UCLA
2024 Team Stats (33 games)
66.0
PPG
65.5
Opp
+0.5
Margin
41.9%
FG%
33.2%
3P%
73.0%
FT%
33.8
RPG
11.2
APG
10.8
TO
74.6
Pace
Model Outputs
2023-2024
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 → | 1260 (#62) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1273 (#80) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +34.4 (#50) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.421 (#72) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.485 (#185) | NetEff -0.5 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.485 (#73) | AdjNet -0.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.482 (#73) | AdjNet -0.6 |
2024 Schedule & Results
2024 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
D. Andrews
|
- | 32 | 35.2 | 12.9 | 2.2 | 3.7 | 0.8 | 0.1 | 1.9 | 12.1 | 5.7 | 2 | 0.1 | 0.3 | 39.5 | 32.4 | 80.8 | 0.05 | 49.2 | 45.6 |
Adem Bona
|
- | 33 | 26.5 | 12.4 | 5.9 | 1.2 | 1.1 | 1.8 | 2.5 | 7.9 | 12.1 | 18 | 2.2 | 4.4 | 58.8 | 0.0 | 69.6 | 0.35 | 62.9 | 58.8 |
S. Mack
|
- | 33 | 26.8 | 12.1 | 3.6 | 1.6 | 1.3 | 0.1 | 1.6 | 9.6 | 7.4 | -10 | -1.2 | -2.5 | 38.7 | 28.3 | 72.7 | -0.13 | 50.7 | 43.1 |
L. Stefanovic
|
- | 33 | 34.6 | 11.5 | 6.1 | 1.6 | 1.1 | 0.1 | 1.1 | 9.6 | 9.8 | -7 | -0.8 | -1.2 | 38.5 | 38.9 | 86.8 | -0.08 | 53.4 | 47.6 |
B. Buyuktuncel
|
F | 26 | 16.3 | 4.5 | 2.5 | 0.4 | 0.2 | 0.3 | 0.8 | 4.0 | 3.1 | 25 | 1.2 | 13.1 | 38.5 | 29.7 | 62.8 | 0.26 | 48.0 | 43.8 |
W. McClendon
|
G | 33 | 21.1 | 4.1 | 3.3 | 1.1 | 0.6 | 0.1 | 0.5 | 3.8 | 4.7 | 19 | 2.4 | 5.6 | 33.9 | 35.4 | 71.4 | 0.34 | 48.1 | 44.9 |
Aday Mara
|
- | 28 | 9.5 | 3.5 | 1.9 | 0.5 | 0.1 | 0.7 | 0.7 | 3.1 | 3.0 | -136 | -8.0 | -140.6 | 44.2 | 0 | 70.0 | -0.4 | 48.9 | 44.2 |
Brandon Williams
|
- | 32 | 17.3 | 3.1 | 2.2 | 0.5 | 0.2 | 0.1 | 0.4 | 3.5 | 2.3 | -46 | -5.8 | -12.5 | 35.7 | 25.0 | 61.9 | -0.67 | 41.2 | 38.8 |
J. Vide
|
- | 24 | 7.3 | 1.9 | 0.8 | 0.5 | 0.2 | 0.0 | 0.4 | 2.1 | 0.8 | 33 | 1.5 | 23.2 | 38.0 | 66.7 | 75.0 | 0.12 | 43.0 | 40.0 |
Devin Williams
|
- | 10 | 3.3 | 1.4 | 0.7 | 0.0 | 0.0 | 0.1 | 0.2 | 0.8 | 1.2 | -38 | -2.4 | -416.4 | 62.5 | 0.0 | 57.1 | 0.04 | 63.2 | 62.5 |
K. Nwuba
|
- | 33 | 8.0 | 1.3 | 1.5 | 0.2 | 0.2 | 0.1 | 0.4 | 0.8 | 2.0 | -9 | -1.1 | -6.5 | 57.1 | 0 | 52.6 | -0.08 | 57.8 | 57.1 |
Ilane Fibleuil
|
- | 25 | 6.4 | 1.0 | 1.5 | 0.2 | 0.2 | 0.2 | 0.2 | 0.9 | 2.0 | -2 | -0.5 | -24.9 | 43.5 | 20.0 | 75.0 | 0.0 | 50.5 | 47.8 |
L. Cremonesi
|
- | 3 | 1.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -1 | -0.5 | -14.8 | 0 | 0 | 0 | -0.02 | 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