A relative strength
Offensive rebound rate
37.5% · rank 16 of 366 · 28 games
Who crashes the glass, and how does that affect transition defense?
← Program librarySource edition Sep 12, 2026
The program dossier / men’s basketball
Columbia
2025–26 performance, personnel and game context.
A starting point for 2026–27 preparation.
Independent preseason modelNo.217
-4.0 adjusted net
per 100 estimated possessions
16–122025–26 recorded finals
106.5Adjusted offense · 2026–27 baseline
110.5Adjusted defense · lower is better
69.1Model tempo · possessions / 40 min
Publisher lens / exact source team ID
A second read on Columbia.
Checking the attributed publisher rating…
01 / Both ends of the floor
The possession profile.
16–1228 recorded games · 28 paired efficiency samples · pace 67.6Mean opponent adj. net -2.0 · 26 rated opponents
Offense
Effective FG%
54.1%28 games · higher is betterRank 78 / 366 · 79th favorable percentileDefense
Opponent effective FG%
49.5%28 games · lower is betterRank 103 / 366 · 72th favorable percentileOffense
Turnover rate
19.1%28 games · lower is betterRank 331 / 366 · 10th favorable percentileDefense
Turnovers forced
14.9%28 games · higher is betterRank 313 / 366 · 15th favorable percentileOffense
Offensive rebound rate
37.5%28 games · higher is betterRank 16 / 366 · 96th favorable percentileDefense
Opponent offensive rebound rate
25.9%28 games · lower is betterRank 26 / 366 · 93th favorable percentileOffense
Free-throw attempt rate
28.2%28 games · higher is betterRank 339 / 366 · 7th favorable percentileDefense
Opponent free-throw attempt rate
32.8%28 games · lower is betterRank 138 / 366 · 62th favorable percentileShooting and ball-movement detail
| Metric | Observed rate | Games | Definition |
|---|---|---|---|
| Offensive efficiency | 112.4 | 28 | Points per 100 estimated possessions. |
| Defensive efficiency | 105.2 | 28 | Opponent points per 100 estimated possessions. |
| Two-point FG% | 54.6% | 28 | (FGM − 3PM) / (FGA − 3PA). |
| Opponent two-point FG% | 48.8% | 28 | Opponent (FGM − 3PM) / (FGA − 3PA). |
| Three-point FG% | 35.5% | 28 | 3PM / 3PA. |
| Opponent three-point FG% | 33.9% | 28 | Opponent 3PM / 3PA. |
| Three-point attempt share | 37.2% | 28 | 3PA / FGA; a style measure, not a quality grade. |
| Opponent three-point attempt share | 36.3% | 28 | Opponent 3PA / FGA; a style measure. |
| Free-throw accuracy | 68.8% | 28 | FTM / FTA. |
| Opponent free-throw accuracy | 74.1% | 28 | Opponent FTM / FTA; not attributed to defensive skill. |
| Assisted field-goal share | 55.4% | 28 | Assists / FGM; describes recorded ball movement. |
| Opponent assisted FG share | 58.2% | 28 | Opponent assists / FGM. |
Window changes describe the historical sample; they do not refit the preseason model. Full-season ranks require 10 games. Percentiles compare qualifying programs in the model’s rated field. Source coverage can differ by metric.
NCAA source context / 2025–26
What did the possessions look like?
1,931 source possession rows across 28 recorded team-games. These are descriptive NCAA source aggregates: they do not assign individual credit or enter the forecast.
02 / The film queue
Turn a number into a question.
A relative strength
Opponent offensive rebound rate
25.9% · rank 26 of 366 · 28 games
Which matchups demand an extra box-out assignment?
A closer look
Turnover rate
19.1% · rank 331 of 366 · 28 games
Where do turnovers occur under pressure, and who can relieve that pressure?
A closer look
Free-throw attempt rate
28.2% · rank 339 of 366 · 28 games
Who generates contact, and how do opponents keep them off the line?
These are stat-led film prompts, not verified explanations of a scheme. Lower-ranked factors can still be above average. A five-point-or-closer final occurred 6 times in the selected window; Columbia won 4. That small-sample record is not a clutch-skill estimate.
03 / How the season moved
Read beyond the average.
● Offense● Opponent offenseRaw points / 100 possessions · game order
Mar 7, 2026 · road vs Harvard · L 71–81 · offense 105.4 / defense 120.2
Higher offense and lower opponent offense are better. Opponent strength and venue are not adjusted here. Missing paired boxes create gaps.
