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 → | 1019 (#232) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1030 (#228) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1008 (#324) | HCA +75 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +33.1 (#27) | HCA +3.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 1.000 (#32) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.998 (#21) | AdjNet +54.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.999 (#26) | AdjNet +54.0 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.956 (#31) | AdjO 83.1 | AdjD 49.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.727 (#68) | AdjO 70.8 | AdjD 60.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.897 (#32) | 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 → | 0.876 (#37) | Blend of Elo, BT, Margin, PythLog, PtsOD |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-12-15 | vs | Tex. A&M-Kingsville | W | 82 - 40 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Ereauna Hardaway | - | 1 | 21.7 | 15.0 | 5.0 | 8.0 | 4.0 | 0.0 | 0.0 | 6.0 | 26.0 | - | - | - | 83.3 | 100.0 | 100.0 | - | 109.0 | 108.3 |
| Cheyenne Rowe | - | 1 | 16.7 | 12.0 | 7.0 | 2.0 | 0.0 | 0.0 | 1.0 | 10.0 | 10.0 | - | - | - | 50.0 | 50.0 | 100.0 | - | 57.5 | 55.0 |
| Mia Hammonds | - | 1 | 27.6 | 12.0 | 6.0 | 4.0 | 3.0 | 0.0 | 2.0 | 8.0 | 15.0 | - | - | - | 50.0 | 75.0 | 50.0 | - | 67.6 | 68.8 |
| Damara Allen | - | 1 | 27.2 | 10.0 | 3.0 | 3.0 | 3.0 | 0.0 | 2.0 | 12.0 | 5.0 | - | - | - | 33.3 | 33.3 | 0 | - | 41.7 | 41.7 |
| Jayda Holiman | - | 1 | 28.4 | 9.0 | 0.0 | 4.0 | 4.0 | 1.0 | 0.0 | 11.0 | 7.0 | - | - | - | 36.4 | 16.7 | 0 | - | 40.9 | 40.9 |
| Emilia Dannebauer | - | 1 | 20.9 | 9.0 | 4.0 | 0.0 | 2.0 | 1.0 | 1.0 | 6.0 | 9.0 | - | - | - | 33.3 | 0 | 71.4 | - | 49.6 | 33.3 |
| Adriana Robles | - | 1 | 23.9 | 7.0 | 3.0 | 3.0 | 1.0 | 0.0 | 1.0 | 5.0 | 8.0 | - | - | - | 40.0 | 66.7 | 50.0 | - | 59.5 | 60.0 |
| Idara Udo | - | 1 | 20.1 | 6.0 | 5.0 | 2.0 | 0.0 | 0.0 | 2.0 | 11.0 | 0.0 | - | - | - | 27.3 | 0.0 | 0.0 | - | 26.2 | 27.3 |
| Sanaa Bean | - | 1 | 13.4 | 2.0 | 3.0 | 1.0 | 0.0 | 1.0 | 1.0 | 3.0 | 3.0 | - | - | - | 33.3 | 0 | 0 | - | 33.3 | 33.3 |
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