Western Mich.
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 → | 963 (#381) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 907 (#428) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 966 (#530) | HCA +75 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -14.5 (#553) | HCA +3.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.522 (#352) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.622 (#343) | AdjNet +4.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.637 (#343) | AdjNet +4.8 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.531 (#379) | AdjO 66.9 | AdjD 65.5 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.373 (#559) | AdjO 63.7 | AdjD 69.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.281 (#537) | 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 → | 0.314 (#518) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 887 (#392) | RD 350 | GP 1 |
2026 Schedule & Results
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Nile Muguira Orbe | - | 1 | 37.6 | 17.0 | 5.0 | 1.0 | 2.0 | 0.0 | 1.0 | 15.0 | 9.0 | - | - | - | 40.0 | 33.3 | 100.0 | - | 53.5 | 50.0 |
| D'Myjah Bolds | - | 1 | 38.5 | 15.0 | 6.0 | 0.0 | 0.0 | 0.0 | 1.0 | 9.0 | 11.0 | - | - | - | 66.7 | 0 | 75.0 | - | 69.7 | 66.7 |
| Kailey Starks | - | 1 | 32.2 | 15.0 | 5.0 | 1.0 | 1.0 | 1.0 | 3.0 | 11.0 | 9.0 | - | - | - | 36.4 | 25.0 | 100.0 | - | 55.0 | 40.9 |
| Alli Carlson | - | 1 | 40.9 | 14.0 | 3.0 | 7.0 | 1.0 | 0.0 | 3.0 | 13.0 | 9.0 | - | - | - | 38.5 | 25.0 | 100.0 | - | 48.9 | 42.3 |
| Ariana Wilkes | - | 1 | 33.3 | 7.0 | 15.0 | 0.0 | 0.0 | 2.0 | 4.0 | 5.0 | 15.0 | - | - | - | 60.0 | 0 | 25.0 | - | 51.8 | 60.0 |
| Emma Dibarboure | - | 1 | 9.6 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 3.0 | -3.0 | - | - | - | 33.3 | 0.0 | 0 | - | 33.3 | 33.3 |
| Olivia Flynn | - | 1 | 6.0 | 0.0 | 0.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 3.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
| Irene Trujillo | - | 1 | 26.9 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 3.0 | 5.0 | -7.0 | - | - | - | 0.0 | 0.0 | 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