Union (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 → | 1098 (#79) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1199 (#50) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1162 (#51) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +10.2 (#92) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +6.9 (#249) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.592 (#409) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.853 (#195) | NetEff +13.0 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.550 (#366) | AdjNet +1.7 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.548 (#364) | AdjNet +1.6 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.495 (#377) | AdjO 61.2 | AdjD 61.5 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.686 (#138) | AdjO 65.2 | AdjD 56.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.763 (#156) | 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 → | 0.761 (#155) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1221 (#57) | RD 105 | GP 21 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-07 | @ | Utica | W | 74 - 44 |
| 2025-11-12 | vs | Russell Sage | W | 64 - 61 |
| 2025-11-22 | vs | Middlebury | W | 82 - 75 |
| 2025-11-24 | vs | Bowdoin | L | 56 - 68 |
| 2025-12-13 | @ | Hamilton | L | 68 - 71 |
| 2025-12-17 | @ | JWU (Providence) | W | 65 - 60 |
| 2026-01-10 | @ | Ithaca | W | 58 - 51 |
| 2026-01-13 | vs | RIT | W | 64 - 57 |
| 2026-01-16 | vs | Bard | W | 81 - 50 |
| 2026-01-17 | vs | Vassar | L | 52 - 54 |
| 2026-01-23 | @ | William Smith | W | 77 - 45 |
| 2026-01-27 | @ | Skidmore | L | 54 - 71 |
| 2026-01-30 | vs | Ithaca | W | 69 - 53 |
| 2026-01-31 | vs | Rensselaer | W | 62 - 41 |
| 2026-02-06 | vs | Skidmore | W | 59 - 54 |
| 2026-02-07 | vs | William Smith | W | 70 - 52 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Jelena Perovic | - | 16 | 31.0 | 14.4 | 8.1 | 2.0 | 1.1 | 1.4 | 2.6 | 13.2 | 11.1 | 62 | 2.8 | 12.2 | 44.8 | 0.0 | 69.0 | 0.12 | 48.4 | 44.8 |
| Kate Peek | - | 16 | 32.9 | 11.2 | 2.8 | 1.2 | 1.4 | 0.3 | 2.1 | 10.2 | 4.5 | 79 | 3.8 | 14.5 | 35.6 | 31.4 | 90.9 | 0.08 | 50.4 | 45.7 |
| Olivia Cunningham | - | 16 | 28.3 | 9.8 | 11.2 | 2.9 | 2.2 | 0.9 | 3.0 | 9.3 | 14.8 | 84 | 3.8 | 17.9 | 40.9 | 0.0 | 66.0 | 1.31 | 45.6 | 40.9 |
| Grace Ardito | - | 16 | 31.3 | 9.3 | 2.6 | 1.6 | 0.7 | 0.1 | 1.1 | 9.3 | 3.9 | 105 | 4.8 | 21.7 | 38.9 | 28.2 | 73.3 | 1.62 | 47.9 | 46.3 |
| Grace Ceseretti | - | 16 | 29.9 | 8.5 | 5.2 | 3.5 | 1.3 | 0.4 | 2.4 | 7.8 | 8.8 | 107 | 4.9 | 20.5 | 35.5 | 31.3 | 79.4 | 2.42 | 48.9 | 44.0 |
| Aiden Gill | - | 2 | 5.9 | 4.5 | 1.5 | 0.0 | 0.0 | 0.0 | 2.0 | 2.0 | 2.0 | -16 | -3.2 | -153.6 | 100.0 | 100.0 | 0 | -0.04 | 112.5 | 112.5 |
| Ryley Tate-Padian | - | 16 | 12.0 | 4.2 | 2.6 | 0.3 | 0.3 | 0.1 | 1.2 | 3.4 | 2.9 | 107 | 5.1 | 62.6 | 45.5 | 26.7 | 63.6 | 4.76 | 52.6 | 49.1 |
| Morgan Schultz | - | 16 | 16.0 | 3.6 | 3.0 | 0.5 | 0.3 | 0.2 | 0.7 | 3.8 | 3.2 | 70 | 3.2 | 25.2 | 40.0 | 0 | 56.2 | 2.31 | 42.5 | 40.0 |
| Ryanne Gulbin | - | 6 | 7.5 | 3.0 | 1.7 | 0.5 | 0.2 | 0.0 | 0.3 | 3.3 | 1.7 | 17 | 1.9 | 26.3 | 30.0 | 30.8 | 100.0 | -1.1 | 43.1 | 40.0 |
| Aiko Bastiaens | - | 10 | 5.0 | 2.2 | 0.8 | 0.2 | 0.2 | 0.2 | 0.2 | 1.5 | 1.9 | 7 | 0.5 | 7.8 | 60.0 | 0 | 80.0 | 1.61 | 64.0 | 60.0 |
| Ally Burke | - | 4 | 5.5 | 2.2 | 1.0 | 0.0 | 0.8 | 0.0 | 0.5 | 1.8 | 1.8 | -2 | -0.5 | -5.1 | 57.1 | 50.0 | 0 | -0.73 | 64.3 | 64.3 |
| Casey Weeren | - | 8 | 6.3 | 1.0 | 1.6 | 0.1 | 0.0 | 0.0 | 0.5 | 1.5 | 0.8 | -9 | -0.8 | -12.7 | 25.0 | 25.0 | 50.0 | -1.38 | 31.1 | 29.2 |
| Allie Grove | - | 5 | 4.7 | 1.0 | 0.8 | 0.0 | 0.0 | 0.0 | 0.6 | 1.0 | 0.2 | -9 | -1.1 | -22.5 | 40.0 | 33.3 | 0.0 | 0.15 | 42.5 | 50.0 |
| Anna O'Keefe | - | 10 | 7.7 | 0.6 | 0.8 | 0.4 | 0.1 | 0.1 | 1.0 | 0.6 | 0.4 | 3 | 0.2 | 2.2 | 33.3 | 25.0 | 25.0 | -0.39 | 38.7 | 41.7 |
| Hazel Hoog | - | 5 | 4.0 | 0.4 | 0.4 | 0.4 | 0.2 | 0.0 | 0.6 | 0.6 | 0.2 | -13 | -1.6 | -34.2 | 33.3 | 0 | 0 | 0.19 | 33.3 | 33.3 |
| Grace Arcoleo | - | 1 | 0.1 | 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