Green Bay
Also known as: Green Bay
Program History
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1101 (#136) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1016 (#316) | HCA +62 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +44.2 (#39) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 1.000 (#98) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 1.000 (#41) | NetEff +69.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 1.000 (#8) | AdjNet +74.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 1.000 (#16) | AdjNet +73.8 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.982 (#26) | AdjO 84.3 | AdjD 40.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.696 (#129) | AdjO 65.4 | AdjD 56.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.967 (#17) | 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 → | 0.947 (#24) | Blend of Elo, BT, Margin, PythLog, PtsOD |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-03 | vs | Wis.-Stevens Point | W | 85 - 37 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Meghan Schultz | - | 1 | 24.5 | 20.0 | 9.0 | 1.0 | 1.0 | 0.0 | 1.0 | 12.0 | 18.0 | 70 | 3.2 | 25.2 | 66.7 | 0 | 80.0 | 2.31 | 70.4 | 66.7 |
| Carley Duffney | - | 1 | 19.1 | 12.0 | 4.0 | 0.0 | 1.0 | 1.0 | 3.0 | 9.0 | 6.0 | - | - | - | 66.7 | 0.0 | 0 | - | 66.7 | 66.7 |
| Kristina Ouimette | - | 1 | 25.7 | 10.0 | 4.0 | 3.0 | 0.0 | 1.0 | 0.0 | 7.0 | 11.0 | - | - | - | 42.9 | 60.0 | 50.0 | - | 63.5 | 64.3 |
| Julianna Ouimette | - | 1 | 13.2 | 10.0 | 2.0 | 0.0 | 0.0 | 1.0 | 0.0 | 5.0 | 8.0 | - | - | - | 60.0 | 50.0 | 60.0 | - | 69.4 | 70.0 |
| Ellie Buzzelle | - | 1 | 22.2 | 8.0 | 8.0 | 4.0 | 0.0 | 0.0 | 1.0 | 7.0 | 12.0 | - | - | - | 42.9 | 0.0 | 33.3 | - | 41.5 | 42.9 |
| Kamy Peppler | - | 1 | 20.0 | 8.0 | 0.0 | 7.0 | 2.0 | 0.0 | 1.0 | 6.0 | 10.0 | - | - | - | 50.0 | 33.3 | 50.0 | - | 58.1 | 58.3 |
| Maddy Skorupski | - | 1 | 18.3 | 6.0 | 6.0 | 7.0 | 1.0 | 0.0 | 3.0 | 3.0 | 14.0 | - | - | - | 33.3 | 0.0 | 100.0 | - | 63.0 | 33.3 |
| Gracie Grzesk | - | 1 | 21.6 | 5.0 | 5.0 | 1.0 | 1.0 | 0.0 | 0.0 | 5.0 | 7.0 | - | - | - | 40.0 | 50.0 | 0 | - | 50.0 | 50.0 |
| Lily Hansford | - | 1 | 16.0 | 5.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 3.0 | 4.0 | - | - | - | 66.7 | 50.0 | 0 | - | 83.3 | 83.3 |
| Kallie Peppler | - | 1 | 19.3 | 1.0 | 4.0 | 3.0 | 1.0 | 0.0 | 2.0 | 1.0 | 6.0 | - | - | - | 0.0 | 0 | 50.0 | - | 26.6 | 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