UCLA
2023 Team Stats (33 games)
73.8
PPG
60.0
Opp
+13.8
Margin
46.0%
FG%
34.5%
3P%
73.9%
FT%
34.9
RPG
14.5
APG
9.9
TO
77.4
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 → | 1307 (#61) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1409 (#32) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +39.0 (#27) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.822 (#4) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.915 (#4) | NetEff +20.3 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.886 (#7) | AdjNet +17.8 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.887 (#7) | AdjNet +17.9 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Jaime Jaquez Jr.
|
- | 33 | 33.3 | 17.8 | 8.3 | 2.2 | 1.5 | 0.6 | 1.8 | 14.6 | 14.1 | 74 | 6.2 | 8.2 | 48.2 | 32.3 | 77.5 | 1.26 | 55.1 | 51.5 |
T. Campbell
|
- | 33 | 32.1 | 13.2 | 2.6 | 5.2 | 1.2 | 0.0 | 1.4 | 11.7 | 9.1 | -40 | -2.5 | -3.4 | 37.7 | 35.0 | 85.0 | 0.73 | 49.9 | 43.9 |
Jaylen Clark
|
- | 26 | 30.1 | 12.8 | 5.8 | 1.8 | 2.7 | 0.3 | 1.3 | 10.3 | 11.8 | 40 | 5.0 | 29.4 | 46.1 | 34.7 | 74.4 | 0.75 | 54.7 | 50.9 |
A. Bailey
|
- | 26 | 27.3 | 11.8 | 3.9 | 2.2 | 1.2 | 0.3 | 2.6 | 9.4 | 7.5 | - | - | - | 51.0 | 35.4 | 72.7 | - | 57.0 | 54.5 |
D. Singleton
|
- | 33 | 28.4 | 8.8 | 2.8 | 1.1 | 1.1 | 0.2 | 0.5 | 6.8 | 6.7 | - | - | - | 41.5 | 41.2 | 85.4 | - | 59.2 | 55.6 |
Adem Bona
|
- | 29 | 23.8 | 8.2 | 5.4 | 0.7 | 0.6 | 1.8 | 1.3 | 4.9 | 10.5 | - | - | - | 68.8 | 0 | 55.1 | - | 67.6 | 68.8 |
D. Andrews
|
- | 32 | 11.0 | 3.4 | 1.0 | 0.9 | 0.3 | 0.1 | 0.5 | 3.0 | 2.2 | -4 | -0.3 | -0.5 | 44.8 | 33.3 | 61.1 | 0.72 | 52.4 | 51.0 |
K. Nwuba
|
- | 31 | 12.7 | 1.4 | 1.6 | 0.4 | 0.2 | 0.6 | 0.4 | 0.9 | 2.8 | - | - | - | 64.3 | 0 | 63.6 | - | 65.5 | 64.3 |
A. Canka
|
- | 20 | 5.5 | 1.4 | 0.8 | 0.1 | 0.1 | 0.1 | 0.2 | 1.2 | 1.0 | - | - | - | 40.0 | 37.5 | 100.0 | 0.17 | 50.4 | 46.0 |
M. Etienne
|
- | 29 | 6.4 | 1.2 | 1.8 | 0.2 | 0.2 | 0.5 | 0.1 | 1.2 | 2.6 | - | - | - | 42.9 | 0 | 40.0 | - | 43.1 | 42.9 |
W. McClendon
|
G | 26 | 9.5 | 1.1 | 1.2 | 0.8 | 0.3 | 0.0 | 0.2 | 1.9 | 1.4 | - | - | - | 20.4 | 7.1 | 60.0 | - | 26.2 | 22.4 |
R. Stong
|
- | 10 | 1.8 | 0.3 | 0.7 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | 0.5 | - | - | - | 0.0 | 0.0 | 75.0 | - | 22.2 | 0.0 |
L. Cremonesi
|
- | 8 | 1.9 | 0.1 | 0.2 | 0.1 | 0.0 | 0.0 | 0.1 | 0.0 | 0.4 | - | - | - | 0 | 0 | 50.0 | - | 56.8 | 0 |
Evan Manjikian
|
F | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -1.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
J. Seidler
|
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