UCLA
2022 Team Stats (30 games)
74.9
PPG
64.5
Opp
+10.9
Margin
44.8%
FG%
34.6%
3P%
74.4%
FT%
36.6
RPG
13.8
APG
8.7
TO
77.9
Pace
Model Outputs
2021-2022
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 → | 1345 (#59) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1456 (#23) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +38.5 (#25) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.774 (#10) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.842 (#27) | NetEff +14.9 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.858 (#11) | AdjNet +15.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.860 (#11) | AdjNet +15.7 |
2022 Schedule & Results
2022 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Johnny Juzang
|
- | 30 | 31.8 | 15.6 | 4.7 | 1.8 | 0.7 | 0.1 | 1.6 | 13.4 | 8.1 | - | - | - | 43.1 | 35.5 | 83.6 | - | 54.1 | 48.5 |
Jaime Jaquez Jr.
|
- | 34 | 30.5 | 13.9 | 5.7 | 2.3 | 1.1 | 0.3 | 1.4 | 10.6 | 11.4 | 74 | 6.2 | 8.2 | 46.9 | 26.0 | 76.1 | 1.26 | 56.4 | 49.6 |
J. Bernard
|
- | 33 | 30.8 | 12.9 | 4.8 | 1.7 | 1.0 | 0.2 | 1.0 | 10.1 | 9.5 | - | - | - | 41.7 | 33.3 | 82.8 | - | 55.3 | 49.4 |
T. Campbell
|
- | 33 | 32.4 | 11.9 | 2.5 | 4.3 | 1.0 | 0.1 | 1.3 | 9.3 | 9.2 | -40 | -2.5 | -3.4 | 44.4 | 40.0 | 82.9 | 0.73 | 57.9 | 52.3 |
C. Riley
|
F | 25 | 22.3 | 7.6 | 3.9 | 1.0 | 0.7 | 0.4 | 0.9 | 6.1 | 6.6 | - | - | - | 46.4 | 50.0 | 67.2 | - | 52.2 | 47.7 |
Jaylen Clark
|
- | 29 | 18.1 | 6.7 | 3.8 | 1.0 | 1.1 | 0.2 | 0.7 | 5.4 | 6.8 | 40 | 5.0 | 29.4 | 50.0 | 26.9 | 51.2 | 0.75 | 55.7 | 52.2 |
D. Singleton
|
- | 33 | 16.8 | 4.8 | 1.5 | 0.9 | 0.5 | 0.2 | 0.3 | 3.4 | 4.2 | - | - | - | 47.8 | 44.3 | 61.5 | - | 66.5 | 63.3 |
Miles Johnson
|
C | 33 | 17.9 | 3.5 | 5.2 | 0.7 | 0.5 | 1.2 | 1.0 | 2.2 | 7.8 | 40 | 2.9 | 3.5 | 62.2 | 0 | 56.1 | 1.38 | 62.5 | 62.2 |
P. Watson
|
- | 30 | 12.2 | 2.6 | 2.8 | 0.8 | 0.5 | 0.6 | 0.9 | 3.2 | 3.3 | - | - | - | 28.4 | 25.0 | 67.9 | - | 36.8 | 31.6 |
Jake Kyman
|
- | 21 | 7.9 | 2.5 | 1.0 | 0.5 | 0.2 | 0.0 | 0.1 | 2.5 | 1.7 | - | - | - | 36.5 | 26.7 | 100.0 | - | 47.6 | 44.2 |
K. Nwuba
|
- | 20 | 6.3 | 1.2 | 0.9 | 0.2 | 0.1 | 0.3 | 0.3 | 0.7 | 1.6 | - | - | - | 61.5 | 0 | 50.0 | - | 72.6 | 61.5 |
R. Stong
|
- | 12 | 1.8 | 0.2 | 0.3 | 0.1 | 0.0 | 0.0 | 0.2 | 0.2 | 0.2 | - | - | - | 33.3 | 33.3 | 0 | - | 50.0 | 50.0 |
W. McClendon
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
L. Cremonesi
|
- | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 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