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Rock M Bracket Racket: Projecting The At-Large Field — February 20, 2023

See our latest bracket projections for this year’s NCAA Men’s Basketball Tournament

rock m tology bracketology

If you write about college basketball on the internet, but don’t have your own bracket projection, are you even covering college basketball? Nothing goes together like rankings and the worldwide web. We here at Rock M have officially entered the fray.

How to Read Projection: The teams are broken down by seed line with their S-Curve ranking in parentheses. This is our attempt to rank teams in the same fashion the NCAA tournament committee does (1-68). Teams bolded are Auto-Qualifiers based on having the highest formula rating in their respective league. The list “snakes,” to show the matchups prior to bracketing principles. I.e. The Highest rated 8-seed faces the lowest rated 9-seed, prior to bracketing principles (e.g., distance from home, conference affiliation, prior games, etc.)


Before we begin, the NCAA tournament committee released a sneak preview of their top four seeds on Saturday. Here is the list along with how they compared to these projections last Monday.

Now, let’s get on with the good stuff.

February 20, 2023, S-Curve Projection

  1. Alabama (1) | Kansas (2) | Houston (3) | Purdue (4)
  2. Baylor (8) | UCLA (7) | Arizona (6) | Texas (5)
  3. Virginia (9) | Kansas St. (10) | Tennessee (11) | Iowa St. (12)
  4. Xavier (16) | Gonzaga (15) | Marquette (14) | Indiana (13)
  5. Connecticut (17) | Creighton (18) | St. Mary’s (19) | Northwestern (20)
  6. Illinois (24) | Miami Fl (23) | San Diego St. (22) | TCU (21)
  7. Maryland (25) | Iowa (26) | Providence (27) | Michigan St. (28)
  8. Arkansas (32) | Auburn (31) | Duke (30) | Rutgers (29)
  9. Kentucky (33) | Texas A&M (34) | North Carolina St. (35) | Mizzou (36)
  10. Boise St. (40) | Oklahoma St. (39) | Florida Atlantic (38) | Nevada (37)
  11. Memphis (41) | Mississippi St. (42) | Pittsburgh (43) | West Virginia (44) | USC (45) | Utah St. (46)

Last Four BYES: Oklahoma St. (39) | Boise St. (40) | Memphis (41) | Mississippi St. (42)

Last Four Teams IN: Pittsburgh (43) | West Virginia (44) | USC (45) | Utah St. (46)

First Four OUT: Oregon (47) | Texas Tech (48) | North Carolina (49) | Wisconsin (50)

Next Four OUT: Oklahoma (51) | New Mexico (52) | North Texas (53) | Michigan (54)

Auto-Bids Bolded


NCAA Basketball: NCAA Tournament-UC Santa Barbara at Creighton Christopher Hanewinckel-USA TODAY Sports

How it Works: At this juncture in the season, we’re only going to be looking at potential at-large teams and where they slot in the “S-Curve.” The only consideration given to automatic qualifiers — conference tournament winners — will be to “extend” the at-large pool. That is to say, there are 32 auto-bids and 36 at-large bids. When a team considered a “lock” for inclusion wins their league’s auto-bid, an extra at-large team grows its wings. As we move along further into the season, we’ll start to look at potential conference tourney winners as well.

This bracket projection is 100% retrospective. Meaning: it looks at what the bracket would be if the season ended TODAY. Many bracket projections consider prospective results. This one doesn’t. There are benefits and drawbacks to both. I’ve chosen to live in the present for accuracy’s sake.

These are not necessarily where I would project these teams. Rather, whatever the formula spits out, you see.

Why This One is Different: Several years back I had the brilliant (read: time-consuming) idea to study the selection committee’s decision-making as it pertained to a team’s “team sheet.” For the uninitiated, a team sheet is merely a resume of a team’s qualifications for inclusion to the annual March tournament. Being the inherently curious individual that I am, I logged every metric on the team sheets over several seasons and where that team ended up in the bracket.

After a LOT of trial and error in Excel, I believe I’ve found a formula that is fairly predictive of whether given teams will be included in the field, and if so, where they will be seeded. It’s not perfect as you simply can’t use math to predict human behavior with a high level of certainty. However, I feel pretty confident that this system knows what was important to the selection committee in years past when it came time to bracket the teams.


S-Curve — The ranking of teams 1-68 by the NCAA Selection Committee. They rate teams in this fashion before bracketing them. There are numerous bracket rules (e.g., proximity to home; avoiding conference rematches, etc.) that will affect a team’s final seed. But this is the holy grail of how the Committee has previously viewed a team and is the basis for my formula. It’s what I’m attempting to replicate.

At-Large — A team voted in by the NCAA Tournament Selection Committee

Auto-Qualifier — A team that wins an automatic bid from their respective conference.

Team Sheet — A “resume” that includes a host of rankings and criteria used by the Tournament Selection Committee to bracket teams. Namely, the current team sheets include information such as: NET Rankings, Ken Pomeroy rankings, ESPN BPI Rankings, Sagarin Rankings, ESPN Strength of Record Rankings, KPI Rankings, team record, conference record, and quad results.

Predictive Metrics — The Ken Pomeroy, ESPN BPI and Sagarin rankings are considered “predictive metrics.” That is, they “predict,” how good a team will be based on past information. They measure a team’s strength, not their resume. They are based on “efficiency.” They are very similar to how Las Vegas sets game lines. Every possession matters. Margin of victory/defeat is a big consideration.

Resume Metrics — Comparatively ESPN Strength of Record and KPI are only measuring the quality of wins and losses a team has accumulated. They are retrospective. It doesn’t matter if you beat a team by 1 or 100, you get the same credit. Teams that rack up a ton of wins by close margins will have a better resume rating and a predictive rating. Teams that lose a bunch of close games? The opposite.

Blend Metric — The NET is a combination of both resume and predictive components. Margin of victory matters, but so do the results. No one in the public sphere really knows the formula for this, we just know it’s used as both a ranking device, but primarily as a sorting tool for wins and losses in the quad system.

Quad System — The NET “sorts” a team’s opponents into four groups to come up with “Quad Records.” The teams are sorted as follows:

  • Quad 1: Home vs. 1-30 in rankings; neutral vs. 1-50; away vs. 1-75
  • Quad 2: Home vs. 31-75; neutral vs. 51-100; away vs. 76-135
  • Quad 3: Home vs. 76-160; neutral vs. 101-200; away vs. 135-240
  • Quad 4: Home vs. 161-363; neutral vs. 201-363; away vs. 241-363