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 → | 1027 (#180) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1011 (#317) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1122 (#74) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +5.0 (#136) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +2.9 (#323) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.586 (#414) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.435 (#377) | NetEff -1.8 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.849 (#241) | AdjNet +15.0 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.852 (#241) | AdjNet +14.8 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.679 (#252) | AdjO 68.8 | AdjD 60.5 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.611 (#218) | AdjO 60.6 | AdjD 55.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.659 (#253) | 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 → | 0.661 (#251) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1165 (#95) | RD 104 | GP 20 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-08 | @ | Caltech | W | 64 - 50 |
| 2025-11-09 | @ | Pomona-Pitzer | L | 65 - 73 |
| 2025-11-13 | vs | JWU (Providence) | L | 67 - 69 |
| 2025-11-18 | vs | Emmanuel (MA) | L | 56 - 64 |
| 2025-11-22 | @ | Rhode Island Col. | L | 57 - 58 |
| 2025-11-25 | @ | Nichols | W | 62 - 41 |
| 2025-12-01 | @ | Endicott | W | 70 - 54 |
| 2025-12-03 | @ | Tufts | L | 63 - 79 |
| 2025-12-10 | @ | Smith | L | 45 - 78 |
| 2025-12-13 | vs | Brandeis | L | 59 - 67 |
| 2026-01-17 | @ | Clark (MA) | L | 61 - 62 |
| 2026-01-21 | @ | WPI | W | 53 - 51 |
| 2026-01-24 | vs | Babson | L | 48 - 63 |
| 2026-01-27 | vs | Middlebury | W | 60 - 48 |
| 2026-01-28 | @ | Emerson | W | 69 - 58 |
| 2026-01-31 | @ | Salve Regina | W | 66 - 54 |
| 2026-02-04 | vs | Wellesley | W | 59 - 49 |
| 2026-02-07 | vs | Mount Holyoke | W | 62 - 51 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Ruth Lanouette | - | 18 | 32.9 | 12.1 | 3.4 | 2.2 | 2.8 | 0.3 | 3.4 | 11.7 | 5.7 | 88 | 4.2 | 13.2 | 35.5 | 20.3 | 72.0 | 2.98 | 44.5 | 38.6 |
| Riley O'Sullivan | - | 18 | 27.2 | 10.1 | 6.5 | 0.9 | 0.9 | 0.6 | 2.2 | 8.1 | 8.7 | 10 | 0.5 | 1.9 | 55.5 | 35.7 | 62.5 | 2.11 | 58.1 | 57.2 |
| Deana Prasad | - | 8 | 27.6 | 8.9 | 3.0 | 1.2 | 1.1 | 0.2 | 1.6 | 7.9 | 5.0 | 14 | 1.8 | 3.5 | 36.5 | 44.4 | 70.8 | -0.38 | 48.3 | 42.9 |
| Mary Lobon | - | 18 | 26.5 | 8.7 | 8.8 | 2.7 | 1.1 | 0.9 | 3.9 | 7.2 | 11.1 | 60 | 2.9 | 11.3 | 43.4 | 14.3 | 74.6 | 1.77 | 50.7 | 43.8 |
| April Chan | - | 10 | 33.9 | 7.6 | 5.5 | 4.1 | 1.6 | 0.3 | 3.7 | 8.9 | 6.5 | 29 | 2.2 | 14.4 | 29.2 | 15.0 | 67.7 | -1.34 | 37.0 | 30.9 |
| Olivia Joseph | - | 18 | 25.1 | 6.8 | 3.4 | 1.0 | 1.1 | 0.7 | 1.2 | 6.7 | 5.2 | 29 | 1.4 | 6.8 | 35.0 | 30.8 | 71.9 | 0.52 | 45.9 | 41.7 |
| Brianna Lebrun | - | 18 | 14.4 | 5.6 | 4.1 | 0.4 | 0.4 | 0.7 | 1.1 | 5.6 | 4.4 | 9 | 0.5 | 3.0 | 42.6 | 0 | 44.1 | 1.05 | 43.5 | 42.6 |
| Mariam Abdelbarr | - | 18 | 17.4 | 3.8 | 3.2 | 1.1 | 1.1 | 0.1 | 2.2 | 5.6 | 1.6 | -60 | -3.0 | -18.5 | 28.0 | 24.1 | 37.5 | -1.21 | 32.2 | 31.5 |
| Rachael Zacks | - | 17 | 13.6 | 2.7 | 1.9 | 0.9 | 0.6 | 0.2 | 0.8 | 3.1 | 2.5 | 5 | 0.3 | 2.1 | 25.0 | 29.4 | 62.5 | 2.24 | 39.0 | 34.6 |
| Kaitlin Tam | - | 15 | 10.1 | 2.2 | 1.1 | 0.5 | 0.3 | 0.1 | 1.4 | 3.1 | -0.3 | -4 | -0.3 | -3.1 | 25.5 | 30.8 | 50.0 | -4.5 | 34.5 | 34.0 |
| Monagoz Okorie | - | 9 | 4.8 | 0.6 | 1.2 | 0.0 | 0.2 | 0.1 | 0.4 | 0.4 | 1.2 | -19 | -2.4 | -107.3 | 50.0 | 0 | 20.0 | -0.88 | 40.3 | 50.0 |
| Francesca Garfi | - | 11 | 2.6 | 0.5 | 0.5 | 0.0 | 0.0 | 0.0 | 0.5 | 0.5 | 0.2 | -16 | -1.3 | -75.6 | 60.0 | 0 | 0 | -1.75 | 60.0 | 60.0 |
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