California Golden Bears
2023 Team Stats (13 games)
66.2
PPG
78.1
Opp
-11.9
Margin
39.3%
FG%
36.3%
3P%
73.5%
FT%
31.8
RPG
13.5
APG
13.8
TO
81.5
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 → | 1063 (#155) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1176 (#100) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +37.1 (#43) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.626 (#142) | - |
2023 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2022-11-12 | @ | Notre Dame Fighting Irish | L | 79 - 90 |
| 2022-11-26 | vs | Montana Lady Griz | W | 65 - 44 |
| 2022-12-23 | @ | Stanford Cardinal | L | 69 - 90 |
| 2022-12-31 | vs | Arizona Wildcats | L | 56 - 63 |
| 2023-01-08 | vs | Stanford Cardinal | L | 56 - 60 |
| 2023-01-15 | @ | UCLA Bruins | L | 70 - 87 |
| 2023-01-20 | vs | Colorado Buffaloes | L | 66 - 73 |
| 2023-01-22 | vs | Utah Utes | L | 62 - 87 |
| 2023-02-12 | @ | Arizona Wildcats | L | 57 - 80 |
| 2023-02-17 | vs | UCLA Bruins | L | 54 - 67 |
| 2023-02-19 | vs | USC Trojans | W | 81 - 78 |
| 2023-02-23 | @ | Utah Utes | L | 76 - 101 |
| 2023-02-25 | @ | Colorado Buffaloes | L | 69 - 95 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
J. Curry
|
G | 13 | 34.9 | 17.8 | 3.6 | 3.7 | 0.5 | 0.0 | 2.5 | 16.2 | 7.0 | - | - | - | 36.7 | 35.4 | 82.0 | - | 49.0 | 43.3 |
K. Martin
|
G | 13 | 29.0 | 11.7 | 3.8 | 1.5 | 0.7 | 0.3 | 1.8 | 10.8 | 5.4 | - | - | - | 39.3 | 42.3 | 70.6 | - | 51.5 | 50.0 |
L. McIntosh
|
G | 13 | 34.2 | 10.2 | 2.7 | 3.2 | 1.5 | 0.0 | 2.0 | 8.3 | 7.2 | - | - | - | 43.5 | 35.7 | 80.0 | - | 54.9 | 50.5 |
E. Lutje Schipholt
|
F | 12 | 20.1 | 7.2 | 4.2 | 1.0 | 0.8 | 0.8 | 1.3 | 6.2 | 6.3 | - | - | - | 45.3 | 0 | 63.3 | - | 49.3 | 45.3 |
U. Onyiah
|
F | 13 | 14.2 | 6.4 | 4.6 | 0.3 | 0.5 | 1.2 | 1.2 | 6.0 | 5.8 | - | - | - | 42.3 | 0 | 63.0 | - | 46.2 | 42.3 |
J. Bush
|
F | 3 | 9.0 | 4.7 | 3.3 | 0.0 | 0.3 | 0.7 | 0.3 | 2.7 | 6.0 | - | - | - | 37.5 | 0 | 88.9 | - | 58.5 | 37.5 |
P. Tuitele
|
F | 12 | 18.8 | 3.6 | 4.0 | 0.8 | 0.7 | 0.2 | 0.8 | 4.2 | 4.2 | - | - | - | 39.2 | 22.2 | 50.0 | - | 41.4 | 41.2 |
C. Langarita
|
F | 12 | 12.5 | 3.4 | 1.1 | 0.2 | 0.5 | 0.2 | 1.0 | 3.2 | 1.3 | - | - | - | 42.1 | 30.0 | 75.0 | - | 49.4 | 46.1 |
M. Mastrov
|
G | 11 | 11.8 | 2.7 | 0.6 | 0.7 | 0.5 | 0.1 | 0.7 | 2.6 | 1.3 | - | - | - | 31.0 | 36.4 | 66.7 | - | 47.4 | 44.8 |
K. Ortiz
|
G | 13 | 23.5 | 2.3 | 2.1 | 2.3 | 0.4 | 0.7 | 1.5 | 2.5 | 3.8 | - | - | - | 31.2 | 30.8 | 75.0 | - | 42.2 | 37.5 |
S. Heide
|
F | 4 | 3.0 | 1.5 | 0.2 | 0.0 | 0.0 | 0.5 | 0.2 | 1.8 | 0.2 | - | - | - | 42.9 | 0 | 0 | - | 42.9 | 42.9 |
O. Muca
|
G | 5 | 2.2 | 0.6 | 0.4 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8 | 0.2 | - | - | - | 25.0 | 50.0 | 0 | - | 37.5 | 37.5 |
A. Bonner
|
G | 11 | 5.5 | 0.5 | 0.5 | 0.0 | 0.0 | 0.0 | 0.3 | 1.1 | -0.3 | - | - | - | 25.0 | 0.0 | 0.0 | - | 23.3 | 25.0 |
B. Stevens
|
G | 2 | 1.0 | 0.0 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Numbers/Game vs RAPM
Not enough players with both Numbers/Game and RAPM to plot.
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