis | 63 | 64 | 86.6% | NIT At-Large |
| Richmond | 63 | 64 | 84.1% | NIT At-Large |
| South Florida | 64 | 66 | 79.8% | NIT At-Large |
| Butler | 66 | 67 | 95.9% | NIT At-Large |
| Bradley | 72 | 67 | 78.1% | NIT At-Large |
| SMU | 78 | 67 | 74.0% | NIT At-Large |
| Oregon | 67 | 68 | 90.7% | NIT Auto |
| Xavier | 78 | 68 | 73.1% | NIT Auto |
| Kansas State | 63 | 71 | 87.5% | NIT At-Large |
| Appalachian State | 71 | 74 | 54.6% | NIT At-Large |
| Maryland | 78 | 74 | 80.0% | NIT At-Large |
| St. Bonaventure | 77 | 76 | 70.3% | NIT At-Large |
| Minnesota | 86 | 77 | 74.9% | NIT At-Large |
| VCU | 77 | 78 | 60.1% | NIT At-Large |
| Samford | 80 | 78 | 35.8% | NCAAT Auto |
| Loyola (IL) | 76 | 80 | 51.6% | NIT At-Large |
| UNLV | 72 | 81 | 48.6% | NIT At-Large |
| Yale | 84 | 81 | 26.8% | NIT At-Large |
| UC Irvine | 86 | 81 | 6.3% | NCAAT Auto |
| LSU | 71 | 82 | 77.1% | N/A |
| UCF | 99 | 82 | 66.6% | NIT Auto |
| NC State | 76 | 82 | 53.6% | N/A |
| Washington | 90 | 83 | 66.8% | N/A |
| San Francisco | 91 | 86 | 25.2% | N/A |
| UMass | 92 | 86 | 27.2% | N/A |
| Rutgers | 173 | 88 | 28.6% | N/A |
| Florida State | 174 | 89 | 23.2% | N/A |
| Duquesne | 84 | 91 | 18.4% | N/A |
| Cornell | 90 | 91 | 5.4% | N/A |
| Miami (FL) | 92 | 93 | 16.5% | N/A |
| Indiana | 177 | 96 | 9.5% | N/A |
| Georgia | 176 | 98 | 9.4% | N/A |
| USC | 195 | 193 | 7.6% | N/A |
Thought #1: Automatic Bids and the NIT/CBI Bubble
The discrepancies between the NIT probabilities of Yale and teams like LSU and Washington are due to the complications of automatic bid possibilities. Yale has a high probability of receiving an NCAAT automatic bid by winning the Ivy League Tournament. They also have a high(er) probability of suffering a devastating loss. LSU and Washington have strong possibilities of receiving NIT automatic bids. LSU could get one either by passing Ole Miss in NET (possible) or seeing Texas A&M make the NCAA Tournament (still possible). Washington could get one if both Utah and Colorado make the NCAA Tournament field (again, still possible).
Thought #2: .500 and Sub-.500 Records
The NCAA Tournament won’t take a team as an at-large if their overall record is .500 or worse, something which happens a lot for Rutgers, Florida State, Indiana, Georgia, and USC in our simulations. We don’t yet know how the NIT will handle sub-.500 NIT candidates, but historically, .500 teams have been fine and sub-.500 teams haven’t been.
We told our model to let the NIT accept sub-.500 at-large candidates 10% of the time, provided all their other metrics were deserving of inclusion. So, USC is eligible for an NIT automatic bid, but they have little chance at an at-large. Meanwhile, all of Rutgers, Florida State, Indiana, and Georgia end up .500 in their median simulation, making it not a concern for them.
Thought #3: The NCAAT/NIT Bubble
If I was following better bracketologists than myself and making my best guess this morning at their opinions of the cut line, I would probably switch our field as follows:
| Team | Objective Model | Subjective Guess |
| Wake Forest | NCAAT | NCAAT |
| St. John’s | NCAAT | NCAAT |
| Colorado | NCAAT | Bid Thief Seat |
| Virginia | NCAAT | NCAAT |
| New Mexico | Bid Thief Seat | Bid Thief Seat |
| Utah | Bid Thief Seat | NIT |
| Seton Hall | NIT | NCAAT |
| Providence | NIT | NIT |
I’m including Wake Forest, St. John’s, and Virginia because they’re all receiving a lot of bubble talk, even though I agree with our model on them all.
