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 → | 933 (#383) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 964 (#451) | HCA +95 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -15.9 (#507) | HCA +3.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.948 (#104) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.862 (#185) | AdjNet +15.9 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.870 (#178) | AdjNet +16.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.744 (#190) | AdjO 87.5 | AdjD 75.7 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.459 (#381) | AdjO 75.8 | AdjD 77.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.296 (#474) | 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 → | 0.335 (#444) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 901 (#362) | RD 350 | GP 1 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-10 | vs | North Greenville | L | 81 - 92 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Julius Clark | - | 1 | 29.7 | 15.0 | 3.0 | 2.0 | 1.0 | 1.0 | 0.0 | 11.0 | 11.0 | 67 | 3.2 | 13.2 | 45.5 | 25.0 | 100.0 | 1.39 | 58.8 | 50.0 |
| Jacob Hogarth | - | 1 | 19.9 | 15.0 | 5.0 | 1.0 | 1.0 | 1.0 | 2.0 | 9.0 | 12.0 | - | - | - | 66.7 | 0 | 100.0 | - | 72.7 | 66.7 |
| Jacob Hudson | - | 1 | 32.7 | 15.0 | 7.0 | 2.0 | 2.0 | 0.0 | 0.0 | 11.0 | 15.0 | - | - | - | 45.5 | 66.7 | 60.0 | - | 56.8 | 54.5 |
| Colin Hawkins | - | 1 | 24.1 | 11.0 | 1.0 | 2.0 | 1.0 | 0.0 | 1.0 | 6.0 | 8.0 | 0 | 0.0 | 0.0 | 50.0 | 50.0 | 66.7 | -0.12 | 63.7 | 58.3 |
| Spence Sims | - | 1 | 21.3 | 10.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 6.0 | 6.0 | 1 | 0.5 | 15.6 | 50.0 | 50.0 | 100.0 | -0.49 | 72.7 | 66.7 |
| Ace Talbert | - | 1 | 27.3 | 9.0 | 4.0 | 3.0 | 2.0 | 0.0 | 0.0 | 10.0 | 8.0 | - | - | - | 40.0 | 16.7 | 0.0 | - | 43.1 | 45.0 |
| Riek Riek | - | 1 | 15.8 | 4.0 | 2.0 | 1.0 | 0.0 | 0.0 | 1.0 | 5.0 | 1.0 | - | - | - | 40.0 | 0.0 | 0 | - | 40.0 | 40.0 |
| D.J. Jefferson | - | 1 | 5.9 | 2.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 2.0 | 0.0 | - | - | - | 0.0 | 0.0 | 100.0 | - | 34.7 | 0.0 |
| NaVuan Peterson | - | 1 | 12.2 | 0.0 | 2.0 | 2.0 | 1.0 | 0.0 | 0.0 | 2.0 | 3.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
| Curtis Williams | - | 1 | 10.9 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 2.0 | -3.0 | 136 | 6.2 | 40.7 | 0.0 | 0 | 0.0 | 2.43 | 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