North Carolina Tar Heels
2025 Team Stats (36 games)
69.3
PPG
57.3
Opp
+12.3
Margin
42.0%
FG%
33.9%
3P%
66.5%
FT%
38.6
RPG
13.6
APG
13.0
TO
81.4
Pace
75.3
AdjO
48.3
AdjD
#23
Rank
Model Outputs
2024-2025
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → | 1387 (#12) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1372 (#15) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +27.6 (#24) | HCA +2.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.904 (#31) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.904 (#30) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.992 (#17) | AdjNet +41.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.993 (#17) | AdjNet +42.5 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.921 (#23) | AdjO 75.3 | AdjD 48.3 |
2025 Schedule & Results
2025 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A. Ustby
|
G | 33 | 29.9 | 10.9 | 9.5 | 2.8 | 1.2 | 1.0 | 2.6 | 9.9 | 12.9 | 81 | 2.3 | 3.0 | 45.6 | 34.0 | 55.0 | 1.57 | 49.6 | 48.2 |
M. Gakdeng
|
F | 33 | 25.4 | 10.8 | 7.6 | 0.8 | 0.8 | 1.1 | 1.7 | 7.3 | 12.2 | 32 | 1.0 | 1.4 | 58.7 | 0 | 65.2 | 0.72 | 61.3 | 58.7 |
L. Donarski
|
G | 37 | 30.0 | 10.7 | 1.9 | 1.4 | 1.0 | 0.2 | 0.8 | 9.3 | 5.2 | 91 | 2.4 | 3.6 | 42.3 | 39.8 | 67.7 | 1.49 | 55.7 | 54.8 |
R. Kelly
|
G | 33 | 27.4 | 9.6 | 2.7 | 2.1 | 1.1 | 0.1 | 1.3 | 8.9 | 5.4 | 65 | 2.0 | 3.0 | 41.0 | 41.2 | 86.4 | 1.04 | 50.9 | 47.8 |
I. Nivar
|
G | 34 | 24.0 | 8.3 | 4.5 | 2.0 | 2.0 | 0.4 | 2.3 | 9.1 | 5.9 | 56 | 1.6 | 2.4 | 36.8 | 21.5 | 55.9 | 0.99 | 41.6 | 39.5 |
L. Grant
|
G | 37 | 21.6 | 7.3 | 1.8 | 1.1 | 0.4 | 0.1 | 1.3 | 6.2 | 3.1 | 39 | 1.1 | 1.6 | 36.4 | 34.6 | 80.8 | 1.29 | 51.7 | 46.1 |
T. Crisp
|
G | 28 | 13.9 | 5.6 | 1.5 | 1.1 | 0.5 | 0.1 | 0.7 | 5.3 | 2.9 | -8 | -0.3 | -0.5 | 37.8 | 25.6 | 80.0 | 0.32 | 48.7 | 44.9 |
G. Townsend
|
G | 37 | 15.6 | 4.2 | 2.1 | 2.4 | 0.7 | 0.0 | 1.5 | 3.7 | 4.2 | 18 | 0.5 | 1.0 | 40.9 | 18.4 | 69.2 | 0.26 | 48.5 | 43.4 |
C. Toomey
|
F | 32 | 10.3 | 3.2 | 2.2 | 0.4 | 0.2 | 0.4 | 0.4 | 3.2 | 2.8 | -6 | -0.2 | -0.5 | 39.8 | 31.4 | 25.0 | 0.14 | 46.6 | 47.6 |
L. Hull
|
G | 23 | 7.7 | 2.6 | 1.6 | 0.3 | 0.4 | 0.3 | 0.5 | 2.4 | 2.3 | 17 | 0.7 | 4.5 | 38.2 | 38.9 | 66.7 | -0.31 | 52.0 | 50.9 |
B. Thomas
|
C | 33 | 10.9 | 2.4 | 3.5 | 0.3 | 0.2 | 0.8 | 0.6 | 2.3 | 4.3 | 28 | 0.8 | 2.5 | 36.4 | 0.0 | 59.0 | 0.42 | 41.9 | 36.4 |
S. Barker
|
G | 9 | 3.7 | 1.7 | 0.2 | 0.1 | 0.0 | 0.0 | 0.2 | 0.7 | 1.1 | 35 | 1.2 | 1.4 | 83.3 | 100.0 | 75.0 | 1.09 | 96.6 | 100.0 |
J. Zubich
|
G | 17 | 6.1 | 1.5 | 0.3 | 0.5 | 0.1 | 0.1 | 0.1 | 1.6 | 0.7 | -8 | -0.5 | -3.0 | 28.6 | 20.8 | 100.0 | -0.58 | 43.0 | 37.5 |
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