A relative strength
Effective FG%
59.9% · rank 5 of 366 · 28 games
Which actions create the team's efficient looks, and which personnel can reproduce them?
← Program librarySource edition Sep 12, 2026
The program dossier / men’s basketball
Cornell
2025–26 performance, personnel and game context.
A starting point for 2026–27 preparation.
Independent preseason modelNo.122
+3.7 adjusted net
per 100 estimated possessions
15–132025–26 recorded finals
116.4Adjusted offense · 2026–27 baseline
112.7Adjusted defense · lower is better
71.6Model tempo · possessions / 40 min
Publisher lens / exact source team ID
A second read on Cornell.
Checking the attributed publisher rating…
01 / Both ends of the floor
The possession profile.
15–1328 recorded games · 28 paired efficiency samples · pace 72.1Mean opponent adj. net -0.8 · 26 rated opponents
Offense
Effective FG%
59.9%28 games · higher is betterRank 5 / 366 · 99th favorable percentileDefense
Opponent effective FG%
54.8%28 games · lower is betterRank 339 / 366 · 7th favorable percentileOffense
Turnover rate
16.0%28 games · lower is betterRank 146 / 366 · 60th favorable percentileDefense
Turnovers forced
15.6%28 games · higher is betterRank 262 / 366 · 28th favorable percentileOffense
Offensive rebound rate
31.2%28 games · higher is betterRank 177 / 366 · 52th favorable percentileDefense
Opponent offensive rebound rate
29.5%28 games · lower is betterRank 159 / 366 · 57th favorable percentileOffense
Free-throw attempt rate
29.0%28 games · higher is betterRank 328 / 366 · 10th favorable percentileDefense
Opponent free-throw attempt rate
35.5%28 games · lower is betterRank 217 / 366 · 41th favorable percentileShooting and ball-movement detail
| Metric | Observed rate | Games | Definition |
|---|---|---|---|
| Offensive efficiency | 121.5 | 28 | Points per 100 estimated possessions. |
| Defensive efficiency | 114.6 | 28 | Opponent points per 100 estimated possessions. |
| Two-point FG% | 60.9% | 28 | (FGM − 3PM) / (FGA − 3PA). |
| Opponent two-point FG% | 54.2% | 28 | Opponent (FGM − 3PM) / (FGA − 3PA). |
| Three-point FG% | 39.3% | 28 | 3PM / 3PA. |
| Opponent three-point FG% | 37.2% | 28 | Opponent 3PM / 3PA. |
| Three-point attempt share | 52.6% | 28 | 3PA / FGA; a style measure, not a quality grade. |
| Opponent three-point attempt share | 38.4% | 28 | Opponent 3PA / FGA; a style measure. |
| Free-throw accuracy | 74.2% | 28 | FTM / FTA. |
| Opponent free-throw accuracy | 71.7% | 28 | Opponent FTM / FTA; not attributed to defensive skill. |
| Assisted field-goal share | 68.7% | 28 | Assists / FGM; describes recorded ball movement. |
| Opponent assisted FG share | 56.8% | 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?
2,045 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
Turnover rate
16.0% · rank 146 of 366 · 28 games
Where do turnovers occur under pressure, and who can relieve that pressure?
A closer look
Free-throw attempt rate
29.0% · rank 328 of 366 · 28 games
Who generates contact, and how do opponents keep them off the line?
A closer look
Opponent effective FG%
54.8% · rank 339 of 366 · 28 games
What coverages and lineups account for the shot quality opponents receive?
