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 → | 1001 (#243) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1116 (#116) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1139 (#65) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +8.1 (#107) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +9.5 (#212) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.452 (#473) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.703 (#276) | NetEff +6.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.466 (#391) | AdjNet -1.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.460 (#388) | AdjNet -1.4 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.458 (#395) | AdjO 61.5 | AdjD 63.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.735 (#93) | AdjO 64.4 | AdjD 53.1 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.776 (#148) | 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 → | 0.779 (#139) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1174 (#84) | RD 103 | GP 21 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-08 | @ | Chatham | L | 40 - 64 |
| 2025-11-09 | @ | Allegheny | W | 62 - 60 |
| 2025-11-15 | @ | Stevens | W | 59 - 39 |
| 2025-11-16 | @ | Emmanuel (MA) | W | 61 - 50 |
| 2025-11-22 | @ | SUNY Geneseo | L | 63 - 64 |
| 2025-12-02 | @ | SUNY Brockport | L | 61 - 65 |
| 2026-01-10 | @ | William Smith | W | 68 - 39 |
| 2026-01-13 | @ | Union (NY) | L | 57 - 64 |
| 2026-01-16 | vs | Vassar | W | 62 - 43 |
| 2026-01-17 | vs | Rensselaer | W | 59 - 43 |
| 2026-01-23 | @ | St. Lawrence | W | 62 - 35 |
| 2026-01-24 | @ | Clarkson | W | 68 - 53 |
| 2026-01-30 | vs | William Smith | W | 86 - 67 |
| 2026-01-31 | vs | Ithaca | W | 80 - 55 |
| 2026-02-06 | vs | Clarkson | W | 87 - 54 |
| 2026-02-07 | vs | St. Lawrence | W | 71 - 49 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Maddy Ramsgard | - | 16 | 31.0 | 13.2 | 6.5 | 2.8 | 1.6 | 0.2 | 2.6 | 11.8 | 9.8 | 122 | 6.1 | 24.0 | 50.3 | 44.4 | 86.7 | 4.16 | 53.9 | 52.4 |
| Caroline Henderson | - | 16 | 29.8 | 12.5 | 5.4 | 2.4 | 1.1 | 0.0 | 1.9 | 11.6 | 8.0 | 126 | 6.3 | 27.6 | 38.9 | 37.3 | 64.3 | 2.03 | 52.3 | 51.6 |
| Ben Kayser-Cochran | - | 13 | 21.5 | 9.4 | 3.8 | 0.8 | 0.3 | 0.4 | 1.8 | 9.2 | 3.8 | 88 | 4.9 | 19.4 | 36.1 | 34.2 | 85.2 | 1.86 | 46.6 | 41.6 |
| Faye Kaplinski | - | 16 | 25.7 | 9.0 | 6.8 | 1.0 | 0.8 | 0.4 | 1.1 | 7.4 | 9.4 | 83 | 4.2 | 20.5 | 47.9 | 0.0 | 75.0 | 0.59 | 52.7 | 47.9 |
| Hannah Durand | - | 16 | 17.9 | 6.3 | 1.8 | 1.4 | 0.6 | 0.1 | 1.2 | 4.2 | 4.8 | 45 | 2.2 | 17.2 | 55.2 | 51.4 | 60.0 | 0.49 | 68.6 | 68.7 |
| Erin DiPaola | - | 16 | 26.8 | 5.1 | 3.2 | 3.2 | 1.1 | 0.1 | 1.5 | 3.2 | 8.1 | 105 | 5.2 | 22.8 | 57.7 | 47.6 | 75.0 | 2.09 | 69.4 | 67.3 |
| Sydney Pearson | - | 16 | 13.4 | 3.3 | 2.5 | 0.4 | 0.3 | 0.8 | 0.7 | 4.1 | 2.4 | 6 | 0.3 | 2.5 | 30.3 | 7.1 | 80.0 | 0.51 | 36.5 | 31.1 |
| Ella Wilson | - | 16 | 14.0 | 2.8 | 2.8 | 1.8 | 0.9 | 0.1 | 0.9 | 2.6 | 4.9 | 59 | 3.1 | 23.8 | 31.0 | 28.6 | 83.3 | -0.02 | 45.1 | 35.7 |
| Mia Firdman | - | 14 | 5.4 | 2.4 | 1.3 | 0.0 | 0.1 | 0.0 | 0.2 | 2.0 | 1.5 | -2 | -0.1 | -2.2 | 42.9 | 0.0 | 64.3 | -2.55 | 48.3 | 42.9 |
| Caroline Smith | - | 11 | 7.2 | 1.5 | 0.6 | 0.2 | 0.4 | 0.1 | 0.5 | 1.2 | 1.2 | 14 | 1.2 | 15.0 | 38.5 | 0.0 | 77.8 | -0.68 | 50.1 | 38.5 |
| Hannah Manley | - | 12 | 6.9 | 1.4 | 1.2 | 0.5 | 0.3 | 0.2 | 0.5 | 1.0 | 2.2 | 5 | 0.3 | 3.7 | 41.7 | 33.3 | 75.0 | -1.36 | 54.8 | 45.8 |
| Sophia Spizuoco | - | 14 | 7.9 | 1.4 | 1.3 | 0.6 | 0.3 | 0.0 | 0.4 | 2.0 | 1.1 | 5 | 0.3 | 2.2 | 25.0 | 22.2 | 100.0 | -1.56 | 32.4 | 28.6 |
| Abby Cleary | - | 11 | 3.1 | 0.2 | 0.8 | 0.1 | 0.2 | 0.0 | 0.3 | 0.8 | 0.2 | 5 | 0.4 | 9.6 | 11.1 | 0.0 | 0 | 0.15 | 11.1 | 11.1 |
| Addison Westbook | - | 1 | 1.7 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Sydney Dodds | - | 2 | 1.9 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | 0.0 | -6 | -2.0 | -109.1 | 0.0 | 0.0 | 0 | -0.61 | 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