UC Davis
2022 Team Stats (3 games)
60.3
PPG
66.2
Opp
+1.2
Margin
36.8%
FG%
25.0%
3P%
71.9%
FT%
35.0
RPG
9.0
APG
11.3
TO
76.7
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 → | 1212 (#122) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1171 (#176) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +21.2 (#205) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.765 (#14) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.231 (#209) | NetEff -9.8 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.318 (#85) | AdjNet -6.6 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.314 (#86) | AdjNet -6.8 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A. Sow
|
F | 1 | 36.0 | 17.0 | 11.0 | 0.0 | 0.0 | 2.0 | 3.0 | 0.0 | 27.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
C. Fuller
|
- | 3 | 32.3 | 15.0 | 5.3 | 1.7 | 1.0 | 1.0 | 2.7 | 11.3 | 10.0 | - | - | - | 41.2 | 21.4 | 70.0 | - | 52.6 | 45.6 |
E. Pepper
|
- | 23 | 33.7 | 14.8 | 5.2 | 1.6 | 1.6 | 0.3 | 2.1 | 2.3 | 19.0 | - | - | - | 35.8 | 26.1 | 73.3 | - | 285.2 | 41.5 |
E. Manjon
|
- | 3 | 33.3 | 10.0 | 1.3 | 3.3 | 0.7 | 0.7 | 2.0 | 13.3 | 0.7 | - | - | - | 22.5 | 0.0 | 80.0 | - | 32.2 | 22.5 |
C. Anigwe
|
- | 23 | 22.3 | 9.8 | 5.7 | 0.7 | 0.8 | 1.0 | 1.5 | 1.1 | 15.4 | - | - | - | 61.5 | 50.0 | 77.8 | - | 375.5 | 63.5 |
K. Milling
|
- | 23 | 28.4 | 7.3 | 3.4 | 1.3 | 1.0 | 0.1 | 1.0 | 1.0 | 11.0 | - | - | - | 45.8 | 30.0 | 0.0 | - | 343.7 | 52.1 |
C. Ba
|
G | 4 | 17.5 | 5.0 | 0.5 | 0.8 | 0.2 | 0.0 | 0.0 | 3.0 | 3.5 | - | - | - | 50.0 | 55.6 | 0 | - | 83.3 | 70.8 |
Adebayo, Ade
|
- | 23 | 17.9 | 2.1 | 2.2 | 0.9 | 0.6 | 0.3 | 0.9 | 0.1 | 5.1 | - | - | - | 50.0 | 0.0 | 0 | - | 1200.0 | 50.0 |
S. Touré
|
G | 1 | 4.0 | 2.0 | 4.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 6.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
R. Idehen
|
F | 1 | 11.0 | 2.0 | 4.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 7.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
A. Murphy
|
F | 7 | 9.0 | 1.6 | 3.0 | 0.1 | 0.1 | 0.1 | 0.1 | 0.6 | 4.3 | - | - | - | 25.0 | 0 | 0.0 | - | 112.7 | 25.0 |
Leo Debruhl
|
- | 21 | 7.0 | 1.3 | 1.1 | 0.9 | 0.2 | 0.1 | 0.8 | 0.2 | 2.6 | - | - | - | 40.0 | 33.3 | 66.7 | - | 221.5 | 50.0 |
F. Borra
|
- | 18 | 7.1 | 1.1 | 1.0 | 0.1 | 0.1 | 0.3 | 0.8 | 0.0 | 1.7 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
B.J. Shaw
|
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 |
C. McGill
|
F | 2 | 8.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.5 | 0.0 | 0.0 | 1.5 | - | - | - | 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