Open the game-by-game scouting log · 28 games
| Game / venue | Result | Current opponent rank | Off. eff. | Def. eff. | Pace | eFG% | TO% | ORB% |
|---|---|---|---|---|---|---|---|---|
| HarvardMar 7, 2026 · road | L 71–81 | 175 | 105.4 | 120.2 | 67.4 | 47.1 | 11.9 | 31.8 |
| YaleFeb 28, 2026 · home | L 54–60 | 62 | 89.0 | 98.9 | 60.7 | 39.7 | 23.1 | 37.1 |
| BrownFeb 28, 2026 · home | W 80–62 | 249 | 117.6 | 91.1 | 68.1 | 60.2 | 22.0 | 45.2 |
| DartmouthFeb 21, 2026 · home | L 63–64 | 253 | 93.8 | 95.3 | 67.2 | 43.2 | 14.9 | 31.0 |
| PrincetonFeb 14, 2026 · road | W 75–65 | 184 | 133.2 | 115.5 | 56.3 | 67.3 | 8.9 | 28.6 |
| PennFeb 14, 2026 · road | L 67–76 | 203 | 95.2 | 108.0 | 70.4 | 55.6 | 28.4 | 32.3 |
| CornellFeb 7, 2026 · home | L 67–88 | 122 | 101.9 | 133.9 | 65.7 | 53.7 | 22.8 | 32.4 |
| PrincetonJan 31, 2026 · home | L 68–80 | 184 | 109.6 | 129.0 | 62.0 | 44.9 | 9.7 | 43.5 |
| PennJan 31, 2026 · home | W 72–67 | 203 | 107.4 | 99.9 | 67.0 | 60.7 | 26.9 | 32.1 |
| DartmouthJan 24, 2026 · road | W 79–69 | 253 | 110.6 | 96.6 | 71.4 | 48.4 | 12.6 | 28.2 |
| YaleJan 19, 2026 · road | L 74–91 | 62 | 114.8 | 141.2 | 64.5 | 54.1 | 18.6 | 32.0 |
| BrownJan 17, 2026 · road | L 80–86 | 249 | 109.5 | 117.7 | 64.9 | 50.7 | 17.8 | 40.5 |
| HarvardJan 10, 2026 · home | L 54–79 | 175 | 89.7 | 131.2 | 60.2 | 39.3 | 23.2 | 38.9 |
| CornellJan 5, 2026 · road | W 104–99 | 122 | 125.9 | 119.9 | 82.6 | 63.3 | 19.4 | 31.0 |
| PSU AbingtonDec 31, 2025 · home | W 106–51 | Unrated | 147.4 | 70.9 | 71.9 | 62.5 | 15.3 | 60.5 |
| North FloridaDec 28, 2025 · road | W 90–82 | 321 | 125.3 | 114.1 | 71.8 | 66.4 | 15.3 | 20.0 |
| CaliforniaDec 21, 2025 · road | L 56–74 | 104 | 83.5 | 110.4 | 67.1 | 45.5 | 22.4 | 23.5 |
| Stony BrookDec 10, 2025 · road | L 73–77 | 280 | 92.4 | 97.5 | 70.2 | 42.0 | 22.8 | 40.0 |
| UAlbanyDec 6, 2025 · home | W 93–65 | 303 | 134.9 | 94.3 | 68.9 | 62.1 | 17.4 | 51.7 |
| HofstraDec 4, 2025 · home | W 72–70 | 115 | 109.0 | 106.0 | 66.0 | 51.7 | 18.2 | 31.4 |
| Sarah LawrenceNov 29, 2025 · home | W 92–44 | Unrated | 123.9 | 59.2 | 74.3 | 59.2 | 17.5 | 47.4 |
| FairfieldNov 27, 2025 · road | W 106–77 | 271 | 149.1 | 108.3 | 71.1 | 71.1 | 14.1 | 45.8 |
| LongwoodNov 23, 2025 · home | W 95–70 | 220 | 131.2 | 96.7 | 72.4 | 65.2 | 19.3 | 37.1 |
| LehighNov 21, 2025 · road | W 82–67 | 291 | 119.7 | 97.8 | 68.5 | 58.3 | 21.9 | 50.0 |
| Boston UNov 19, 2025 · home | W 54–49 | 270 | 90.9 | 82.4 | 59.4 | 46.1 | 21.9 | 27.3 |
| UMass LowellNov 14, 2025 · home | W 86–72 | 272 | 123.7 | 103.6 | 69.5 | 54.0 | 24.5 | 60.5 |
| UConnNov 10, 2025 · road | L 62–89 | 10 | 93.0 | 133.6 | 66.6 | 42.0 | 19.5 | 28.9 |
| New HavenNov 7, 2025 · road | W 71–53 | 332 | 108.2 | 80.8 | 65.6 | 63.3 | 24.4 | 30.8 |
04 / The people behind the possessions
Personnel and workload.
