N.C. Central
Model Outputs
2025-2026 latest available
No materialized model snapshot for 2024 yet, so this section is showing the latest available team-model rows.
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 → | 1061 (#219) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1068 (#139) | HCA +62 elo |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1044 (#196) | HCA +62 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +47.5 (#31) | HCA +2.9 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +10.7 (#203) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 1.000 (#106) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 1.000 (#39) | NetEff +65.7 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.994 (#97) | AdjNet +44.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.995 (#98) | AdjNet +43.4 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.960 (#70) | AdjO 90.8 | AdjD 55.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.938 (#5) | AdjO 87.7 | AdjD 57.7 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.677 (#144) | AdjO 67.5 | AdjD 59.3 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.938 (#34) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.662 (#250) | 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 → | 0.938 (#28) | 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 → | 0.675 (#239) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1077 (#213) | RD 105 | GP 21 |
2024 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2023-11-19 | vs | JWU (Charlotte) | W | 83 - 50 |
| 2024-01-16 | vs | N.C. Wesleyan | W | 110 - 42 |
2024 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Kimeira Burks | - | 1 | 34.0 | 25.0 | 3.0 | 2.0 | 3.0 | 0.0 | 2.0 | 17.0 | 14.0 | - | - | - | 41.2 | 41.7 | 100.0 | - | 63.6 | 55.9 |
| Kimia Carter | - | 1 | 16.0 | 17.0 | 5.0 | 2.0 | 0.0 | 0.0 | 1.0 | 9.0 | 14.0 | - | - | - | 66.7 | 66.7 | 33.3 | - | 82.4 | 88.9 |
| Morgan Callahan | - | 2 | 29.0 | 16.5 | 12.5 | 5.0 | 1.5 | 0.5 | 3.5 | 13.0 | 19.5 | - | - | - | 57.7 | 0 | 75.0 | 0.39 | 59.4 | 57.7 |
| Sydney Avoletta | - | 1 | 18.0 | 16.0 | 10.0 | 0.0 | 0.0 | 4.0 | 1.0 | 10.0 | 19.0 | - | - | - | 70.0 | 0 | 33.3 | - | 63.3 | 70.0 |
| Kyla Bryant | - | 2 | 27.5 | 14.5 | 5.5 | 1.5 | 3.0 | 0.5 | 3.5 | 13.0 | 8.5 | 61 | 5.5 | 10.9 | 50.0 | 11.1 | 40.0 | 0.44 | 51.4 | 51.9 |
| Janiah Jones | - | 2 | 22.5 | 11.5 | 4.0 | 3.0 | 3.0 | 0.0 | 3.0 | 9.5 | 9.0 | 88 | 14.7 | 16.2 | 47.4 | 12.5 | 100.0 | 0.78 | 55.4 | 50.0 |
| Aniya Finger | - | 1 | 9.0 | 11.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0 | 7.0 | - | - | - | 71.4 | 0 | 100.0 | - | 73.9 | 71.4 |
| Jada Tiggett | - | 2 | 18.5 | 8.0 | 4.5 | 0.5 | 1.0 | 3.0 | 2.5 | 7.0 | 7.5 | - | - | - | 42.9 | 0.0 | 100.0 | - | 50.8 | 42.9 |
| Nijah Cunningham | - | 1 | 21.0 | 8.0 | 7.0 | 0.0 | 0.0 | 1.0 | 4.0 | 9.0 | 3.0 | - | - | - | 44.4 | 0 | 0 | - | 44.4 | 44.4 |
| Ray'ven Robinson | - | 2 | 21.5 | 5.0 | 5.0 | 7.0 | 1.5 | 0.5 | 3.0 | 6.5 | 9.5 | 54 | 5.4 | 16.2 | 38.5 | 0.0 | 0.0 | 0.08 | 34.9 | 38.5 |
| Tippy Robertson | - | 2 | 31.0 | 2.5 | 6.0 | 8.5 | 2.0 | 0.0 | 3.0 | 4.0 | 12.0 | - | - | - | 25.0 | 33.3 | 0 | - | 31.2 | 31.2 |
| Taylor Williams | - | 1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -22 | -1.6 | -2.1 | 0 | 0 | 0 | 0.3 | 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