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 4 times in the selected window; Cornell won 2. 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 14, 2026 · neutral vs Yale · L 76–88 · offense 125.2 / defense 144.9
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% |
|---|---|---|---|---|---|---|---|---|
| YaleMar 14, 2026 · neutral | L 76–88 | 62 | 125.2 | 144.9 | 60.7 | 51.4 | 9.9 | 46.3 |
| DartmouthMar 7, 2026 · road | W 111–90 | 253 | 142.5 | 115.5 | 77.9 | 77.7 | 12.8 | 14.8 |
| BrownFeb 28, 2026 · home | W 86–80 | 249 | 119.1 | 110.7 | 72.2 | 57.3 | 16.6 | 30.0 |
| YaleFeb 27, 2026 · home | W 72–69 | 62 | 112.1 | 107.4 | 64.3 | 61.1 | 18.7 | 27.6 |
| HarvardFeb 21, 2026 · home | L 54–73 | 175 | 89.9 | 121.5 | 60.1 | 39.1 | 13.3 | 26.5 |
| PennFeb 14, 2026 · road | L 76–82 | 203 | 99.7 | 107.6 | 76.2 | 52.4 | 21.0 | 33.3 |
| PrincetonFeb 14, 2026 · road | W 89–65 | 184 | 140.6 | 102.7 | 63.3 | 66.7 | 12.6 | 35.7 |
| ColumbiaFeb 7, 2026 · road | W 88–67 | 217 | 133.9 | 101.9 | 65.7 | 58.9 | 15.2 | 46.2 |
| PennJan 31, 2026 · home | L 81–91 | 203 | 112.3 | 126.1 | 72.1 | 56.5 | 12.5 | 25.0 |
| PrincetonJan 30, 2026 · home | W 87–64 | 184 | 141.5 | 104.1 | 61.5 | 73.6 | 19.5 | 36.4 |
| HarvardJan 24, 2026 · road | W 86–79 | 175 | 131.4 | 120.7 | 65.4 | 63.7 | 16.8 | 29.6 |
| BrownJan 19, 2026 · road | W 89–67 | 249 | 126.1 | 94.9 | 70.6 | 63.8 | 14.2 | 25.0 |
| YaleJan 17, 2026 · road | L 68–102 | 62 | 96.0 | 144.0 | 70.8 | 41.9 | 12.7 | 27.1 |
| DartmouthJan 10, 2026 · home | L 91–102 | 253 | 121.0 | 135.6 | 75.2 | 54.6 | 16.0 | 32.4 |
| ColumbiaJan 5, 2026 · home | L 99–104 | 217 | 119.9 | 125.9 | 82.6 | 54.0 | 14.5 | 35.0 |
| Alfred StJan 2, 2026 · home | W 133–65 | Unrated | 159.3 | 77.8 | 83.5 | 79.5 | 14.4 | 50.0 |
| Michigan StDec 30, 2025 · road | L 97–114 | 13 | 116.6 | 137.1 | 83.2 | 56.4 | 14.4 | 23.1 |
| UAlbanyDec 21, 2025 · road | W 83–75 | 303 | 137.2 | 124.0 | 60.5 | 61.9 | 13.2 | 45.2 |
| SamfordDec 8, 2025 · road | L 90–93 | 147 | 117.5 | 121.4 | 76.6 | 50.7 | 11.7 | 37.0 |
| TowsonDec 4, 2025 · road | L 80–93 | 150 | 116.2 | 135.1 | 68.8 | 58.9 | 17.4 | 24.1 |
| George MasonDec 3, 2025 · road | L 81–99 | 90 | 111.8 | 136.6 | 72.5 | 60.5 | 17.9 | 25.0 |
| BucknellNov 30, 2025 · road | W 101–72 | 310 | 136.8 | 97.5 | 73.8 | 85.5 | 21.7 | 23.5 |
| MisericordiaNov 26, 2025 · home | W 114–70 | Unrated | 136.7 | 83.9 | 83.4 | 68.4 | 19.2 | 41.7 |
| ColgateNov 21, 2025 · home | W 95–94 | 209 | 103.6 | 102.5 | 73.4 | 52.2 | 19.6 | 20.0 |
| ArmyNov 19, 2025 · home | W 86–73 | 340 | 109.8 | 93.2 | 78.4 | 60.3 | 19.1 | 22.2 |
| LafayetteNov 13, 2025 · road | W 97–78 | 319 | 129.0 | 103.7 | 75.2 | 63.4 | 14.6 | 30.6 |
| Illinois StNov 9, 2025 · road | L 65–76 | 112 | 89.6 | 104.8 | 72.5 | 40.0 | 15.2 | 23.3 |
| Kent StateNov 8, 2025 · road | L 102–110 | 133 | 129.0 | 139.1 | 79.1 | 67.5 | 21.5 | 39.4 |
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| Cooper NoardG | 28 | 27.5 | 18.2 | 3.3 | 2.0 | 65.4 | 27.6% | 28 | 1.2728 games | 21328 games |
| Adam HintonG | 28 | 24.6 | 12.5 | 3.1 | 1.9 | 61.2 | 22.8% | 28 | 1.5128 games | 13528 games |
| Jacob BecclesG | 28 | 23.4 | 7.7 | 2.5 | 3.1 | 55.2 | 17.2% | 28 | 2.4428 games | 6128 games |
| Jake FiegenG | 24 | 26.1 | 17.1 | 5.1 | 2.1 | 66.9 | 26.4% | 24 | 1.8224 games | 13324 games |
| Kaspar SeppF | 28 | 18.8 | 4.8 | 5.5 | 2.6 | 54.4 | 15.0% | 28 | 1.9728 games | 2128 games |
| Josh BaldwinG | 26 | 19.0 | 7.4 | 4.1 | 3.2 | 56.4 | 21.6% | 26 | 1.8626 games | 5926 games |
| Anthony NimaniG | 22 | 17.3 | 5.4 | 1.6 | 1.9 | 68.9 | 14.3% | 22 | 1.8622 games | 2522 games |
| DJ NixF | 27 | 12.3 | 3.5 | 1.7 | 1.1 | 54.3 | 15.3% | 27 | 1.5527 games | 5127 games |
| Gioacchino PanziniF | 26 | 10.8 | 3.9 | 2.0 | 0.6 | 75.0 | 14.0% | 26 | 1.0726 games | 2426 games |
| Corbin ZentnerG | 24 | 11.6 | 3.2 | 0.9 | 0.8 | 58.3 | 12.8% | 24 | 3.0024 games | 5724 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 Cornell?
