Colorado State Rams
2023 Team Stats (4 games)
64.8
PPG
62.2
Opp
+2.6
Margin
42.9%
FG%
33.8%
3P%
77.2%
FT%
26.3
RPG
12.0
APG
7.8
TO
68.8
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 → | 1171 (#78) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1255 (#58) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +27.8 (#89) | HCA +2.6 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.879 (#46) | - |
2023 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2022-11-26 | vs | Auburn Tigers | L | 73 - 74 |
| 2023-01-16 | vs | San Diego State Aztecs | W | 71 - 58 |
| 2023-03-06 | vs | Boise State Broncos | W | 59 - 52 |
| 2023-03-07 | @ | Wyoming Cowgirls | L | 56 - 65 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
M. Hofschild
|
G | 4 | 39.2 | 20.5 | 4.8 | 7.2 | 1.8 | 0.0 | 2.2 | 13.2 | 18.8 | - | - | - | 56.6 | 25.0 | 76.9 | - | 63.6 | 58.5 |
D. Thurman
|
G | 4 | 34.5 | 11.8 | 4.2 | 1.5 | 1.8 | 0.0 | 1.5 | 12.0 | 5.8 | - | - | - | 33.3 | 25.0 | 90.9 | - | 44.5 | 38.5 |
S. Mech
|
G | 4 | 34.5 | 9.0 | 2.8 | 0.8 | 0.8 | 1.2 | 0.2 | 6.5 | 7.8 | - | - | - | 53.8 | 60.0 | 66.7 | - | 65.9 | 65.4 |
C. Crocker
|
G | 4 | 30.5 | 7.8 | 4.5 | 1.2 | 0.8 | 0.0 | 1.5 | 7.8 | 5.0 | - | - | - | 35.5 | 40.0 | 70.0 | - | 43.8 | 38.7 |
M. Boyd
|
G | 4 | 14.2 | 6.5 | 1.0 | 0.2 | 0.2 | 0.0 | 0.2 | 5.8 | 2.0 | - | - | - | 39.1 | 33.3 | 66.7 | - | 53.5 | 52.2 |
K. Kinzer
|
F | 4 | 16.0 | 4.5 | 2.2 | 0.5 | 0.5 | 1.0 | 0.5 | 4.8 | 3.5 | - | - | - | 31.6 | 37.5 | 0 | - | 47.4 | 47.4 |
C. Clark
|
F | 4 | 16.8 | 3.2 | 3.8 | 0.2 | 0.2 | 1.2 | 1.0 | 2.8 | 5.0 | - | - | - | 45.5 | 0.0 | 75.0 | - | 50.9 | 45.5 |
J. Vaz
|
F | 2 | 16.0 | 2.0 | 0.5 | 0.5 | 0.5 | 0.0 | 0.0 | 3.0 | 0.5 | - | - | - | 33.3 | 0 | 0 | - | 33.3 | 33.3 |
M. Leimane
|
G | 1 | 1.0 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | - | - | - | 100.0 | 0 | 0 | - | 100.0 | 100.0 |
P. Farkas
|
G | 2 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
H. Ronsiek
|
G | 4 | 5.2 | 0.0 | 1.0 | 0.0 | 0.5 | 0.2 | 0.5 | 0.2 | 1.0 | - | - | - | 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