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 → | 904 (#402) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 751 (#555) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 724 (#721) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -24.2 (#378) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -25.5 (#649) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.011 (#707) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.062 (#510) | NetEff -16.9 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.003 (#701) | AdjNet -50.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.002 (#697) | AdjNet -50.4 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.064 (#687) | AdjO 42.1 | AdjD 71.6 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.133 (#693) | AdjO 42.5 | AdjD 63.1 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.062 (#688) | 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 → | 0.063 (#693) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 626 (#565) | RD 110 | GP 22 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-08 | @ | Russell Sage | L | 44 - 61 |
| 2025-11-14 | vs | Alfred | L | 35 - 58 |
| 2025-11-15 | @ | Alfred St. | L | 45 - 59 |
| 2025-11-17 | @ | New Haven | L | 28 - 87 |
| 2025-11-19 | vs | Elms | W | 58 - 48 |
| 2025-11-24 | vs | MCLA | W | 88 - 38 |
| 2025-12-01 | vs | Sarah Lawrence | L | 64 - 73 |
| 2025-12-13 | vs | Rensselaer | L | 30 - 52 |
| 2026-01-10 | vs | Clarkson | L | 45 - 54 |
| 2026-01-13 | vs | Mount Holyoke | L | 51 - 60 |
| 2026-01-16 | @ | Union (NY) | L | 50 - 81 |
| 2026-01-17 | @ | Ithaca | L | 45 - 71 |
| 2026-01-23 | @ | Skidmore | L | 29 - 54 |
| 2026-01-24 | @ | Vassar | L | 34 - 51 |
| 2026-01-30 | @ | Clarkson | L | 42 - 53 |
| 2026-01-31 | @ | St. Lawrence | L | 39 - 71 |
| 2026-02-06 | vs | Vassar | L | 41 - 63 |
| 2026-02-07 | vs | Skidmore | L | 31 - 67 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Shirley Dong | - | 18 | 28.8 | 8.6 | 4.9 | 2.1 | 1.9 | 0.2 | 3.9 | 9.8 | 3.9 | -71 | -3.5 | -16.5 | 33.9 | 26.7 | 83.3 | -0.19 | 42.2 | 40.7 |
| Erin Tobes | - | 18 | 25.3 | 7.5 | 5.4 | 2.6 | 1.9 | 0.3 | 5.9 | 8.1 | 3.7 | -155 | -7.8 | -35.9 | 28.3 | 14.3 | 67.6 | -3.31 | 38.0 | 29.3 |
| Lexi Miller | - | 18 | 33.1 | 6.5 | 10.1 | 1.1 | 1.2 | 0.4 | 3.4 | 8.8 | 7.0 | -188 | -9.4 | -32.7 | 32.1 | 12.5 | 38.9 | -4.0 | 33.5 | 32.4 |
| Morgan Kottka | - | 14 | 26.3 | 6.4 | 4.3 | 1.5 | 0.9 | 0.3 | 2.4 | 8.4 | 2.6 | -50 | -3.1 | -28.0 | 29.1 | 24.2 | 46.7 | 1.83 | 36.4 | 35.5 |
| Aislynn Dixon | - | 17 | 31.5 | 5.4 | 2.8 | 1.8 | 1.5 | 0.5 | 2.5 | 7.0 | 2.4 | -246 | -12.9 | -44.8 | 21.8 | 20.7 | 74.1 | -6.12 | 34.8 | 29.8 |
| Ava Gregory | - | 18 | 30.3 | 5.3 | 4.8 | 1.1 | 1.4 | 0.2 | 3.1 | 7.2 | 2.4 | -116 | -6.1 | -29.0 | 25.4 | 21.4 | 55.0 | -0.29 | 34.2 | 32.3 |
| Jessica Martin | - | 18 | 24.0 | 4.6 | 2.4 | 0.6 | 0.5 | 0.1 | 0.9 | 6.2 | 1.1 | -113 | -5.7 | -24.2 | 26.8 | 24.7 | 100.0 | -0.86 | 36.6 | 35.7 |
| Tianna Gonzalez | - | 10 | 14.3 | 3.4 | 4.5 | 0.5 | 0.8 | 0.1 | 2.7 | 4.1 | 2.5 | -27 | -2.2 | -54.8 | 34.1 | 22.2 | 36.4 | -0.06 | 37.1 | 36.6 |
| Melina Koulouri | - | 1 | 1.9 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | - | - | - | 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