Colby
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 (#129) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1165 (#94) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1061 (#153) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +8.3 (#128) | HCA +2.4 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +7.7 (#235) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.746 (#332) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.881 (#179) | NetEff +14.3 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.905 (#208) | AdjNet +19.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.907 (#207) | AdjNet +19.3 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.733 (#216) | AdjO 67.2 | AdjD 56.1 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.724 (#104) | AdjO 61.6 | AdjD 51.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.736 (#176) | 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 → | 0.734 (#177) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1131 (#119) | RD 95 | GP 21 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-15 | vs | Dean | - | Incomplete score |
| 2025-11-16 | vs | Wellesley | - | Incomplete score |
| 2025-11-20 | vs | Rivier | - | Incomplete score |
| 2025-11-22 | @ | Rutgers-Camden | - | Incomplete score |
| 2025-11-25 | @ | Brooklyn | - | Incomplete score |
| 2025-12-02 | vs | Bates | - | Incomplete score |
| 2025-12-30 | @ | Albertus Magnus | - | Incomplete score |
| 2026-01-10 | @ | Tufts | - | Incomplete score |
| 2026-01-14 | @ | Husson | - | Incomplete score |
| 2026-01-18 | @ | Bates | - | Incomplete score |
| 2026-01-20 | @ | Maine Maritime | - | Incomplete score |
| 2026-01-24 | vs | Bowdoin | - | Incomplete score |
| 2026-01-30 | vs | Amherst | - | Incomplete score |
| 2026-01-31 | vs | Hamilton | - | Incomplete score |
| 2026-02-03 | @ | Me.-Farmington | - | Incomplete score |
| 2026-02-06 | @ | Williams | - | Incomplete score |
| 2026-02-07 | @ | Middlebury | - | Incomplete score |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Kate Olenik | - | 16 | 32.2 | 17.2 | 5.6 | 2.0 | 1.2 | 0.7 | 1.6 | 13.2 | 11.9 | 10 | 0.7 | 3.6 | 50.0 | 36.6 | 72.5 | 4.43 | 58.7 | 56.1 |
| Amelia Hanscom | - | 17 | 25.4 | 9.8 | 6.4 | 2.4 | 1.1 | 0.2 | 2.3 | 7.2 | 10.5 | -16 | -1.0 | -8.4 | 52.5 | 0.0 | 79.6 | 1.71 | 58.2 | 52.5 |
| Lydia Mordarski | - | 17 | 26.4 | 8.8 | 4.4 | 1.2 | 0.5 | 0.2 | 1.2 | 8.5 | 5.4 | -16 | -1.0 | -6.5 | 32.6 | 31.3 | 68.0 | 0.9 | 44.9 | 39.9 |
| Chelsea Ibenegbu | - | 16 | 23.7 | 5.2 | 1.9 | 1.6 | 1.1 | 0.0 | 1.9 | 4.3 | 3.6 | -22 | -1.4 | -9.9 | 33.3 | 0.0 | 67.3 | -1.07 | 44.5 | 33.3 |
| Caroline Hartley | - | 16 | 12.3 | 4.7 | 2.4 | 0.4 | 0.8 | 0.1 | 1.1 | 4.4 | 2.8 | -6 | -0.4 | -5.2 | 42.9 | 0.0 | 57.7 | 1.09 | 46.0 | 42.9 |
| Emily Ryan | - | 17 | 18.6 | 3.8 | 1.5 | 1.6 | 0.7 | 0.1 | 1.1 | 3.7 | 2.8 | -19 | -1.3 | -22.5 | 39.7 | 21.1 | 71.4 | -1.57 | 46.3 | 42.9 |
| Ava Bryan | - | 8 | 7.0 | 3.5 | 1.4 | 0.2 | 0.4 | 0.2 | 0.9 | 3.0 | 1.9 | 7 | 1.2 | 45.5 | 45.8 | 41.7 | 50.0 | - | 56.3 | 56.2 |
| Ana Von Rumohr | - | 17 | 14.1 | 3.4 | 1.4 | 0.2 | 0.5 | 0.0 | 1.1 | 3.9 | 0.5 | -15 | -1.0 | -15.1 | 31.3 | 20.5 | 57.1 | -0.16 | 39.6 | 37.3 |
| Lauren Cho | - | 14 | 10.9 | 2.9 | 1.2 | 0.9 | 0.6 | 0.1 | 1.1 | 2.6 | 2.0 | -4 | -0.4 | -5.6 | 44.4 | 0.0 | 66.7 | 0.96 | 48.4 | 44.4 |
| Shea Donnelly | - | 12 | 11.6 | 2.8 | 2.4 | 0.2 | 0.9 | 0.2 | 1.0 | 3.7 | 1.8 | 10 | 0.9 | 29.3 | 27.3 | 29.6 | 50.0 | 0.48 | 36.8 | 36.4 |
| Talia Thompson | - | 16 | 20.0 | 2.6 | 3.8 | 0.9 | 0.8 | 0.4 | 0.8 | 1.9 | 5.9 | 33 | 2.4 | 20.2 | 56.7 | 0 | 57.1 | 2.12 | 58.1 | 56.7 |
| Defne Pekinbas | - | 10 | 6.9 | 2.5 | 1.9 | 0.4 | 0.3 | 0.0 | 0.7 | 2.0 | 2.4 | 18 | 2.0 | 164.9 | 50.0 | 0 | 83.3 | 1.38 | 55.2 | 50.0 |
| Brooke Braen | - | 6 | 7.8 | 2.0 | 1.5 | 0.3 | 0.2 | 0.2 | 0.8 | 2.2 | 1.2 | -15 | -2.5 | -241.6 | 15.4 | 0.0 | 100.0 | -3.08 | 36.3 | 15.4 |
| Lili Nagy | - | 10 | 8.9 | 1.4 | 1.6 | 0.9 | 0.4 | 0.0 | 0.7 | 1.8 | 1.8 | 3 | 0.4 | 7.9 | 27.8 | 14.3 | 50.0 | -1.05 | 33.9 | 30.6 |
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