West Virginia Mountaineers
2025 Team Stats (32 games)
74.8
PPG
55.7
Opp
+19.4
Margin
44.6%
FG%
32.1%
3P%
76.1%
FT%
34.7
RPG
13.3
APG
15.6
TO
84.2
Pace
80.1
AdjO
49.0
AdjD
#13
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 → | 1315 (#22) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1309 (#33) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +31.6 (#13) | HCA +2.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.969 (#6) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.967 (#5) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.996 (#10) | AdjNet +47.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.996 (#10) | AdjNet +48.2 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.944 (#13) | AdjO 80.1 | AdjD 49.0 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
JJ Quinerly
|
- | 32 | 31.5 | 20.4 | 3.1 | 3.2 | 3.0 | 0.3 | 3.2 | 16.4 | 10.3 | 31 | 0.9 | 1.0 | 44.3 | 31.4 | 82.9 | 0.92 | 54.5 | 49.0 |
J. Harrison
|
G | 33 | 30.8 | 13.7 | 3.3 | 4.5 | 2.2 | 0.2 | 3.2 | 10.4 | 10.2 | 47 | 1.4 | 1.6 | 43.9 | 36.9 | 82.7 | 0.7 | 56.3 | 49.9 |
S. Shaw
|
G | 32 | 31.7 | 11.4 | 3.7 | 1.6 | 1.8 | 0.3 | 1.7 | 9.7 | 7.3 | 78 | 2.4 | 2.7 | 41.8 | 33.5 | 88.1 | 1.55 | 55.2 | 52.6 |
J. Thomas
|
F | 33 | 16.1 | 6.2 | 4.3 | 0.4 | 0.4 | 0.3 | 1.2 | 4.5 | 5.9 | 10 | 0.3 | 0.6 | 54.4 | 0 | 60.8 | 0.55 | 57.1 | 54.4 |
K. Blacksten
|
F | 33 | 17.8 | 6.1 | 2.3 | 0.5 | 0.6 | 0.3 | 1.0 | 5.4 | 3.5 | 24 | 0.7 | 1.5 | 43.0 | 31.6 | 81.8 | 0.29 | 53.5 | 51.4 |
K. Watson
|
G | 33 | 31.6 | 5.9 | 7.6 | 1.5 | 3.1 | 0.5 | 1.8 | 5.5 | 11.2 | 75 | 2.2 | 2.5 | 41.2 | 27.9 | 63.6 | 1.89 | 49.6 | 47.8 |
S. Woodley
|
G | 32 | 15.8 | 3.9 | 2.1 | 0.6 | 1.7 | 0.0 | 0.6 | 2.7 | 5.0 | 33 | 1.0 | 2.0 | 52.3 | 34.6 | 77.1 | 0.85 | 62.1 | 57.6 |
C. Rivière
|
F | 26 | 10.7 | 3.3 | 2.6 | 1.0 | 0.3 | 0.2 | 0.7 | 3.1 | 3.6 | - | - | - | 42.5 | 25.0 | 76.2 | - | 48.2 | 43.8 |
D. Agubata
|
G | 24 | 5.5 | 2.5 | 1.2 | 0.2 | 0.3 | 0.0 | 0.9 | 1.8 | 1.6 | -12 | -0.5 | -3.4 | 46.5 | 29.4 | 83.3 | -0.5 | 58.9 | 52.3 |
T. Moore
|
F | 29 | 8.2 | 2.4 | 1.6 | 0.0 | 0.3 | 0.1 | 0.7 | 1.8 | 1.9 | 86 | 2.5 | 3.5 | 45.3 | 0 | 57.9 | 0.94 | 50.2 | 45.3 |
Z. Nugent
|
G | 20 | 5.7 | 1.6 | 1.2 | 0.3 | 0.2 | 0.0 | 0.9 | 1.4 | 1.0 | -4 | -0.2 | -1.1 | 39.3 | 12.5 | 55.6 | -0.46 | 45.9 | 41.1 |
A. Moseberry
|
G | 7 | 3.0 | 1.4 | 0.3 | 0.0 | 0.6 | 0.1 | 0.3 | 0.9 | 1.3 | 1 | 0.1 | 2.0 | 50.0 | 33.3 | 75.0 | -1.38 | 64.4 | 58.3 |
D. Arigbabu
|
F | 15 | 5.8 | 1.1 | 0.5 | 0.3 | 0.1 | 0.2 | 0.2 | 0.6 | 1.4 | -1 | -0.1 | -0.5 | 66.7 | 0 | 57.1 | -0.63 | 66.2 | 66.7 |
F. Atili
|
F | 8 | 3.2 | 0.9 | 0.8 | 0.1 | 0.1 | 0.0 | 0.6 | 0.5 | 0.8 | - | - | - | 50.0 | 0 | 50.0 | - | 52.7 | 50.0 |
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