My reasoning is this, team by team:
- Wake Forest: Yesterday’s loss wasn’t a bad one. They’re just in the bubble spotlight because of the Duke game, and the loss to Notre Dame primed everyone to view them as back in trouble. The bubble, however, doesn’t work in a linear fashion, and what Wake’s résumé generally boils down to is this: They’re good enough for the NCAAT committee. They’re not quite deserving enough for the NCAAT committee. That first is stronger than the second, which puts them narrowly ahead of the cut line. Then, there’s the question of Q1 wins, but our model expects them to get another one of those over Clemson, and I believe it. Being better than you are deserving isn’t a great recipe for a bubble team on Selection Sunday. Right now, though, it implies better things to come for the Deacs. The Duke win moved the needle further for them than the Notre Dame loss. Because of the committee’s emphasis on Q1 wins.
- St. John’s: We’re starting to see more people put the Johnnies in the projected field. Again, we think future results will be kind to them. Their likeliest Big East Tournament position is the 5-seed, opening against Seton Hall. That’s a great game to use to play yourself in.
- Colorado: Our model still expects Colorado to lose once more this regular season, and it still has them in the NCAA Tournament field. I do not trust our model on this, and this is why: The Buffaloes would have Q1 wins, but they’d be the road wins over Washington and Oregon, if the Oregon win even happens. They might pick up another in the Pac-12 Tournament, but they’d have to either knock off Arizona or play their way to playing Washington State to get that win. If the committee turns a kind eye to the injuries, the Buffs should be in, but right now, I don’t see awareness of those injuries being high enough. I’d imagine the committee leaves them out, if all goes roughly according to the median scenario from here. I think they might need a 4–1 or 5–1 record down the stretch to make it happen. That is possible enough, though, to keep them ahead of Providence, Utah, Texas A&M, Pitt, Drake, Iowa, etc.
- Virginia: As with Wake, I think the emotion of the reaction to yesterday’s performance outpaced the bubble impact. Virginia is bad right now. But they have a decent enough résumé to end up fine in the end, especially if there aren’t very many bid thieves. It was a bad loss, but it’s still only a road loss to Duke.
- New Mexico: I don’t know what to make of New Mexico, but I trust our model pretty well on them. The bad loss was so bad, but it’s only one bad loss, and they do have a couple Q1 wins, both of which are over teams expected to make the field, and one of which came on the road. There’s also a decent possibility they get Utah State in the MWC quarterfinals and grab another one.
- Utah: This isn’t a disagreement with our model over Utah. It’s about Seton Hall, whose promotion from our model’s estimate of their position pushes the Utes downwards in my guess.
- Seton Hall: The Q1A wins are a big deal to the committee and not something we’ve found a way yet to reliably emphasize in our model. This is a known weakness of our formula. Seton Hall beat UConn and Marquette. I think that’s enough to push them across the line if they go 2–1 from here (which is likelier than 1–2 entering today’s game, but probably won’t be likelier after today’s game).
- Providence: Providence does have wins over Marquette and Creighton, but I don’t see those carrying the same weight as UConn and Marquette, especially since the Marquette win here came with Bryce Hopkins still in the picture. Providence just isn’t as close to the cut line as Seton Hall is before all those little things get considered, and Wisconsin’s fade is hurting the Friars. They’ve got a tough stretch left. There’s time, but I’m guessing the industry is going to agree that they need to beat UConn next weekend or make serious MSG noise to get into the field.
Overall? Our model hasn’t historically been a great bracketologist around this particular margin. It’s been stronger on the NIT/CBI cut line. It is, however, good at predicting future results, because it relies on kenpom to predict those, and kenpom’s great at it.
Some of our model’s oddities come from its accounting for future results. Some come from its shortcomings. We think the Seton Hall estimate is happening because of shortcomings. We’re not too worried just yet about the others.
