Colorado State
2026 Team Stats (32 games)
75.2
PPG
71.1
Opp
+4.1
Margin
47.9%
FG%
38.0%
3P%
76.9%
FT%
32.6
RPG
15.9
APG
11.8
TO
72.7
Pace
76.6
AdjO
68.7
AdjD
#88
Rank
Model Outputs
2025-2026
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 → | 1101 (#95) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1085 (#105) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1023 (#142) | HCA +109 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +7.7 (#88) | HCA +2.2 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +20.9 (#75) | HCA +2.5 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.626 (#98) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.994 (#6) | NetEff +44.4 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.762 (#88) | AdjNet +10.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.764 (#90) | AdjNet +10.2 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.672 (#88) | AdjO 76.6 | AdjD 68.7 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.607 (#110) | AdjO 73.0 | AdjD 68.2 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.836 (#93) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. More → | 0.802 (#92) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1121 (#121) | RD 115 | GP 32 |
2026 Schedule & Results
2026 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Brandon Rechsteiner
|
G | 32 | 27.8 | 11.9 | 2.2 | 2.4 | 0.8 | 0.1 | 1.7 | 9.2 | 6.5 | 60 | 2.7 | 4.3 | 44.7 | 40.0 | 80.9 | 0.74 | 60.6 | 58.4 |
K. Jorgensen
|
F | 26 | 25.2 | 11.2 | 4.3 | 2.2 | 0.6 | 0.5 | 1.5 | 7.6 | 9.7 | 118 | 6.6 | 12.1 | 50.5 | 39.6 | 81.2 | 1.11 | 64.1 | 60.1 |
C. Booth
|
F | 32 | 24.5 | 10.9 | 5.6 | 0.6 | 0.4 | 1.1 | 1.1 | 6.6 | 10.9 | 18 | 0.8 | 1.6 | 52.8 | 40.5 | 82.9 | 0.19 | 67.1 | 60.8 |
J. Pascarelli
|
- | 25 | 26.3 | 9.6 | 2.8 | 1.5 | 0.6 | 0.0 | 0.8 | 7.8 | 6.0 | 22 | 1.0 | 1.5 | 43.1 | 37.8 | 87.0 | -0.48 | 58.3 | 56.2 |
J. Muniz
|
G | 32 | 30.5 | 9.4 | 3.9 | 4.9 | 0.9 | 0.2 | 1.4 | 7.1 | 10.8 | 88 | 4.0 | 6.1 | 47.3 | 36.7 | 69.9 | 0.63 | 58.3 | 55.3 |
Jase Butler
|
- | 32 | 26.2 | 9.3 | 3.2 | 1.9 | 0.6 | 0.1 | 1.1 | 5.8 | 8.1 | 40 | 1.8 | 3.6 | 44.1 | 40.6 | 81.1 | 0.12 | 63.2 | 55.6 |
R. Mbemba
|
F | 21 | 17.5 | 8.1 | 3.7 | 0.9 | 0.4 | 0.2 | 1.4 | 4.2 | 7.6 | -26 | -2.9 | -6.2 | 59.6 | 50.0 | 72.0 | -0.4 | 68.0 | 62.4 |
A. Kiudulas
|
F | 32 | 14.8 | 6.1 | 2.8 | 0.8 | 0.5 | 0.0 | 1.1 | 3.5 | 5.7 | 40 | 1.9 | 5.2 | 55.0 | 45.2 | 69.0 | 0.45 | 65.6 | 61.3 |
Jojo Mciver
|
- | 31 | 12.6 | 2.7 | 1.9 | 1.1 | 0.4 | 0.0 | 0.9 | 2.2 | 3.1 | 24 | 1.1 | 4.5 | 39.7 | 16.7 | 74.3 | -0.25 | 51.0 | 43.4 |
N. Djapa
|
- | 17 | 9.2 | 2.5 | 1.8 | 0.7 | 0.4 | 0.1 | 1.0 | 1.5 | 3.0 | 10 | 0.6 | 2.6 | 65.4 | 25.0 | 50.0 | 0.1 | 65.1 | 67.3 |
J. Mekonnen
|
- | 10 | 5.0 | 2.1 | 1.4 | 0.4 | 0.4 | 0.0 | 0.4 | 1.9 | 2.0 | -5 | -0.5 | -5.6 | 26.3 | 0.0 | 91.7 | -0.14 | 43.2 | 26.3 |
D. Slater
|
- | 22 | 6.6 | 1.5 | 0.6 | 0.1 | 0.1 | 0.1 | 0.2 | 1.2 | 1.0 | 2 | 0.1 | 1.5 | 40.7 | 11.1 | 90.9 | -0.3 | 51.8 | 42.6 |
C. Dortch
|
- | 4 | 3.8 | 0.5 | 0.8 | 0.5 | 0.0 | 0.0 | 0.2 | 0.5 | 1.0 | 13 | 2.6 | 88.4 | 50.0 | 0 | 0 | -0.11 | 50.0 | 50.0 |
Docker Tedeschi
|
F | 0 | - | 0.0 | 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