NC State Wolfpack
2026 Team Stats (31 games)
83.7
PPG
77.6
Opp
+6.1
Margin
46.7%
FG%
39.1%
3P%
77.4%
FT%
34.1
RPG
15.1
APG
9.1
TO
79.4
Pace
87.8
AdjO
71.1
AdjD
#32
Rank
Model Outputs
2025-2026
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 → | 1047 (#143) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1206 (#48) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 977 (#556) | HCA +109 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +16.6 (#33) | HCA +2.2 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +23.6 (#63) | HCA +2.5 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.731 (#54) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.643 (#132) | NetEff +5.6 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.925 (#34) | AdjNet +21.8 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.928 (#34) | AdjNet +22.0 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.821 (#32) | AdjO 87.8 | AdjD 71.1 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.612 (#103) | AdjO 80.5 | AdjD 75.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.899 (#53) | 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 → | 0.857 (#58) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1167 (#81) | RD 118 | GP 31 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dar. Williams
|
- | 30 | 30.5 | 14.6 | 4.5 | 2.6 | 1.0 | 0.3 | 1.5 | 12.5 | 8.9 | 9 | 0.8 | 8.3 | 41.9 | 41.8 | 75.8 | 0.05 | 54.3 | 52.0 |
P. McNeil
|
G | 31 | 29.4 | 14.5 | 3.6 | 0.9 | 0.6 | 0.4 | 0.4 | 9.6 | 10.0 | - | - | - | 44.3 | 43.8 | 82.7 | - | 65.3 | 60.9 |
Q. Copeland
|
G | 31 | 29.2 | 14.0 | 3.5 | 6.5 | 1.7 | 0.2 | 2.9 | 9.1 | 13.9 | -3 | -0.3 | -1.7 | 50.0 | 39.1 | 78.8 | 0.32 | 60.8 | 53.2 |
V. Lubin
|
- | 31 | 28.3 | 13.4 | 7.0 | 0.8 | 0.5 | 0.8 | 0.8 | 7.6 | 14.1 | 76 | 3.5 | 12.5 | 66.5 | 30.0 | 76.2 | 0.08 | 70.9 | 67.2 |
T. Holloman
|
G | 29 | 25.7 | 9.3 | 2.0 | 2.1 | 0.9 | 0.2 | 1.2 | 6.8 | 6.6 | -3 | -0.3 | -1.8 | 42.1 | 40.2 | 82.6 | 0.06 | 59.4 | 54.1 |
Matt Able
|
- | 31 | 22.0 | 8.7 | 3.4 | 0.9 | 1.3 | 0.3 | 0.9 | 7.5 | 6.2 | 124 | 5.6 | 19.9 | 40.3 | 34.4 | 78.7 | 0.89 | 53.0 | 49.8 |
J. Deng
|
F | 6 | 13.7 | 7.3 | 2.3 | 0.3 | 0.7 | 0.2 | 0.5 | 6.3 | 4.0 | -15 | -15.0 | -34.1 | 36.8 | 33.3 | 85.7 | 0.04 | 53.6 | 50.0 |
A. Breed
|
G | 18 | 13.9 | 4.4 | 1.9 | 1.1 | 0.7 | 0.0 | 0.4 | 3.5 | 4.2 | 46 | 2.7 | 13.4 | 39.7 | 33.3 | 91.7 | 0.3 | 54.4 | 46.0 |
T. Arceneaux
|
G | 27 | 15.8 | 3.8 | 2.6 | 0.5 | 0.9 | 0.4 | 0.4 | 3.4 | 4.4 | 0 | 0.0 | 0.0 | 41.3 | 30.0 | 77.8 | 0.41 | 51.0 | 47.8 |
Musa Sagnia
|
- | 31 | 12.4 | 2.2 | 2.9 | 0.3 | 0.6 | 0.5 | 0.5 | 1.7 | 4.4 | -30 | -3.3 | -39.2 | 57.7 | 25.0 | 40.0 | 0.35 | 56.7 | 58.7 |
S. Ebube
|
- | 16 | 3.9 | 1.2 | 0.8 | 0.0 | 0.2 | 0.5 | 0.2 | 0.5 | 1.9 | -7 | -1.8 | -52.5 | 100.0 | 0 | 25.0 | 0.03 | 71.5 | 100.0 |
J. Snell
|
G | 7 | 2.1 | 0.4 | 0.1 | 0.3 | 0.0 | 0.0 | 0.0 | 1.0 | -0.1 | 2 | 0.3 | 3.2 | 14.3 | 16.7 | 0 | 0.03 | 21.4 | 21.4 |
C. Langdon
|
- | 5 | 2.8 | 0.4 | 0.2 | 0.0 | 0.0 | 0.0 | 0.2 | 0.8 | -0.4 | -9 | -1.5 | -10.9 | 0.0 | 0.0 | 100.0 | -0.01 | 20.5 | 0.0 |
Zymicah Wilkins
|
F | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Jayme Kontuniemi
|
G | 0 | - | 0.0 | 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