South Dakota Coyotes
2022 Team Stats (7 games)
60.0
PPG
59.6
Opp
+0.4
Margin
41.1%
FG%
37.7%
3P%
69.6%
FT%
29.7
RPG
12.4
APG
11.0
TO
70.6
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 → | 1174 (#77) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1187 (#81) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +29.8 (#82) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.845 (#58) | - |
2022 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2021-11-12 | vs | South Carolina Gamecocks | L | 41 - 72 |
| 2021-11-25 | @ | Northwestern Wildcats | L | 57 - 73 |
| 2022-03-07 | vs | Kansas City Roos | W | 81 - 67 |
| 2022-03-08 | @ | South Dakota State Jackrabbits | W | 56 - 45 |
| 2022-03-18 | @ | Ole Miss Rebels | W | 75 - 61 |
| 2022-03-20 | @ | Baylor Bears | W | 61 - 47 |
| 2022-03-26 | @ | Michigan Wolverines | L | 49 - 52 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
C. Lamb
|
G | 7 | 36.6 | 18.0 | 3.4 | 2.6 | 1.3 | 0.1 | 1.9 | 13.4 | 10.1 | - | - | - | 47.9 | 52.8 | 89.5 | 0.38 | 61.5 | 58.0 |
H. Sjerven
|
C | 7 | 29.0 | 16.3 | 6.4 | 0.6 | 1.7 | 1.0 | 1.9 | 11.9 | 12.3 | - | - | - | 50.6 | 44.4 | 68.4 | 0.83 | 57.2 | 53.0 |
L. Korngable
|
G | 7 | 36.3 | 11.1 | 2.0 | 4.4 | 0.9 | 0.1 | 1.9 | 9.3 | 7.4 | - | - | - | 44.6 | 50.0 | 70.6 | 0.95 | 53.8 | 50.8 |
M. Krull
|
G | 7 | 32.0 | 4.7 | 4.4 | 1.9 | 1.1 | 0.0 | 1.6 | 5.4 | 5.1 | - | - | - | 26.3 | 25.0 | 55.6 | 0.68 | 35.9 | 30.3 |
K. Watson
|
G | 7 | 30.7 | 4.3 | 2.9 | 2.1 | 0.7 | 0.4 | 1.9 | 6.6 | 2.0 | 112 | 5.1 | 28.6 | 26.1 | 15.4 | 50.0 | 1.03 | 31.4 | 30.4 |
G. Larkins
|
G | 7 | 13.7 | 3.1 | 2.0 | 0.3 | 0.3 | 0.0 | 1.0 | 3.9 | 0.9 | 208 | 6.5 | 26.5 | 33.3 | 50.0 | 50.0 | 3.23 | 39.5 | 38.9 |
M. Guebert
|
G | 6 | 4.8 | 1.3 | 0.5 | 0.3 | 0.0 | 0.0 | 0.2 | 1.3 | 0.7 | - | - | - | 37.5 | 33.3 | 0 | 1.9 | 50.0 | 50.0 |
N. Mazurek
|
F | 2 | 10.0 | 1.0 | 1.5 | 0.5 | 0.5 | 0.0 | 0.0 | 1.0 | 2.5 | 88 | 4.4 | 22.5 | 50.0 | 0 | 0 | 1.07 | 50.0 | 50.0 |
A. Peplowski
|
F | 6 | 9.3 | 0.7 | 1.7 | 0.0 | 0.0 | 0.0 | 0.5 | 0.5 | 1.3 | - | - | - | 66.7 | 0 | 0 | 2.2 | 66.7 | 66.7 |
J. Ugofsky
|
F | 7 | 6.1 | 0.4 | 0.9 | 0.1 | 0.1 | 0.3 | 0.1 | 0.4 | 1.3 | - | - | - | 0.0 | 0.0 | 75.0 | 2.09 | 31.5 | 0.0 |
A. Williston
|
C | 1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 13 | 13.0 | 52.0 | 0 | 0 | 0 | -0.52 | 0 | 0 |
R. Sankey
|
F | 3 | 1.0 | 0.0 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7 | -0.3 | - | - | - | 0.0 | 0.0 | 0 | -0.77 | 0.0 | 0.0 |
M. Hansen
|
F | 1 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | -33 | -11.0 | -125.9 | 0.0 | 0 | 0 | -0.55 | 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