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 → | 1025 (#277) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1046 (#274) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1016 (#319) | HCA +56 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -13.3 (#584) | HCA +3.0 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.656 (#362) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.272 (#478) | AdjNet -8.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.262 (#480) | AdjNet -8.9 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.357 (#480) | AdjO 73.5 | AdjD 80.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.454 (#501) | AdjO 70.4 | AdjD 72.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.397 (#489) | 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 → | 0.410 (#485) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1073 (#246) | RD 294 | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Jaquris Slaughter | - | 1 | 31.0 | 20.0 | 2.0 | 0.0 | 4.0 | 2.0 | 0.0 | 12.0 | 16.0 | - | - | - | 58.3 | 60.0 | 0 | - | 83.3 | 83.3 |
| Orlando Thomas | - | 1 | 25.0 | 13.0 | 1.0 | 1.0 | 1.0 | 1.0 | 3.0 | 10.0 | 4.0 | - | - | - | 40.0 | 33.3 | 100.0 | - | 59.7 | 55.0 |
| Gabriel Sorensen | - | 1 | 32.0 | 13.0 | 5.0 | 2.0 | 2.0 | 0.0 | 3.0 | 6.0 | 13.0 | - | - | - | 50.0 | 0 | 70.0 | - | 62.5 | 50.0 |
| Zachary O'Callaghan | - | 1 | 15.0 | 8.0 | 8.0 | 1.0 | 0.0 | 1.0 | 0.0 | 8.0 | 10.0 | - | - | - | 50.0 | 0 | 0 | - | 50.0 | 50.0 |
| Khalyl Simmons | - | 1 | 29.0 | 7.0 | 2.0 | 2.0 | 0.0 | 0.0 | 2.0 | 9.0 | 0.0 | - | - | - | 33.3 | 0.0 | 50.0 | - | 35.4 | 33.3 |
| Jovon Rosse | - | 1 | 17.0 | 3.0 | 4.0 | 0.0 | 0.0 | 0.0 | 1.0 | 3.0 | 3.0 | - | - | - | 33.3 | 100.0 | 0 | - | 50.0 | 50.0 |
| Amir Benelbasry | - | 1 | 5.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0.0 | - | 0.0 | 0 |
| Montrell Bell | - | 1 | 16.0 | 0.0 | 4.0 | 2.0 | 1.0 | 0.0 | 2.0 | 1.0 | 4.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
| Montreal McCullough | - | 1 | 5.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 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