2026 NCAA Tournament Bracket Projection
Generated Thursday, March 12, 2026
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Projected #1 Seeds
The current #1 seeds in our projected NCAA Tournament bracket are Duke, Michigan, Arizona, and Florida. According to our model, Duke has the highest bracket score at 98.7, earning them the top spot. Their impressive 29-2 overall record and 17-1 conference record in the Atlantic Coast Conference contribute to their strong standing. With a NET ranking of #1 and a quad 1 record of 15-2, Duke has demonstrated their ability to perform well against top-level competition. Michigan, with a bracket score of 98.3, is close behind, boasting a 29-2 overall record and a 19-1 conference record in the Big Ten Conference.
Arizona and Florida round out the #1 seeds, with Arizona holding a bracket score of 96.5 and Florida at 92.4, according to our model. Arizona's 29-2 overall record and 16-2 conference record in the Big 12 Conference are notable, as is their quad 1 record of 14-2. Florida, with a 25-6 overall record and a 16-2 conference record in the Southeastern Conference, has a slightly lower NET ranking of #4, but still manages to secure a #1 seed. What separates these teams is their performance in quad 1 games, with Duke and Arizona having stronger records in this category. Michigan's dominance in the Big Ten Conference and Arizona's impressive overall record also set them apart from Florida, which has a lower overall win total despite a strong conference record.
The last four teams projected to be in the NCAA Tournament field are UCF, Tulsa, SMU, and New Mexico. UCF is holding on to a spot with a 9-9 conference record and a 6-6 mark in Quad 1 games, which helps to offset its relatively low NET ranking of 51. According to our model, UCF has a bracket score of 75.1, the highest among these four teams. Tulsa, on the other hand, has a strong overall record of 25-6, but its lack of Quad 1 wins, with only a 0-1 record, makes its position precarious. SMU has a better NET ranking of 39, but its 4-9 record in Quad 1 games is a concern, and its 8-10 conference record does not inspire confidence.
New Mexico is currently tied with SMU in terms of bracket score, according to our model, at 74.5. New Mexico's 13-7 conference record and 6-1 mark in Quad 2 games are positives, but its 2-6 record in Quad 1 games is a significant weakness. Tulsa's 74.7 bracket score, also according to our model, puts it just ahead of SMU and New Mexico. UCF's position is the most secure of the four, but only slightly, and any of these teams could be pushed out of the field with a loss or a strong finish by a team just outside the current field. Each of these teams needs to be careful, as their positions are tenuous at best, and their NET rankings, conference records, and quad records will be closely scrutinized in the final evaluation.
The first four teams out of the NCAA Tournament field are facing an uphill battle to secure a spot in the bracket. Texas is currently on the outside looking in with a 74.1 bracket score, according to our model. To play their way in, Texas needs to improve its Quad 1 record, which currently stands at 6-9. With a NET ranking of 42, Texas must close the gap in its resume by securing more high-quality wins. A stronger finish in the Southeastern Conference, where they currently sit at 9-9, would also bolster their case.
Indiana, Missouri, and Auburn are also on the cusp of the tournament field. Indiana, with a 73.9 bracket score, according to our model, and a NET ranking of 37, needs to address its Quad 1 woes, having gone just 3-11 in such games. Missouri, which has a 73.7 bracket score, according to our model, and a NET ranking of 60, must demonstrate it can compete against top-tier opponents, given its 5-7 Quad 1 record. Auburn, with a 73.1 bracket score, according to our model, and a NET ranking of 40, faces a steep climb due to its 4-12 Quad 1 record and 7-11 conference mark. For these teams, a strong finish to the season, including key wins in their respective conferences, is essential to closing the resume gaps and earning a spot in the tournament field. Texas, Indiana, Missouri, and Auburn must each focus on improving their respective weaknesses to have any chance of hearing their name called on selection day.
The current state of the bracket remains relatively stable, with Duke, Michigan, Arizona, and Florida maintaining their positions as the top seeds. According to our model, these teams continue to demonstrate the strongest resumes, solidifying their grip on the number one seeds. Notable trends include the emergence of Tulsa and SMU as the last four teams in, displacing Texas and South Florida from the bubble. The field size of 68 teams, comprised of 31 auto-bids and 37 at-large berths, will continue to undergo scrutiny as the season progresses. According to our model, the top seeds' consistent performance has resulted in minimal changes to the overall bracket landscape, with the primary focus shifting to the bubble teams and their ongoing battle for tournament inclusion.
How Our Bracket Model Works
Normalized 0–100 from rank position. The NCAA's own evaluation tool combining wins/losses and game-level efficiency across all Division I opponents.
Weighted quality score — Q1 wins +5, Q1 losses −1, Q2 wins +2.5, Q2 losses −2.5, Q3 wins +0.5, Q3 losses −5, Q4 wins 0, Q4 losses −8. Normalized 0–100.
SoR rank normalized 0–100. Measures how impressive a team's record is given the difficulty of its schedule — a 20-win team in a weak conference scores lower than a 20-win team in the ACC.
Adjusted offensive minus defensive efficiency (points per 100 possessions). Captures how dominant a team is regardless of pace. Normalized 0–100 across the field.
60% road record value + 40% SOS rank, both normalized. Rewards teams that schedule tough and win away from home — factors the committee explicitly values.
Final bracket score = weighted sum of all five components, scaled 0–100.
Our Model vs. The Selection Committee
The NCAA Selection Committee uses the same core inputs — NET rankings, quad records, strength of schedule, and road record — but applies subjective judgment to each case. Committee members can weigh injuries, recent form, head-to-head results, conference tournament performance, and what is often called the “eye test.”
Our model is purely data-driven: the same formula applied consistently to every team, with no adjustments for narrative or circumstance. That removes human bias — but it also means we can't account for context that only humans can evaluate. When the model and the committee diverge, it's often because of factors that don't yet show up in the numbers.