Fisher
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 → | 930 (#364) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 669 (#586) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 820 (#669) | HCA +62 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -106.3 (#436) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -98.0 (#730) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.000 (#758) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.000 (#603) | NetEff -101.0 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.000 (#761) | AdjNet -115.4 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.000 (#761) | AdjNet -120.2 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.002 (#761) | AdjO 20.2 | AdjD 87.3 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.003 (#730) | AdjO 25.9 | AdjD 88.9 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.001 (#730) | 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 → | 0.002 (#730) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 551 (#578) | RD 185 | GP 8 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-08 | @ | Me.-Presque Isle | L | 28 - 76 |
| 2025-11-15 | vs | Me.-Farmington | L | 20 - 111 |
| 2025-11-16 | @ | VTSU Castleton | L | 10 - 100 |
| 2026-01-14 | @ | Clark (MA) | L | 16 - 91 |
| 2026-02-03 | @ | Lesley | L | 23 - 77 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Karen Korentang | - | 2 | 30.7 | 16.0 | 4.5 | 0.0 | 2.5 | 0.0 | 5.0 | 15.0 | 3.0 | - | - | - | 36.7 | 36.4 | 85.7 | - | 48.4 | 43.3 |
| Kenuelys Velazquez | - | 3 | 35.8 | 10.0 | 3.7 | 1.0 | 1.3 | 0.7 | 6.0 | 22.7 | -12.0 | - | - | - | 16.2 | 14.0 | 40.0 | - | 21.4 | 20.6 |
| Mayouri Yath | - | 1 | 25.2 | 3.0 | 0.0 | 0.0 | 2.0 | 0.0 | 6.0 | 5.0 | -6.0 | - | - | - | 20.0 | 0.0 | 50.0 | - | 25.5 | 20.0 |
| Tyler Wilkinson | - | 3 | 34.9 | 2.7 | 2.0 | 0.7 | 0.7 | 0.0 | 5.0 | 9.3 | -8.3 | - | - | - | 14.3 | 0.0 | 0 | - | 14.3 | 14.3 |
| Isabelle Jean | - | 5 | 35.8 | 2.0 | 4.4 | 0.2 | 1.2 | 0.0 | 5.0 | 6.2 | -3.4 | - | - | - | 12.9 | 0.0 | 18.2 | - | 14.0 | 12.9 |
| Aziriah Wilson | - | 2 | 9.7 | 2.0 | 2.0 | 0.0 | 0.0 | 0.5 | 1.0 | 4.0 | -0.5 | 35 | 2.2 | 47.6 | 25.0 | 0 | 0.0 | -0.36 | 21.5 | 25.0 |
| Doha Marbouh | - | 1 | 27.0 | 2.0 | 2.0 | 0.0 | 0.0 | 0.0 | 9.0 | 7.0 | -12.0 | - | - | - | 0.0 | 0.0 | 33.3 | - | 10.4 | 0.0 |
| Christelle Jean | - | 5 | 31.7 | 1.6 | 4.2 | 1.0 | 1.2 | 0.0 | 4.4 | 9.0 | -5.4 | - | - | - | 6.7 | 5.9 | 16.7 | - | 8.4 | 7.8 |
| Angelica Mejia Marinez | - | 2 | 32.6 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.5 | 1.0 | -1.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Xhemile Avdyli | - | 3 | 23.1 | 0.0 | 1.7 | 0.0 | 0.0 | 0.0 | 4.3 | 0.3 | -3.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Melissa Fajardo | - | 2 | 37.9 | 0.0 | 3.5 | 0.0 | 0.0 | 0.0 | 0.5 | 2.5 | 0.5 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
| Kayla Dorn | - | 1 | 17.1 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 1.0 | 3.0 | -1.0 | - | - | - | 0.0 | 0 | 0.0 | - | 0.0 | 0.0 |
| Nada Boumkouk | - | 2 | 18.1 | 0.0 | 5.5 | 0.0 | 0.0 | 0.0 | 2.0 | 2.0 | 1.5 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Karen Koranteng | - | 1 | 26.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 4.0 | -1.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
| Angelica Mejia Marin | - | 1 | 28.0 | 0.0 | 4.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 5.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Numbers/Game vs RAPM
Not enough players with both Numbers/Game and RAPM to plot.
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