North Carolina Tar Heels
2026 Team Stats (36 games)
74.6
PPG
59.1
Opp
+15.5
Margin
45.1%
FG%
35.1%
3P%
68.9%
FT%
39.9
RPG
15.5
APG
14.4
TO
83.4
Pace
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 → | 1177 (#10) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +40.8 (#14) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.860 (#12) | AdjO 72.5 | AdjD 52.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.980 (#11) | 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 → | 0.973 (#11) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1351 (#14) | RD 101 | GP 36 |
2026 Schedule & Results
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
N. Harris
|
F | 35 | 23.8 | 11.4 | 6.9 | 0.9 | 1.0 | 0.3 | 1.6 | 7.7 | 11.0 | 180 | 8.2 | 16.4 | 57.6 | 13.3 | 78.7 | 3.23 | 62.6 | 57.9 |
L. Grant
|
G | 34 | 29.0 | 10.8 | 1.9 | 2.3 | 0.6 | 0.1 | 1.8 | 8.3 | 5.5 | 169 | 8.0 | 11.7 | 44.0 | 41.9 | 80.7 | -0.37 | 59.6 | 56.7 |
I. Nivar
|
G | 35 | 28.7 | 10.6 | 5.2 | 3.7 | 2.7 | 0.5 | 2.6 | 9.3 | 10.9 | 187 | 7.8 | 12.0 | 45.1 | 31.2 | 60.0 | 0.93 | 51.0 | 48.9 |
E. Aarnisalo
|
G | 36 | 26.7 | 10.2 | 3.4 | 2.9 | 0.9 | 0.2 | 2.2 | 8.6 | 6.7 | 181 | 7.9 | 12.5 | 47.3 | 40.4 | 76.1 | 1.39 | 55.4 | 53.4 |
C. Toomey
|
F | 36 | 23.3 | 8.8 | 6.2 | 1.4 | 0.7 | 1.5 | 1.4 | 6.6 | 10.6 | 137 | 6.0 | 9.9 | 54.4 | 29.6 | 66.7 | 3.38 | 60.3 | 58.8 |
N. Brooks
|
G | 36 | 19.9 | 8.6 | 3.5 | 1.1 | 0.8 | 0.4 | 1.5 | 8.1 | 4.7 | 210 | 9.1 | 19.9 | 36.6 | 37.7 | 59.6 | 5.55 | 49.0 | 47.4 |
R. Kelly
|
G | 23 | 25.4 | 6.1 | 2.0 | 2.2 | 1.3 | 0.1 | 1.3 | 7.3 | 3.2 | 142 | 6.5 | 10.1 | 28.6 | 32.3 | 78.1 | 1.61 | 38.7 | 34.5 |
L. Hull
|
G | 31 | 12.2 | 4.0 | 1.9 | 0.8 | 0.6 | 0.4 | 0.5 | 3.7 | 3.5 | 94 | 4.9 | 15.4 | 36.8 | 34.0 | 69.2 | 0.17 | 52.2 | 50.9 |
T. Henderson
|
G | 33 | 10.4 | 3.7 | 2.0 | 0.3 | 0.6 | 0.0 | 0.5 | 2.7 | 3.5 | 98 | 4.5 | 17.1 | 56.8 | 28.6 | 48.3 | 2.21 | 60.5 | 61.4 |
T. Queiroz
|
G | 25 | 12.0 | 2.8 | 2.8 | 0.9 | 0.3 | 0.2 | 1.0 | 2.5 | 3.4 | 61 | 4.7 | 17.4 | 49.2 | 0.0 | 70.0 | 0.22 | 51.2 | 49.2 |
J. Zubich
|
G | 17 | 6.8 | 2.1 | 0.4 | 0.2 | 0.1 | 0.0 | 0.4 | 2.0 | 0.4 | 64 | 5.3 | 29.4 | 32.4 | 32.3 | 75.0 | 0.03 | 48.9 | 47.1 |
L. Astakhova
|
F | 12 | 4.7 | 2.1 | 1.0 | 0.2 | 0.0 | 0.0 | 0.2 | 2.4 | 0.6 | 31 | 3.9 | 31.3 | 34.5 | 20.0 | 75.0 | 0.18 | 40.6 | 37.9 |
B. Thomas
|
C | 20 | 6.9 | 1.7 | 1.9 | 0.5 | 0.1 | 0.2 | 0.7 | 1.8 | 1.9 | 41 | 3.4 | 22.5 | 45.7 | 100.0 | 20.0 | 0.01 | 45.7 | 47.1 |
S. Barker
|
G | 16 | 2.9 | 0.4 | 0.4 | 0.4 | 0.1 | 0.0 | 0.1 | 0.8 | 0.5 | 12 | 1.2 | 15.4 | 25.0 | 16.7 | 0.0 | -0.69 | 27.2 | 29.2 |
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