Vanderbilt
2023 Team Stats (25 games)
72.8
PPG
72.4
Opp
-1.8
Margin
42.2%
FG%
33.8%
3P%
72.3%
FT%
35.5
RPG
11.0
APG
9.7
TO
77.7
Pace
Model Outputs
2022-2023
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 → | 1543 (#11) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1352 (#52) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +34.6 (#65) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.442 (#68) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.446 (#205) | NetEff -2.0 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.554 (#58) | AdjNet +1.9 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.547 (#59) | AdjNet +1.6 |
2023 Schedule & Results
2023 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Liam Robbins
|
- | 14 | 22.7 | 14.6 | 6.2 | 1.2 | 0.3 | 3.1 | 0.9 | 8.2 | 16.3 | - | - | - | 52.2 | 43.5 | 69.8 | - | 66.7 | 56.5 |
T. Lawrence
|
- | 24 | 29.8 | 14.2 | 4.7 | 1.5 | 1.0 | 0.1 | 1.6 | 9.4 | 10.5 | - | - | - | 49.3 | 38.0 | 76.5 | 0.02 | 63.0 | 55.3 |
E. Manjon
|
- | 25 | 28.7 | 11.8 | 2.6 | 3.8 | 0.7 | 0.2 | 1.5 | 8.6 | 9.2 | - | - | - | 50.5 | 30.4 | 78.1 | - | 60.1 | 52.1 |
J. Wright
|
- | 22 | 25.5 | 11.3 | 4.9 | 1.7 | 1.4 | 0.1 | 2.0 | 9.3 | 8.1 | 101 | 9.2 | 10.8 | 39.5 | 31.1 | 80.7 | 1.77 | 53.9 | 46.3 |
M. Stute
|
G | 21 | 24.4 | 7.4 | 4.6 | 0.5 | 0.6 | 0.0 | 1.4 | 6.9 | 4.8 | 18 | 1.3 | 1.8 | 29.9 | 30.7 | 67.9 | 1.26 | 49.6 | 42.0 |
C. Smith
|
- | 25 | 17.8 | 4.6 | 2.5 | 0.6 | 0.2 | 0.1 | 0.3 | 3.4 | 4.2 | 9 | 0.8 | 0.9 | 35.3 | 35.6 | 75.0 | 0.89 | 59.6 | 47.6 |
Trey Thomas
|
G | 23 | 21.4 | 4.4 | 1.7 | 0.6 | 0.3 | 0.1 | 0.8 | 4.8 | 1.4 | - | - | - | 26.4 | 24.2 | 92.3 | 0.04 | 44.1 | 36.4 |
Q. Millora-Brown
|
- | 24 | 20.5 | 3.8 | 5.1 | 0.7 | 0.5 | 0.7 | 0.9 | 2.6 | 7.3 | - | - | - | 46.0 | 50.0 | 56.4 | - | 57.4 | 46.8 |
P. Lewis
|
G | 18 | 10.7 | 3.6 | 0.6 | 0.8 | 0.6 | 0.0 | 0.6 | 2.8 | 2.2 | - | - | - | 48.0 | 45.2 | 40.0 | -0.4 | 61.3 | 62.0 |
N. Shelby
|
- | 9 | 9.3 | 2.9 | 0.4 | 0.0 | 0.1 | 0.0 | 0.1 | 3.0 | 0.3 | - | - | - | 29.6 | 28.6 | 80.0 | - | 44.5 | 40.7 |
M. Dia
|
F | 13 | 8.3 | 2.4 | 1.2 | 0.1 | 0.3 | 0.6 | 0.5 | 2.6 | 1.4 | 89 | 5.2 | 7.0 | 26.5 | 35.3 | 0 | 2.0 | 45.6 | 35.3 |
E. Ansong
|
- | 18 | 10.7 | 2.4 | 1.9 | 0.3 | 0.2 | 0.3 | 0.3 | 2.5 | 2.3 | - | - | - | 42.2 | 20.0 | 60.0 | - | 45.6 | 44.4 |
L. Dort
|
- | 10 | 7.7 | 2.1 | 2.6 | 0.2 | 0.0 | 0.6 | 0.6 | 1.2 | 3.7 | -19 | -1.9 | -3.0 | 83.3 | 0 | 20.0 | 0.3 | 73.9 | 83.3 |
M. Keeffe
|
- | 3 | 5.0 | 0.7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7 | 0.0 | - | - | - | 0.0 | 0.0 | 100.0 | - | 34.7 | 0.0 |
A. Samuels
|
- | 1 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
G. Calton
|
- | 3 | 4.3 | 0.0 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3 | 0.0 | - | - | - | 0.0 | 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