Rochester (NY)
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → | 1067 (#111) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1152 (#86) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 992 (#482) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +14.9 (#60) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +16.1 (#147) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.586 (#415) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.683 (#284) | NetEff +5.7 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.916 (#199) | AdjNet +20.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.919 (#198) | AdjNet +20.6 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.759 (#198) | AdjO 71.6 | AdjD 59.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.744 (#89) | AdjO 64.8 | AdjD 53.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.770 (#151) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. More → | 0.764 (#151) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1068 (#233) | RD 105 | GP 20 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-07 | @ | Cortland | L | 48 - 53 |
| 2025-11-14 | vs | SUNY Geneseo | L | 58 - 66 |
| 2025-11-15 | vs | Middlebury | L | 62 - 67 |
| 2025-11-21 | @ | St. John Fisher | W | 67 - 43 |
| 2025-11-22 | vs | Nazareth | W | 74 - 58 |
| 2025-11-25 | vs | William Smith | W | 83 - 52 |
| 2025-12-02 | @ | Ithaca | W | 80 - 70 |
| 2026-01-10 | vs | Emory | L | 59 - 65 |
| 2026-01-16 | @ | NYU | L | 54 - 75 |
| 2026-01-18 | @ | Brandeis | W | 67 - 64 |
| 2026-01-23 | vs | Carnegie Mellon | L | 52 - 57 |
| 2026-01-25 | vs | CWRU | W | 75 - 70 |
| 2026-01-30 | @ | UChicago | L | 53 - 60 |
| 2026-02-01 | @ | WashU | L | 55 - 62 |
| 2026-02-06 | vs | UChicago | L | 54 - 61 |
| 2026-02-08 | vs | WashU | L | 21 - 33 |
2026 Roster
Minutes by Position
The surface stays filled across the five on-court roles. Use the labels or legend to isolate how each player absorbs guard-to-big minutes.
| Player | Pos | GP | MIN | PTS | REB | AST | STL | BLK | TO | FGA | Numbers | PM | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Grace Corelli | - | 16 | 26.8 | 10.1 | 5.1 | 1.4 | 0.6 | 0.3 | 2.3 | 9.7 | 5.6 | -6 | -0.4 | -1.7 | 35.5 | 26.5 | 73.2 | -1.01 | 46.8 | 42.6 |
| Annelise Dexter | - | 16 | 19.8 | 7.4 | 3.7 | 0.6 | 0.7 | 0.9 | 1.0 | 7.2 | 5.1 | -33 | -2.1 | -10.3 | 37.4 | 19.2 | 87.5 | -0.98 | 46.1 | 39.6 |
| Tia Poulakidas | - | 16 | 19.6 | 7.1 | 4.1 | 1.0 | 0.8 | 0.6 | 1.2 | 6.9 | 5.2 | -17 | -1.2 | -5.8 | 38.7 | 29.4 | 68.8 | -0.69 | 45.2 | 41.0 |
| Bridget Miller | - | 14 | 18.8 | 6.8 | 4.1 | 1.0 | 1.2 | 0.8 | 1.8 | 6.7 | 5.4 | 32 | 2.3 | 16.4 | 40.4 | 19.2 | 48.3 | 3.55 | 44.5 | 43.1 |
| Franki Gomez | - | 15 | 24.5 | 6.7 | 3.7 | 2.2 | 0.5 | 0.3 | 3.0 | 6.2 | 4.3 | -19 | -1.2 | -5.5 | 39.8 | 30.3 | 77.3 | -0.02 | 49.2 | 45.2 |
| Claire Groenewoud | - | 16 | 24.3 | 6.5 | 2.7 | 2.9 | 1.1 | 0.1 | 1.4 | 6.8 | 5.2 | -38 | -2.4 | -9.7 | 34.3 | 28.3 | 73.9 | 0.07 | 44.0 | 40.3 |
| Deniz Alparslan | - | 16 | 17.4 | 5.1 | 3.9 | 1.5 | 1.8 | 0.3 | 1.1 | 4.7 | 6.8 | 25 | 1.6 | 10.9 | 45.3 | 33.3 | 61.1 | 1.78 | 48.8 | 46.7 |
| Hazell Nickerson | - | 16 | 16.2 | 4.6 | 2.8 | 0.9 | 0.6 | 0.6 | 1.1 | 4.0 | 4.4 | -39 | -2.4 | -15.7 | 45.3 | 38.5 | 64.7 | -3.38 | 51.8 | 49.2 |
| Macy Bacon | - | 15 | 9.2 | 3.8 | 1.5 | 0.2 | 0.1 | 0.1 | 0.9 | 2.8 | 2.1 | 17 | 1.1 | 11.4 | 50.0 | 42.1 | 63.6 | 4.82 | 60.8 | 59.5 |
| Melis Alparslan | - | 15 | 16.5 | 3.3 | 2.2 | 1.5 | 0.9 | 0.5 | 1.1 | 4.5 | 2.9 | -11 | -0.7 | -4.1 | 29.9 | 16.7 | 66.7 | 3.4 | 35.2 | 33.6 |
| Peyton Jones | - | 15 | 4.5 | 1.8 | 0.8 | 0.4 | 0.0 | 0.1 | 0.4 | 1.1 | 1.6 | -17 | -1.2 | -84.8 | 58.8 | 100.0 | 100.0 | 0.67 | 72.0 | 67.6 |
| Ava Sandroni | - | 7 | 6.3 | 0.6 | 0.3 | 0.4 | 0.1 | 0.1 | 1.0 | 1.0 | -0.4 | - | - | - | 28.6 | 0.0 | 0 | - | 28.6 | 28.6 |
| Allison Dauer | - | 6 | 2.6 | 0.5 | 0.3 | 0.2 | 0.2 | 0.0 | 0.7 | 1.0 | -0.5 | - | - | - | 16.7 | 0.0 | 50.0 | - | 21.8 | 16.7 |
| Zoey Seymour | - | 12 | 4.2 | 0.3 | 1.7 | 0.2 | 0.2 | 0.0 | 0.2 | 0.9 | 1.2 | 25 | 2.8 | 80.6 | 18.2 | 0.0 | 0 | 1.51 | 18.2 | 18.2 |
| Juliet Schwartz | - | 5 | 3.2 | 0.2 | 0.6 | 0.0 | 0.2 | 0.0 | 0.6 | 0.8 | -0.4 | - | - | - | 0.0 | 0.0 | 50.0 | - | 10.2 | 0.0 |
| Alex Sullivan | - | 1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Numbers/Game vs RAPM
X-axis = Numbers/Game (PTS+REB+AST+STL+BLK-TO-FGA), Y-axis = RAPM.
Advanced: Numbers = PTS+REB+AST+STL+BLK-TO-FGA, PM = total +/-, PM/G = per game, PM/40 = per 40 minutes, RAPM = Regularized Adj Plus-Minus, TS% = True Shooting, eFG% = Effective FG