UNT Dallas
Also known as: UNT Dallas
Program History
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 (#359) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 988 (#351) | HCA +95 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +1.7 (#299) | HCA +3.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.355 (#407) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.705 (#295) | AdjNet +7.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.697 (#303) | AdjNet +7.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.619 (#305) | AdjO 76.3 | AdjD 70.9 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.496 (#306) | AdjO 75.2 | AdjD 75.3 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.496 (#318) | 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 → | 0.491 (#321) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 915 (#338) | RD 350 | GP 1 |
2026 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2025-11-24 | @ | Central Okla. | L | 67 - 81 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Josh Nwankwo | - | 1 | 38.6 | 24.0 | 14.0 | 6.0 | 3.0 | 0.0 | 3.0 | 17.0 | 27.0 | -1 | -0.1 | -0.3 | 41.2 | 0.0 | 76.9 | 2.73 | 52.8 | 41.2 |
| Matthew Willenborg | - | 1 | 36.8 | 23.0 | 9.0 | 1.0 | 2.0 | 2.0 | 1.0 | 18.0 | 18.0 | 42 | 1.8 | 13.1 | 50.0 | 25.0 | 100.0 | 2.75 | 58.2 | 52.8 |
| Ben Averitt | - | 1 | 30.5 | 14.0 | 5.0 | 3.0 | 0.0 | 0.0 | 0.0 | 11.0 | 11.0 | 76 | 3.5 | 39.8 | 63.6 | 0 | 0 | -0.66 | 63.6 | 63.6 |
| Parker Hannah | - | 1 | 30.9 | 10.0 | 3.0 | 1.0 | 0.0 | 0.0 | 1.0 | 10.0 | 3.0 | 42 | 1.8 | 14.3 | 40.0 | 28.6 | 0 | -1.55 | 50.0 | 50.0 |
| Marcus Zeigler, Jr. | - | 1 | 30.5 | 5.0 | 6.0 | 6.0 | 1.0 | 1.0 | 1.0 | 6.0 | 12.0 | 107 | 4.7 | 25.2 | 33.3 | 0.0 | 100.0 | 1.54 | 38.8 | 33.3 |
| Connor Newton | - | 1 | 9.5 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 2.0 | 1.0 | 26 | 2.9 | 183.0 | 50.0 | 0.0 | 50.0 | 0.08 | 52.1 | 50.0 |
| Trey Tuck | - | 1 | 11.2 | 2.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 2.0 | 1.0 | 32 | 1.5 | 78.7 | 50.0 | 0.0 | 0 | 0.32 | 50.0 | 50.0 |
| Brady Hancuff | - | 1 | 12.1 | 0.0 | 1.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | 1.0 | 5 | 0.2 | 4.1 | 0 | 0 | 0 | -3.69 | 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