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 → | 951 (#343) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 985 (#379) | HCA +95 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +4.5 (#253) | HCA +3.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.323 (#430) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.462 (#432) | AdjNet -1.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.469 (#431) | AdjNet -1.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.498 (#423) | AdjO 66.9 | AdjD 67.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.507 (#284) | AdjO 73.3 | AdjD 72.9 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.523 (#297) | 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 → | 0.516 (#301) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 886 (#382) | RD 350 | GP 1 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-26 | @ | Neb.-Kearney | L | 68 - 71 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Tom Connelly | - | 1 | 22.0 | 9.0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 6.0 | 7.0 | -112 | -5.3 | -24.8 | 50.0 | 40.0 | 100.0 | -1.97 | 69.9 | 66.7 |
| Clayton Moore | - | 1 | 13.0 | 5.0 | 3.0 | 1.0 | 1.0 | 0.0 | 0.0 | 2.0 | 8.0 | -113 | -5.4 | -23.4 | 100.0 | 0 | 50.0 | 0.51 | 86.8 | 100.0 |
| Wade Williams | - | 1 | 23.0 | 4.0 | 5.0 | 1.0 | 1.0 | 0.0 | 4.0 | 6.0 | 1.0 | -103 | -4.9 | -19.9 | 16.7 | 0.0 | 100.0 | 1.4 | 29.1 | 16.7 |
| River Johnston | - | 1 | 20.0 | 2.0 | 2.0 | 4.0 | 0.0 | 0.0 | 0.0 | 5.0 | 3.0 | -101 | -6.3 | -70.1 | 20.0 | 0.0 | 0 | -0.64 | 20.0 | 20.0 |
| Zeek Brown | - | 1 | 12.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 3.0 | -81 | -4.5 | -27.3 | 0 | 0 | 0 | -1.72 | 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