California Golden Bears
2022 Team Stats (1 games)
74.0
PPG
97.0
Opp
-23.0
Margin
44.2%
FG%
46.7%
3P%
70.0%
FT%
24.0
RPG
15.0
APG
19.0
TO
84.2
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 → | 1067 (#151) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1174 (#94) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +37.4 (#42) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.626 (#142) | - |
2022 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2022-01-16 | @ | Colorado Buffaloes | - | Preview |
| 2022-01-21 | @ | Stanford Cardinal | L | 74 - 97 |
| 2022-01-23 | vs | Stanford Cardinal | - | Preview |
| 2022-01-28 | vs | Arizona Wildcats | - | Preview |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
J. Curry
|
G | 1 | 36.0 | 30.0 | 1.0 | 2.0 | 1.0 | 0.0 | 2.0 | 17.0 | 15.0 | - | - | - | 41.2 | 50.0 | 85.7 | 0.48 | 64.8 | 52.9 |
L. McIntosh
|
G | 1 | 35.0 | 14.0 | 2.0 | 3.0 | 1.0 | 0.0 | 3.0 | 7.0 | 10.0 | - | - | - | 57.1 | 75.0 | 75.0 | 0.33 | 79.9 | 78.6 |
E. Lutje Schipholt
|
F | 1 | 30.0 | 9.0 | 3.0 | 2.0 | 1.0 | 0.0 | 3.0 | 7.0 | 5.0 | -12 | -0.8 | -6.2 | 57.1 | 0 | 50.0 | 0.19 | 57.1 | 57.1 |
M. Mastrov
|
G | 1 | 20.0 | 7.0 | 0.0 | 0.0 | 1.0 | 0.0 | 1.0 | 9.0 | -2.0 | 100 | 5.6 | 24.0 | 33.3 | 0.0 | 50.0 | 1.37 | 35.4 | 33.3 |
D. Daniels
|
F | 1 | 23.0 | 5.0 | 3.0 | 2.0 | 1.0 | 0.0 | 4.0 | 4.0 | 3.0 | -15 | -0.9 | -6.3 | 50.0 | 0 | 50.0 | 0.58 | 51.2 | 50.0 |
F. Samb
|
C | 1 | 18.0 | 3.0 | 5.0 | 1.0 | 1.0 | 0.0 | 1.0 | 2.0 | 7.0 | 37 | 2.2 | 13.3 | 50.0 | 0 | 50.0 | 0.61 | 52.1 | 50.0 |
A. Elsnitz
|
G | 1 | 7.0 | 3.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 4.0 | 6 | 0.8 | 3.7 | 100.0 | 0 | 50.0 | 0.39 | 79.8 | 100.0 |
U. Onyiah
|
F | 1 | 13.0 | 2.0 | 2.0 | 3.0 | 0.0 | 0.0 | 2.0 | 1.0 | 4.0 | - | - | - | 100.0 | 0 | 0 | 0.64 | 100.0 | 100.0 |
C. Crocker
|
G | 1 | 14.0 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 3.0 | 0.0 | 71 | 3.7 | 26.5 | 0.0 | 0.0 | 50.0 | 0.97 | 12.9 | 0.0 |
J. Green
|
G | 1 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -22 | -1.2 | -10.6 | 0 | 0 | 0 | 0.44 | 0 | 0 |
O. Muca
|
G | 1 | 2.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 53 | 17.7 | 85.7 | 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