UC Davis
2023 Team Stats (23 games)
73.5
PPG
71.6
Opp
+2.2
Margin
44.1%
FG%
33.4%
3P%
73.8%
FT%
35.0
RPG
11.5
APG
13.9
TO
80.6
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 → | 1188 (#121) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1183 (#149) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +23.4 (#173) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.295 (#96) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.561 (#136) | NetEff +2.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.146 (#105) | AdjNet -15.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.143 (#105) | AdjNet -15.5 |
2023 Schedule & Results
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
E. Pepper
|
- | 22 | 35.8 | 23.1 | 5.8 | 3.5 | 1.7 | 0.1 | 3.5 | 14.3 | 16.4 | - | - | - | 46.2 | 32.8 | 81.0 | - | 67.9 | 52.7 |
Ty Johnson
|
- | 23 | 28.6 | 14.8 | 4.7 | 2.4 | 2.0 | 0.1 | 3.8 | 10.0 | 10.3 | 46 | 3.5 | 5.7 | 42.8 | 27.9 | 75.2 | 1.3 | 62.0 | 45.4 |
J. Johnson
|
- | 1 | 18.0 | 12.0 | 2.0 | 0.0 | 0.0 | 1.0 | 3.0 | 0.0 | 12.0 | 34 | 3.8 | 9.0 | 0 | 0 | 0 | 1.19 | 0 | 0 |
C. Anigwe
|
- | 21 | 23.5 | 11.0 | 5.1 | 0.9 | 0.3 | 1.2 | 1.6 | 7.4 | 9.5 | - | - | - | 46.8 | 32.4 | 60.5 | - | 60.0 | 50.3 |
Ro. Beasley
|
- | 18 | 26.6 | 8.3 | 2.3 | 1.3 | 0.7 | 0.1 | 1.1 | 5.5 | 6.2 | -45 | -3.8 | -4.3 | 37.4 | 40.0 | 77.8 | 0.6 | 67.6 | 50.5 |
J. Mani
|
- | 2 | 13.5 | 7.5 | 2.5 | 0.0 | 0.0 | 0.5 | 0.0 | 4.5 | 6.0 | 7 | 1.2 | 4.2 | 55.6 | 33.3 | 100.0 | 0.23 | 69.7 | 61.1 |
K. Milling
|
- | 23 | 28.8 | 7.1 | 4.4 | 1.3 | 0.7 | 0.1 | 1.2 | 5.0 | 7.3 | - | - | - | 40.5 | 30.8 | 88.2 | - | 62.2 | 49.1 |
Adebayo, Ade
|
- | 21 | 24.3 | 4.4 | 4.0 | 0.5 | 0.8 | 0.7 | 0.7 | 2.3 | 7.4 | - | - | - | 68.8 | 0.0 | 66.7 | - | 88.5 | 68.8 |
Leo Debruhl
|
- | 23 | 16.5 | 4.1 | 2.4 | 1.6 | 0.6 | 0.0 | 1.0 | 3.0 | 4.7 | - | - | - | 44.3 | 37.5 | 60.0 | - | 58.0 | 55.0 |
D. Henry
|
F | 2 | 8.5 | 3.0 | 2.0 | 0.5 | 0.0 | 0.0 | 1.0 | 3.5 | 1.0 | - | - | - | 42.9 | 0 | 0 | - | 42.9 | 42.9 |
S. Manu
|
- | 9 | 7.8 | 2.1 | 0.9 | 0.1 | 0.2 | 0.0 | 0.6 | 1.3 | 1.4 | - | - | - | 66.7 | 0.0 | 42.9 | - | 63.0 | 66.7 |
F. Borra
|
- | 11 | 9.7 | 1.6 | 1.9 | 0.5 | 0.0 | 0.4 | 1.0 | 0.8 | 2.6 | - | - | - | 55.6 | 0 | 50.0 | - | 56.1 | 55.6 |
N. Rocak
|
- | 23 | 8.6 | 1.5 | 1.5 | 0.2 | 0.1 | 0.2 | 0.5 | 0.9 | 2.1 | 83 | 5.5 | 7.4 | 40.0 | 0 | 66.7 | 2.23 | 63.9 | 40.0 |
Sione Lose
|
- | 21 | 12.3 | 1.1 | 1.6 | 0.8 | 0.4 | 0.1 | 0.5 | 1.5 | 2.1 | - | - | - | 18.8 | 11.8 | 50.0 | - | 35.5 | 21.9 |
P. Lambey
|
- | 3 | 1.7 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3 | 0.7 | - | - | - | 100.0 | 100.0 | 0 | - | 150.0 | 150.0 |
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