Cal Poly Mustangs
2022 Team Stats (5 games)
61.2
PPG
76.4
Opp
-15.2
Margin
38.6%
FG%
35.1%
3P%
74.3%
FT%
32.2
RPG
12.2
APG
16.0
TO
80.5
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 → | 767 (#388) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 849 (#373) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +3.9 (#325) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.017 (#389) | - |
2022 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2021-11-23 | vs | Louisville Cardinals | L | 32 - 72 |
| 2021-12-13 | @ | Northern Arizona Lumberjacks | L | 73 - 88 |
| 2022-02-22 | @ | Cal State Bakersfield Roadrunners | L | 71 - 85 |
| 2022-03-03 | @ | UC Irvine Anteaters | L | 66 - 67 |
| 2022-03-08 | @ | Cal State Fullerton Titans | L | 64 - 70 |
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. Nielacna
|
F | 5 | 18.6 | 12.8 | 4.0 | 0.2 | 0.4 | 0.0 | 2.0 | 10.6 | 4.8 | - | - | - | 49.1 | 33.3 | 64.3 | 0.29 | 54.1 | 51.9 |
M. Vick
|
G | 5 | 32.6 | 10.8 | 3.0 | 3.6 | 1.6 | 0.0 | 3.2 | 10.2 | 5.6 | - | - | - | 41.2 | 20.0 | 91.7 | 0.03 | 48.0 | 42.2 |
M. Willett
|
G | 5 | 32.0 | 10.0 | 2.8 | 2.0 | 0.4 | 0.0 | 1.8 | 8.4 | 5.0 | - | - | - | 40.5 | 43.5 | 75.0 | 0.49 | 54.9 | 52.4 |
H. Scanlan
|
F | 5 | 19.8 | 6.8 | 4.4 | 0.8 | 0.0 | 0.6 | 1.0 | 4.6 | 7.0 | - | - | - | 56.5 | 0 | 80.0 | 0.04 | 62.0 | 56.5 |
J. Dickson
|
G | 5 | 14.0 | 5.4 | 2.2 | 0.6 | 0.8 | 0.2 | 0.6 | 5.0 | 3.6 | -96 | -6.4 | -36.5 | 36.0 | 38.9 | 100.0 | 0.37 | 52.2 | 50.0 |
S. Dumitrescu
|
G | 5 | 13.2 | 4.6 | 3.0 | 0.8 | 0.2 | 0.0 | 1.4 | 3.8 | 3.4 | - | - | - | 36.8 | 0 | 69.2 | 0.45 | 46.5 | 36.8 |
K. Brown
|
F | 4 | 13.5 | 4.0 | 4.2 | 0.5 | 0.8 | 0.8 | 1.2 | 3.8 | 5.2 | -46 | -2.2 | -28.8 | 46.7 | 0 | 40.0 | 0.27 | 46.5 | 46.7 |
J. Anousinh
|
G | 5 | 21.0 | 3.4 | 1.6 | 2.2 | 0.2 | 0.0 | 1.2 | 4.0 | 2.2 | - | - | - | 25.0 | 20.0 | 100.0 | 0.14 | 37.5 | 27.5 |
A. Shah
|
G | 5 | 7.8 | 1.8 | 0.2 | 0.4 | 0.0 | 0.0 | 0.8 | 2.4 | -0.8 | -150 | -9.4 | -48.4 | 25.0 | 27.3 | 0 | 0.04 | 37.5 | 37.5 |
S. Bourland
|
G | 5 | 20.0 | 1.8 | 1.6 | 0.8 | 0.6 | 0.0 | 1.4 | 4.0 | -0.6 | -170 | -9.4 | -49.7 | 15.0 | 40.0 | 50.0 | -0.03 | 21.6 | 20.0 |
Z. Stachowski
|
PF | 3 | 6.3 | 0.7 | 1.3 | 0.0 | 0.3 | 0.0 | 0.3 | 2.3 | -0.3 | - | - | - | 14.3 | 0 | 0 | 0.13 | 14.3 | 14.3 |
L. Svetich
|
G | 2 | 13.0 | 0.5 | 1.0 | 1.0 | 1.5 | 0.0 | 0.5 | 1.0 | 2.5 | -69 | -8.6 | -63.2 | 0.0 | 0.0 | 50.0 | -0.03 | 17.4 | 0.0 |
F. Bergstrom
|
F | 3 | 2.0 | 0.0 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3 | 0.0 | - | - | - | 0.0 | 0 | 0 | -0.24 | 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