Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1031 (#239) | HCA +56 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -13.2 (#583) | HCA +3.0 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.056 (#760) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.057 (#688) | AdjNet -24.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.056 (#686) | AdjNet -24.2 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.170 (#680) | AdjO 66.6 | AdjD 84.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.468 (#483) | AdjO 74.4 | AdjD 75.8 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.415 (#470) | 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 → | 0.425 (#466) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1022 (#337) | RD 247 | GP 1 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2026-01-23 | vs | Penn St.-Berks | W | 89 - 73 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Zhaad White | - | 1 | 32.0 | 27.0 | 3.0 | 2.0 | 0.0 | 5.0 | 1.0 | 15.0 | 21.0 | - | - | - | 66.7 | 0.0 | 100.0 | - | 74.7 | 66.7 |
| Marquise McClean | - | 1 | 29.0 | 18.0 | 2.0 | 8.0 | 0.0 | 0.0 | 2.0 | 13.0 | 13.0 | - | - | - | 53.8 | 50.0 | 100.0 | - | 64.8 | 61.5 |
| Quentin Wells | - | 1 | 26.0 | 11.0 | 4.0 | 2.0 | 0.0 | 0.0 | 2.0 | 9.0 | 6.0 | - | - | - | 44.4 | 0.0 | 100.0 | - | 53.3 | 44.4 |
| James Barlow | - | 1 | 32.0 | 9.0 | 11.0 | 8.0 | 0.0 | 1.0 | 0.0 | 5.0 | 24.0 | - | - | - | 80.0 | 0 | 25.0 | - | 66.6 | 80.0 |
| Vincent Fonticoba | - | 1 | 20.0 | 9.0 | 2.0 | 2.0 | 0.0 | 0.0 | 0.0 | 8.0 | 5.0 | - | - | - | 50.0 | 33.3 | 0 | - | 56.2 | 56.2 |
| Charles Warren | - | 1 | 9.0 | 5.0 | 2.0 | 2.0 | 0.0 | 0.0 | 0.0 | 7.0 | 2.0 | -49 | -2.3 | -26.5 | 14.3 | 0 | 100.0 | -3.1 | 30.0 | 14.3 |
| Mikko Persia | - | 1 | 10.0 | 3.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 3.0 | - | - | - | 0.0 | 0 | 75.0 | - | 39.9 | 0.0 |
| Logan Kottinger | - | 1 | 2.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | - | - | - | 100.0 | 0 | 0 | - | 100.0 | 100.0 |
| Kamrin Carroll | - | 1 | 8.0 | 0.0 | 1.0 | 2.0 | 0.0 | 0.0 | 0.0 | 1.0 | 2.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Matt Mondoro | - | 1 | 6.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | - | - | - | 0.0 | 0 | 0 | - | 0.0 | 0.0 |
| Lui Abdeta | - | 1 | 7.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | -1.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
| Sky Thomas | - | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 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