Mount Holyoke
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 → | 715 (#579) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 680 (#575) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 803 (#686) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -29.0 (#435) | HCA +2.4 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -20.7 (#613) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.005 (#723) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.059 (#513) | NetEff -15.9 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.000 (#739) | AdjNet -65.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.000 (#737) | AdjNet -67.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.031 (#722) | AdjO 36.8 | AdjD 74.6 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.208 (#663) | AdjO 47.5 | AdjD 62.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.076 (#676) | 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 → | 0.087 (#674) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 688 (#549) | RD 120 | GP 20 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-09 | @ | Sarah Lawrence | - | Incomplete score |
| 2025-11-12 | @ | UMass Boston | - | Incomplete score |
| 2025-11-14 | @ | Plattsburgh St. | - | Incomplete score |
| 2025-11-15 | @ | SUNY Potsdam | - | Incomplete score |
| 2025-11-19 | vs | Fitchburg St. | - | Incomplete score |
| 2025-11-22 | @ | Regis (MA) | - | Incomplete score |
| 2025-11-25 | vs | Lesley | - | Incomplete score |
| 2025-12-03 | vs | New England Col. | - | Incomplete score |
| 2025-12-09 | @ | Elms | - | Incomplete score |
| 2026-01-13 | @ | Bard | - | Incomplete score |
| 2026-01-17 | vs | Wellesley | - | Incomplete score |
| 2026-01-21 | @ | Smith | - | Incomplete score |
| 2026-01-24 | vs | Clark (MA) | - | Incomplete score |
| 2026-01-28 | @ | Wheaton (MA) | - | Incomplete score |
| 2026-01-31 | @ | Babson | - | Incomplete score |
| 2026-02-04 | vs | WPI | - | Incomplete score |
| 2026-02-07 | @ | MIT | - | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Alex Twomey | - | 16 | 34.5 | 10.9 | 6.2 | 2.6 | 2.8 | 0.3 | 3.1 | 12.5 | 7.2 | -95 | -6.3 | -25.2 | 29.5 | 8.5 | 73.9 | 0.45 | 37.8 | 30.8 |
| Taryn White | - | 13 | 24.9 | 8.2 | 6.8 | 0.8 | 1.0 | 0.3 | 2.8 | 8.5 | 5.8 | -27 | -2.5 | -12.6 | 40.9 | 33.3 | 62.5 | -3.55 | 44.0 | 41.4 |
| Sofia Francisco | - | 17 | 28.8 | 8.0 | 9.9 | 0.5 | 0.8 | 2.5 | 3.3 | 7.5 | 11.0 | -87 | -5.8 | -29.0 | 38.6 | 30.8 | 52.6 | -1.92 | 44.7 | 41.7 |
| Ania McMichael | - | 10 | 28.1 | 7.3 | 3.2 | 1.8 | 2.3 | 0.0 | 2.8 | 8.0 | 3.8 | -39 | -3.5 | -16.9 | 28.7 | 24.2 | 59.4 | 1.1 | 38.8 | 33.8 |
| Hannah Goen | - | 17 | 32.9 | 6.2 | 2.3 | 1.9 | 1.8 | 0.2 | 4.3 | 10.8 | -2.6 | -67 | -4.5 | -19.4 | 20.7 | 13.1 | 62.9 | -0.03 | 26.6 | 22.8 |
| Anju Manfred | - | 4 | 14.0 | 6.2 | 5.5 | 1.8 | 1.5 | 0.0 | 3.2 | 7.2 | 4.5 | -15 | -3.8 | -23.1 | 41.4 | 50.0 | 0.0 | -2.5 | 39.5 | 43.1 |
| Melina Peña | - | 2 | 22.5 | 5.5 | 5.0 | 1.0 | 1.0 | 0.5 | 3.0 | 7.5 | 2.5 | - | - | - | 20.0 | 50.0 | 50.0 | - | 29.7 | 23.3 |
| Justine Dessureault | - | 11 | 23.8 | 4.1 | 3.5 | 0.5 | 1.0 | 0.0 | 1.7 | 4.9 | 2.5 | -29 | -2.9 | -17.5 | 29.6 | 20.0 | 40.0 | -0.31 | 34.6 | 32.4 |
| Melina Pena | - | 8 | 19.3 | 2.9 | 2.6 | 0.5 | 0.8 | 0.2 | 3.2 | 4.2 | -0.5 | 3 | 0.5 | 3.9 | 23.5 | 25.0 | 42.9 | 1.87 | 28.6 | 25.0 |
| Erica Yokota | - | 12 | 14.1 | 2.4 | 1.8 | 0.7 | 0.4 | 0.0 | 1.8 | 3.2 | 0.2 | -77 | -5.9 | -48.9 | 25.6 | 21.4 | 50.0 | -3.63 | 32.7 | 29.5 |
| Jane Wu | - | 12 | 10.8 | 1.7 | 1.1 | 0.2 | 0.5 | 0.0 | 0.8 | 2.4 | 0.3 | -40 | -4.4 | -59.4 | 24.1 | 24.0 | 0 | -3.16 | 34.5 | 34.5 |
| Emma Zoubok | - | 14 | 10.3 | 1.6 | 0.7 | 0.4 | 0.1 | 0.0 | 1.0 | 3.6 | -1.7 | -45 | -3.8 | -65.8 | 14.0 | 11.9 | 75.0 | -1.75 | 21.3 | 19.0 |
| Helena Robinson | - | 8 | 11.5 | 1.5 | 1.8 | 0.4 | 0.1 | 0.0 | 0.6 | 2.5 | 0.6 | -62 | -7.8 | -69.3 | 25.0 | 0.0 | 100.0 | -2.54 | 28.7 | 25.0 |
| Ashtyn DiRienzo | - | 13 | 10.5 | 0.7 | 1.5 | 0.5 | 0.5 | 0.0 | 1.2 | 1.6 | 0.3 | -67 | -8.4 | -244.7 | 14.3 | 0.0 | 75.0 | -4.36 | 19.8 | 14.3 |
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