2025–26 recorded affiliations, independent of the split selector. This is not a confirmed 2026–27 roster. Inspect roster observations →
| Player | GP | MIN/G | PTS/G | REB/G | AST/G | TS% | Est. usage | Usage games | AST/TO | 3PA |
|---|---|---|---|---|---|---|---|---|---|---|
| Kenny NolandG | 28 | 33.1 | 17.1 | 3.4 | 3.7 | 58.2 | 26.0% | 28 | 1.4928 games | 19228 games |
| Blair ThompsonF | 28 | 31.0 | 11.4 | 4.8 | 1.1 | 60.7 | 16.5% | 28 | 1.3928 games | 11028 games |
| Mason RitterF | 28 | 24.4 | 7.2 | 5.1 | 1.6 | 57.7 | 16.5% | 28 | 0.9228 games | 1428 games |
| Miles FranklinG | 26 | 23.9 | 9.5 | 4.2 | 0.9 | 50.2 | 21.8% | 26 | 0.9226 games | 7026 games |
| Gerard O'KeefeG | 27 | 21.6 | 8.5 | 1.9 | 1.0 | 61.5 | 17.3% | 27 | 1.6527 games | 9927 games |
| Connor IgoeF | 28 | 19.8 | 8.3 | 5.6 | 3.0 | 56.0 | 23.6% | 28 | 1.6228 games | 4428 games |
| Ryan SoulisF | 26 | 20.0 | 5.8 | 4.6 | 1.5 | 52.7 | 16.7% | 26 | 1.1526 games | 2826 games |
| Hampton SandersG | 28 | 15.3 | 4.2 | 2.0 | 2.2 | 53.9 | 16.3% | 28 | 1.9128 games | 4628 games |
Usage is a minutes-based estimate over the stated sample, not a direct measure of on-court possessions. Low-minute estimates are noisy. AST/TO is unavailable when recorded turnovers are zero; missing fields are never filled with zero.
05 / Recruiting evidence
What changed around Columbia?
This panel keeps dated school publications, source-listed roster observations and prior college production in separate evidence lanes. A source record does not establish eligibility, availability or a future role.
17Source-listed players
14Same-program prior records
0Different-program records
100%Prior minutes represented
Role workload watch
Which source-listed role is represented?
Prior minutes are grouped by the source-reported position on the current listing. “Unrepresented” means prior minutes not attached to a same-program listing in this release; it does not establish a departure, transfer, eligibility or expected role.
| Role | Listed | Prior minutes | Returning minutes | Incoming prior minutes | Returning share | Unrepresented |
|---|---|---|---|---|---|---|
| Guard | 9 | 2,646 | 2,646 | — | 100% | — |
| Forward | 8 | 3,004 | 3,004 | — | 100% | — |
| Center | 0 | — | — | — | — | — |
0 listed players have no recognized source position. The workload denominator is the matched prior-production sample (5,650 minutes).
No dated school announcement is in the selected review file for this program. The roster row below is observation-only; absence of a reviewed announcement does not mean the program made no move.
No announced additions are in the reviewed file for this program.
Roster observation
Who is listed in the source release?
17 source-listed players. Prior rates below are attached by exact source ID where available; missing values remain missing.
| Player | Observation | Prior MPG | Prior PPG | Prior TS% |
|---|---|---|---|---|
| Kenny Noland →G | Same programColumbia Lions | 33.1 | 17.1 | 58.2% |
| Blair Thompson →F | Same programColumbia Lions | 31.0 | 11.4 | 60.7% |
| Mason Ritter →F | Same programColumbia Lions | 24.4 | 7.2 | 57.7% |
| Miles Franklin →G | Same programColumbia Lions | 23.9 | 9.5 | 50.2% |
| Gerard O'Keefe →G | Same programColumbia Lions | 21.6 | 8.5 | 61.5% |
| Connor Igoe →F | Same programColumbia Lions | 19.8 | 8.3 | 56.0% |
| Ryan Soulis →F | Same programColumbia Lions | 20.0 | 5.8 | 52.7% |
| Hampton Sanders →G | Same programColumbia Lions | 15.3 | 4.2 | 53.9% |
| Richard Nweke →F | Same programColumbia Lions | 9.1 | 3.0 | 53.6% |
| Zine Eddine Bedri →F | Same programColumbia Lions | 24.4 | 12.8 | 59.2% |
| Leland Coleman →F | Same programColumbia Lions | 5.2 | 1.3 | 34.8% |
| Avery Brown →G | Same programColumbia Lions | 15.0 | 4.3 | 50.4% |
Showing the 12 highest prior-minute records. Open the full roster board for every source-listed player.