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.
20Source-listed players
17Same-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 | 12 | 4,283 | 4,283 | — | 100% | — |
| Forward | 8 | 1,367 | 1,367 | — | 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?
20 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% |
|---|---|---|---|---|
| Cooper Noard →G | Same programCornell Big Red | 27.5 | 18.2 | 65.4% |
| Adam Hinton →G | Same programCornell Big Red | 24.6 | 12.5 | 61.2% |
| Jacob Beccles →G | Same programCornell Big Red | 23.4 | 7.7 | 55.2% |
| Jake Fiegen →G | Same programCornell Big Red | 26.1 | 17.1 | 66.9% |
| Kaspar Sepp →F | Same programCornell Big Red | 18.8 | 4.8 | 54.4% |
| Josh Baldwin →G | Same programCornell Big Red | 19.0 | 7.4 | 56.4% |
| Anthony Nimani →G | Same programCornell Big Red | 17.3 | 5.4 | 68.9% |
| DJ Nix →F | Same programCornell Big Red | 12.3 | 3.5 | 54.3% |
| Gioacchino Panzini →F | Same programCornell Big Red | 10.8 | 3.9 | 75.0% |
| Corbin Zentner →G | Same programCornell Big Red | 11.6 | 3.2 | 58.3% |
| DaMaryon Fishburn →G | Same programCornell Big Red | 8.6 | 2.5 | 78.8% |
| Mateen Rafiq →G | Same programCornell Big Red | 9.3 | 4.3 | 68.0% |
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…
Cornell vs St Bonaventure
79.6Cornell
83.0St Bonaventure
St Bonaventure win estimate63.1%
Model signalLean
Projected home margin3.4
Projected total162.6
80% home-margin range-12.5 to 19.3
Estimated possessions70.4
Why the model tiltsfour-factor edge
Shot qualityAway 6.9 pts
St Bonaventure attack 51.9% · Cornell defense 53.2%Cornell attack 57.1% · St Bonaventure defense 51.4%
Ball securityAway 1.1 pts
St Bonaventure attack 16.7% · Cornell defense 16.4%Cornell attack 17.0% · St Bonaventure defense 17.7%
Second chancesHome 0.3 pts
St Bonaventure attack 31.0% · Cornell defense 30.3%Cornell attack 29.0% · St Bonaventure defense 28.5%
Free-throw pressureAway 3.4 pts
St Bonaventure attack 32.0% · Cornell defense 35.1%Cornell attack 32.5% · St Bonaventure defense 32.3%
Reilly Center
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Brown vs Cornell
73.3Brown
84.0Cornell
Cornell win estimate79.2%
Model signalStrong lean
Projected home margin10.8
Projected total157.3
80% home-margin range-5.2 to 26.7
Estimated possessions71.0
Why the model tiltsfour-factor edge
Shot qualityHome 9.5 pts
Cornell attack 57.1% · Brown defense 50.6%Brown attack 50.1% · Cornell defense 53.2%
Ball securityHome 3.1 pts
Cornell attack 17.0% · Brown defense 17.3%Brown attack 19.1% · Cornell defense 16.4%
Second chancesAway 0.2 pts
Cornell attack 29.0% · Brown defense 29.9%Brown attack 29.6% · Cornell defense 30.3%
Free-throw pressureHome 0.3 pts
Cornell attack 32.5% · Brown defense 35.0%Brown attack 32.4% · Cornell defense 35.1%
Newman Arena
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Cornell vs Penn
83.7Cornell
82.4Penn
Penn win estimate50.5%
Model signalToss-up
Projected home margin-1.3
Projected total166.1
80% home-margin range-17.2 to 14.6
Estimated possessions72.0
Why the model tiltsfour-factor edge
Shot qualityAway 7.4 pts
Penn attack 51.1% · Cornell defense 53.2%Cornell attack 57.1% · Penn defense 51.8%
Ball securityHome 1.0 pts
Penn attack 16.8% · Cornell defense 16.4%Cornell attack 17.0% · Penn defense 15.6%
Second chancesHome 0.2 pts
Penn attack 29.5% · Cornell defense 30.3%Cornell attack 29.0% · Penn defense 30.1%
Free-throw pressureAway 3.9 pts
Penn attack 33.9% · Cornell defense 35.1%Cornell attack 32.5% · 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 →