Pittsburgh
Season:
2026
Also known as: Pittsburgh
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 → | 985 (#343) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 982 (#509) | HCA +62 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +18.5 (#129) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.260 (#555) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.260 (#426) | NetEff -8.6 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.961 (#159) | AdjNet +27.7 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.965 (#157) | AdjNet +28.7 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.810 (#168) | AdjO 75.1 | AdjD 59.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.579 (#259) | AdjO 62.7 | AdjD 59.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.781 (#143) | 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 → | 0.754 (#160) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 941 (#378) | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Fatima Diakhate | - | 1 | 35.7 | 17.0 | 9.0 | 0.0 | 0.0 | 0.0 | 4.0 | 11.0 | 11.0 | - | - | - | 72.7 | 0 | 50.0 | - | 71.5 | 72.7 |
| Carla Viegas | - | 1 | 27.7 | 16.0 | 3.0 | 1.0 | 1.0 | 0.0 | 1.0 | 12.0 | 8.0 | - | - | - | 50.0 | 50.0 | 0 | - | 66.7 | 66.7 |
| Angel Jones | - | 1 | 26.9 | 15.0 | 3.0 | 3.0 | 1.0 | 0.0 | 0.0 | 12.0 | 10.0 | 38 | 2.2 | 55.2 | 58.3 | 0 | 50.0 | 0.46 | 58.2 | 58.3 |
| Theresa Hagans | - | 1 | 24.7 | 7.0 | 2.0 | 4.0 | 0.0 | 0.0 | 3.0 | 8.0 | 2.0 | - | - | - | 37.5 | 0.0 | 100.0 | - | 41.5 | 37.5 |
| Mikayla Johnson | - | 1 | 20.9 | 5.0 | 3.0 | 0.0 | 0.0 | 0.0 | 3.0 | 8.0 | -3.0 | 11 | 0.8 | 64.5 | 25.0 | 0.0 | 100.0 | 1.33 | 29.6 | 25.0 |
| Lauren Rust | - | 1 | 35.9 | 2.0 | 13.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 15.0 | - | - | - | 0.0 | 0 | 100.0 | - | 53.2 | 0.0 |
| Jayda Queeley | - | 1 | 15.4 | 1.0 | 2.0 | 5.0 | 0.0 | 0.0 | 3.0 | 4.0 | 1.0 | - | - | - | 0.0 | 0.0 | 50.0 | - | 10.2 | 0.0 |
| Megan Hollingsworth | - | 1 | 6.4 | 0.0 | 2.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
| Nylah Wilson | - | 1 | 5.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 2.0 | -3.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
| Amiya Jenkins | - | 1 | 1.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -1.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
Numbers/Game vs RAPM
X-axis = Numbers/Game (PTS+REB+AST+STL+BLK-TO-FGA), Y-axis = RAPM.
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