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 → | 961 (#310) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 994 (#317) | HCA +95 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -4.2 (#388) | HCA +3.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.032 (#575) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.310 (#496) | AdjNet -6.9 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.316 (#497) | AdjNet -6.6 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.385 (#498) | AdjO 74.5 | AdjD 79.6 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.462 (#377) | AdjO 73.8 | AdjD 75.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.394 (#403) | 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 → | 0.404 (#398) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 908 (#345) | RD 347 | GP 1 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-30 | @ | Augustana (SD) | L | 63 - 90 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Nigel Wilson | - | 1 | 30.2 | 16.0 | 6.0 | 1.0 | 2.0 | 0.0 | 4.0 | 15.0 | 6.0 | - | - | - | 33.3 | 27.3 | 100.0 | - | 49.0 | 43.3 |
| Matt Mathok | - | 1 | 14.5 | 10.0 | 2.0 | 0.0 | 1.0 | 2.0 | 3.0 | 4.0 | 8.0 | - | - | - | 100.0 | 0 | 50.0 | - | 86.8 | 100.0 |
| Christian Carter | - | 1 | 14.2 | 8.0 | 2.0 | 0.0 | 0.0 | 0.0 | 3.0 | 11.0 | -4.0 | - | - | - | 27.3 | 28.6 | 0.0 | - | 35.0 | 36.4 |
| RJ Smith | - | 1 | 22.5 | 8.0 | 5.0 | 0.0 | 0.0 | 0.0 | 1.0 | 5.0 | 7.0 | 14 | 1.3 | 9.5 | 60.0 | 0 | 100.0 | 2.81 | 68.0 | 60.0 |
| JJ Montgomery | - | 1 | 6.8 | 3.0 | 2.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 5.0 | - | - | - | 100.0 | 100.0 | 0 | - | 150.0 | 150.0 |
| Connor Mohr | - | 1 | 20.1 | 3.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 6.0 | -2.0 | - | - | - | 16.7 | 16.7 | 0 | - | 25.0 | 25.0 |
| Deng Jal | - | 1 | 10.0 | 2.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 3.0 | 0.0 | - | - | - | 33.3 | 0.0 | 0 | - | 33.3 | 33.3 |
| Willie Williams | - | 1 | 2.1 | 2.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 3.0 | -103 | -4.9 | -19.9 | 100.0 | 0 | 0 | 1.4 | 100.0 | 100.0 |
| Liam Thompson | - | 1 | 22.5 | 2.0 | 6.0 | 0.0 | 0.0 | 0.0 | 1.0 | 5.0 | 2.0 | - | - | - | 20.0 | 0.0 | 0 | - | 20.0 | 20.0 |
| TJ Fritz | - | 1 | 29.7 | 0.0 | 3.0 | 2.0 | 1.0 | 0.0 | 0.0 | 5.0 | 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