USC Trojans
2023 Team Stats (11 games)
63.3
PPG
63.5
Opp
-0.2
Margin
36.8%
FG%
38.0%
3P%
71.8%
FT%
37.1
RPG
12.9
APG
14.2
TO
80.4
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 → | 1158 (#92) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1308 (#38) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +54.5 (#6) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.952 (#12) | - |
2023 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2022-11-26 | vs | Utah State Aggies | W | 79 - 48 |
| 2022-12-15 | vs | UCLA Bruins | L | 56 - 59 |
| 2023-01-01 | @ | Oregon Ducks | L | 45 - 73 |
| 2023-01-08 | @ | UCLA Bruins | L | 60 - 61 |
| 2023-01-15 | vs | Stanford Cardinal | W | 55 - 46 |
| 2023-01-27 | @ | Utah Utes | L | 73 - 83 |
| 2023-01-29 | @ | Colorado Buffaloes | W | 71 - 54 |
| 2023-02-05 | vs | Arizona Wildcats | L | 75 - 81 |
| 2023-02-17 | @ | Stanford Cardinal | L | 47 - 50 |
| 2023-02-19 | @ | California Golden Bears | L | 78 - 81 |
| 2023-03-17 | vs | South Dakota State Jackrabbits | L | 57 - 62 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
K. Sissoko
|
- | 8 | 38.5 | 16.6 | 6.6 | 2.1 | 0.8 | 0.8 | 3.2 | 14.4 | 9.2 | - | - | - | 44.3 | 25.0 | 76.3 | - | 50.5 | 45.2 |
R. Marshall
|
- | 10 | 33.2 | 15.0 | 10.6 | 1.4 | 0.9 | 3.4 | 1.6 | 13.8 | 15.9 | - | - | - | 40.6 | 40.0 | 66.7 | - | 46.4 | 41.3 |
D. Littleton
|
G | 11 | 34.8 | 14.4 | 3.0 | 3.5 | 0.9 | 0.1 | 2.1 | 13.7 | 6.1 | - | - | - | 31.1 | 32.5 | 86.4 | - | 46.4 | 39.7 |
O. Adika
|
G | 11 | 29.0 | 6.7 | 4.3 | 1.7 | 0.7 | 0.3 | 1.7 | 5.9 | 6.1 | - | - | - | 36.9 | 45.9 | 64.3 | - | 52.0 | 50.0 |
K. Williams
|
G | 11 | 25.0 | 5.8 | 2.1 | 2.1 | 0.9 | 0.1 | 1.4 | 5.2 | 4.5 | - | - | - | 29.8 | 37.5 | 72.4 | - | 45.9 | 37.7 |
T. Bigby
|
G | 11 | 18.9 | 4.1 | 1.2 | 0.7 | 0.5 | 0.4 | 0.7 | 2.9 | 3.3 | - | - | - | 43.8 | 60.0 | 83.3 | - | 65.0 | 62.5 |
R. Doumbia
|
G | 9 | 14.8 | 2.8 | 1.3 | 0.9 | 0.2 | 0.1 | 1.0 | 2.2 | 2.1 | - | - | - | 45.0 | 25.0 | 83.3 | - | 55.2 | 50.0 |
A. Miura
|
G | 8 | 15.4 | 2.2 | 0.9 | 0.9 | 0.5 | 0.0 | 1.1 | 2.2 | 1.1 | - | - | - | 33.3 | 42.9 | 0 | - | 50.0 | 50.0 |
K. Love
|
F | 5 | 10.2 | 1.6 | 2.8 | 0.2 | 0.6 | 0.2 | 1.8 | 3.0 | 0.6 | - | - | - | 20.0 | 33.3 | 50.0 | - | 25.2 | 23.3 |
C. Akunwafo
|
C | 11 | 13.1 | 1.6 | 3.6 | 0.3 | 0.3 | 0.7 | 0.8 | 1.8 | 3.9 | - | - | - | 30.0 | 0.0 | 37.5 | - | 33.3 | 30.0 |
B. Perkins
|
G | 2 | 11.5 | 1.5 | 0.5 | 1.5 | 0.0 | 1.0 | 0.5 | 2.5 | 1.5 | - | - | - | 20.0 | 20.0 | 0 | - | 30.0 | 30.0 |
I. Otto
|
G | 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
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