Recruiting review edition Sep 8, 2026 · coverage is partial (14 programs reviewed). See the full methodology and coverage map before drawing a roster conclusion.
Look ahead / 2026–27
The next assignments.
Checking the live schedule edition…
Army vs Columbia
68.7Army
79.6Columbia
Columbia win estimate79.5%
Model signalStrong lean
Projected home margin10.9
Projected total148.3
80% home-margin range-5.0 to 26.8
Estimated possessions68.5
Why the model tiltsfour-factor edge
Shot qualityHome 1.9 pts
Columbia attack 51.9% · Army defense 53.6%Army attack 49.0% · Columbia defense 52.5%
Ball securityAway 1.2 pts
Columbia attack 18.5% · Army defense 15.7%Army attack 17.5% · Columbia defense 15.9%
Second chancesHome 2.5 pts
Columbia attack 30.8% · Army defense 29.6%Army attack 27.8% · Columbia defense 29.0%
Free-throw pressureAway 1.6 pts
Columbia attack 31.5% · Army defense 36.2%Army attack 29.4% · Columbia defense 32.5%
Levien Gymnasium
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Brown vs Columbia
69.1Brown
74.2Columbia
Columbia win estimate67.2%
Model signalLean
Projected home margin5.1
Projected total143.3
80% home-margin range-10.8 to 21.0
Estimated possessions68.5
Why the model tiltsfour-factor edge
Shot qualityHome 3.8 pts
Columbia attack 51.9% · Brown defense 50.6%Brown attack 50.1% · Columbia defense 52.5%
Ball securityHome 2.0 pts
Columbia attack 18.5% · Brown defense 17.3%Brown attack 19.1% · Columbia defense 15.9%
Second chancesHome 0.3 pts
Columbia attack 30.8% · Brown defense 29.9%Brown attack 29.6% · Columbia defense 29.0%
Free-throw pressureAway 3.4 pts
Columbia attack 31.5% · Brown defense 35.0%Brown attack 32.4% · Columbia defense 32.5%
Levien Gymnasium
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Columbia vs Penn
73.8Columbia
77.9Penn
Penn win estimate64.8%
Model signalLean
Projected home margin4.1
Projected total151.7
80% home-margin range-11.8 to 20.0
Estimated possessions69.5
Why the model tiltsfour-factor edge
Shot qualityAway 1.6 pts
Penn attack 51.1% · Columbia defense 52.5%Columbia attack 51.9% · Penn defense 51.8%
Ball securityHome 2.0 pts
Penn attack 16.8% · Columbia defense 15.9%Columbia attack 18.5% · Penn defense 15.6%
Second chancesAway 0.3 pts
Penn attack 29.5% · Columbia defense 29.0%Columbia attack 30.8% · Penn defense 30.1%
Free-throw pressureAway 0.3 pts
Penn attack 33.9% · Columbia defense 32.5%Columbia attack 31.5% · Penn defense 29.8%
The Palestra
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Read the evidence correctly.
The top-line adjusted ratings use the full published preseason model. Split statistics below them are unadjusted observations from 2025–26. Opponent ranks are the current model’s ranks, not what was known before each historical game. The “top 50” split is descriptive and does not enter model evaluation.
Rates pool numerators and denominators from games with all fields required for that metric. Missing values remain unavailable; every metric shows its game count. Ranks require at least 10 games and compare programs in the model’s rated field. Ties share rank; percentiles use their average position. High percentiles mean favorable values only for metrics with a defined direction.
Player workloads refer to recorded 2025–26 appearances. Estimated usage divides FGA + 0.475 × FTA + turnovers by minutes-prorated team opportunities in those same games. It assumes team opportunity rates were constant while a player was on court; it is not a lineup or play-by-play measurement. Overtime is included in available minutes. Minutes and usage samples can differ.
Source statistics: SportsDataverse bulk releases, CC BY 4.0. Calculations and model: Silvermine. Definitions draw on publicly documented Four Factors and basketball rate statistics; these are not another publisher’s proprietary ratings. Model notebook →