2026 NCAA Tournament Bracket Projection
Generated Thursday, February 26, 2026
Field
Bids
Bids
Projected #1 Seeds
The current #1 seeds in our projected NCAA Tournament bracket are Michigan, Duke, Arizona, and Gonzaga. Michigan earned the top line with a 26-2 overall record and a 16-1 mark in the Big Ten Conference. According to our model, Michigan's bracket score of 99.2 is the highest among the four teams, driven by a strong 11-1 record in Quad 1 games and a 9-1 record in Quad 2 games. Duke, on the other hand, boasts the top NET ranking at #1, with a 25-2 overall record and a 14-1 record in the Atlantic Coast Conference. Duke's 11-2 record in Quad 1 games and undefeated 6-0 mark in Quad 2 games also contribute to its high standing.
Arizona and Gonzaga round out the #1 seeds, with Arizona posting a 26-2 overall record and a 13-2 mark in the Big 12 Conference. Arizona's 12-2 record in Quad 1 games is among the best in the country, and its undefeated 5-0 mark in Quad 2 games further solidifies its position. Gonzaga, meanwhile, has a 28-2 overall record and a 16-1 mark in the West Coast Conference, with a 6-1 record in Quad 1 games and a 5-0 record in Quad 2 games. According to our model, Gonzaga's bracket score of 93.9 is the lowest among the four teams, but its strong conference record and overall performance still warrant a #1 seed. Michigan, Duke, and Arizona have higher bracket scores, at 99.2, 98.6, and 97.1, respectively, according to our model.
The last four teams projected in the NCAA Tournament field are holding on to their spots by a slim margin. Texas is currently sitting at a 76.7 bracket score according to our model, with a 5-8 record in Quad 1 games and a 2-2 record in Quad 2 games. Their 8-7 conference record and NET ranking of 40 are also factors in their tenuous position. Ohio State, with a 76.3 bracket score according to our model, is also on the bubble, despite a strong 6-1 record in Quad 2 games. However, their 1-10 record in Quad 1 games is a significant concern. Auburn and Indiana are also in similar positions, with Auburn's 5-11 Quad 1 record and Indiana's 2-10 Quad 1 record being major liabilities.
Texas is holding on due to its respectable conference record and decent NET ranking, but a poor performance in their remaining games could push them out. Ohio State's strong Quad 2 record is helping to offset their poor Quad 1 performance, but they need to avoid any further losses to remain in the field. Auburn's NET ranking of 35 is one of the best among these four teams, but their 6-9 conference record is a concern. Indiana, with a 75.6 bracket score according to our model, is the most vulnerable of the four, and any further losses could drop them out of the tournament field. Texas, Ohio State, Auburn, and Indiana all need to finish the season strong to ensure their spots in the NCAA Tournament, as a poor finish could allow another team to leapfrog them and take their place.
The first four teams on the outside looking in are San Diego State, TCU, Missouri, and Tulsa. According to our model, these teams have bracket scores of 75.5, 75.2, 75.2, and 74.8, respectively. San Diego State needs to improve its Quad 1 record, currently sitting at 2-5, to bolster its resume. With a NET ranking of 43, the Aztecs must close the gap in their top-tier performance to move into the field. TCU, on the other hand, has a more balanced Quad 1 and Quad 2 record, but its NET ranking of 47 and 8-7 conference record leave room for improvement.
Missouri and Tulsa face similar challenges in strengthening their resumes. Missouri's Quad 1 record of 4-5 is respectable, but its Quad 2 record of 4-4 and NET ranking of 60 are concerns. The Tigers must win out in conference play and potentially pick up a marquee win to move up the bracket. Tulsa, with a 23-6 overall record, has a strong conference mark of 11-5, but its lack of Quad 1 wins, with only one opportunity, is a significant gap in its resume. According to our model, Tulsa's bracket score of 74.8 indicates that the Golden Hurricane need to find a way to overcome their limited top-tier schedule to play their way into the tournament. San Diego State, TCU, and Missouri must focus on improving their performance against top opponents to close the resume gaps and move into the field.
The overall state of the bracket remains relatively stable, with Michigan, Duke, Arizona, and Gonzaga holding onto their number one seeds. According to our model, these teams continue to demonstrate the strongest resumes, with a significant gap between them and the next tier of contenders. A notable trend is the emergence of Ohio State as a bubble team, securing a spot among the last four in, while UCLA has fallen out of consideration. The field of 68 teams is rounded out by 31 auto-bids and 37 at-large selections, with the current top seeds well-positioned to maintain their standing as the season progresses, although our model will continue to monitor their performance and adjust the bracket accordingly.
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.