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 → | 943 (#360) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 987 (#354) | HCA +95 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -12.3 (#481) | HCA +3.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.028 (#585) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.193 (#558) | AdjNet -12.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.200 (#555) | AdjNet -11.8 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.304 (#555) | AdjO 70.5 | AdjD 79.6 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.431 (#425) | AdjO 72.9 | AdjD 76.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.317 (#449) | 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 → | 0.337 (#442) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 854 (#418) | RD 350 | GP 1 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-28 | @ | Sioux Falls | L | 67 - 97 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Bryant Brown | - | 1 | 28.3 | 18.0 | 9.0 | 1.0 | 0.0 | 1.0 | 4.0 | 10.0 | 15.0 | - | - | - | 80.0 | 100.0 | 100.0 | - | 86.2 | 85.0 |
| Luke Lee | - | 1 | 19.1 | 12.0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 8.0 | 8.0 | - | - | - | 50.0 | 50.0 | 0 | - | 75.0 | 75.0 |
| Stephen Coleman, Jr. | - | 1 | 24.6 | 10.0 | 3.0 | 5.0 | 1.0 | 0.0 | 1.0 | 9.0 | 9.0 | 50 | 8.3 | 36.9 | 44.4 | 0.0 | 100.0 | -0.47 | 50.6 | 44.4 |
| Chris Peoples | - | 1 | 19.0 | 9.0 | 2.0 | 1.0 | 0.0 | 0.0 | 2.0 | 6.0 | 4.0 | - | - | - | 50.0 | 33.3 | 66.7 | - | 61.5 | 58.3 |
| Carlos Hines | - | 1 | 14.7 | 3.0 | 0.0 | 3.0 | 1.0 | 0.0 | 1.0 | 5.0 | 1.0 | - | - | - | 20.0 | 33.3 | 0.0 | - | 27.6 | 30.0 |
| Isaiah Poindexter | - | 1 | 9.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 3.0 | -2.0 | - | - | - | 33.3 | 100.0 | 0 | - | 50.0 | 50.0 |
| Ty Griggs | - | 1 | 14.6 | 2.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 5.0 | -2.0 | - | - | - | 20.0 | 0.0 | 0.0 | - | 18.4 | 20.0 |
| Christian Tidlane | - | 1 | 9.7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 1.0 | -3.0 | - | - | - | 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