Sam Houston
Also known as: Sam Houston
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 → | 1036 (#271) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1006 (#396) | HCA +62 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +47.4 (#32) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 1.000 (#103) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.998 (#70) | AdjNet +52.9 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.998 (#68) | AdjNet +52.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.966 (#62) | AdjO 85.7 | AdjD 48.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.916 (#13) | AdjO 83.6 | AdjD 57.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.943 (#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 → | 0.932 (#33) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1045 (#261) | RD 279 | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Fanta Kone | - | 1 | 26.0 | 22.0 | 8.0 | 8.0 | 5.0 | 0.0 | 1.0 | 12.0 | 30.0 | - | - | - | 75.0 | 100.0 | 50.0 | - | 85.4 | 87.5 |
| Blessing Okoh | - | 1 | 14.0 | 14.0 | 7.0 | 0.0 | 1.0 | 0.0 | 0.0 | 7.0 | 15.0 | - | - | - | 57.1 | 0.0 | 100.0 | - | 72.6 | 57.1 |
| Whitney Dunn | - | 1 | 18.3 | 14.0 | 1.0 | 4.0 | 2.0 | 0.0 | 2.0 | 9.0 | 10.0 | - | - | - | 66.7 | 33.3 | 50.0 | - | 70.9 | 72.2 |
| Kaylie Carr | - | 1 | 21.3 | 13.0 | 5.0 | 2.0 | 2.0 | 1.0 | 3.0 | 11.0 | 9.0 | - | - | - | 54.5 | 33.3 | 0 | - | 59.1 | 59.1 |
| Bryana Block | - | 1 | 17.0 | 11.0 | 3.0 | 4.0 | 2.0 | 0.0 | 3.0 | 9.0 | 8.0 | - | - | - | 44.4 | 50.0 | 0 | - | 61.1 | 61.1 |
| Deborah Ogayemi | - | 1 | 19.2 | 9.0 | 6.0 | 1.0 | 1.0 | 0.0 | 0.0 | 6.0 | 11.0 | - | - | - | 50.0 | 0 | 60.0 | - | 54.9 | 50.0 |
| Alaisha Brown | - | 1 | 14.3 | 8.0 | 4.0 | 0.0 | 1.0 | 0.0 | 1.0 | 4.0 | 8.0 | 14 | 1.4 | 37.3 | 50.0 | 0 | 100.0 | -0.51 | 69.4 | 50.0 |
| Aysia Ward-Strong | - | 1 | 24.1 | 8.0 | 9.0 | 6.0 | 8.0 | 0.0 | 1.0 | 7.0 | 23.0 | - | - | - | 57.1 | 0.0 | 0.0 | - | 50.8 | 57.1 |
| Nyla Inmon | - | 1 | 16.4 | 5.0 | 3.0 | 3.0 | 1.0 | 0.0 | 1.0 | 4.0 | 7.0 | - | - | - | 50.0 | 0 | 50.0 | - | 51.2 | 50.0 |
| Esther Rodellar | - | 1 | 12.8 | 4.0 | 3.0 | 0.0 | 4.0 | 0.0 | 1.0 | 6.0 | 4.0 | - | - | - | 16.7 | 0.0 | 100.0 | - | 29.1 | 16.7 |
| Lea Salinas Beamen | - | 1 | 16.5 | 2.0 | 1.0 | 1.0 | 0.0 | 2.0 | 2.0 | 3.0 | 1.0 | - | - | - | 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