UConn Huskies
2025 Team Stats (38 games)
81.6
PPG
52.2
Opp
+29.5
Margin
50.9%
FG%
38.3%
3P%
76.4%
FT%
37.0
RPG
21.0
APG
10.7
TO
78.8
Pace
89.1
AdjO
45.1
AdjD
#1
Rank
Model Outputs
2024-2025
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 → | 1610 (#1) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1595 (#2) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +45.2 (#1) | HCA +2.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.994 (#1) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.994 (#1) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 1.000 (#1) | AdjNet +66.9 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 1.000 (#1) | AdjNet +68.1 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.982 (#1) | AdjO 89.1 | AdjD 45.1 |
2025 Schedule & Results
2025 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
P. Bueckers
|
- | 38 | 30.2 | 19.9 | 4.4 | 4.6 | 2.1 | 0.8 | 1.3 | 14.1 | 16.4 | 235 | 6.2 | 6.4 | 53.4 | 41.9 | 88.9 | 2.1 | 63.8 | 60.0 |
S. Strong
|
F | 40 | 28.7 | 16.4 | 8.9 | 3.5 | 2.3 | 1.6 | 1.6 | 11.6 | 19.7 | 254 | 6.3 | 7.3 | 58.6 | 38.8 | 74.0 | 2.7 | 66.2 | 65.0 |
A. Fudd
|
G | 34 | 26.4 | 13.6 | 2.0 | 1.8 | 1.4 | 0.3 | 1.0 | 10.9 | 7.1 | 278 | 7.5 | 10.3 | 47.4 | 43.6 | 91.7 | 2.1 | 60.0 | 58.1 |
A. Shade
|
G | 40 | 22.4 | 7.7 | 2.7 | 1.3 | 1.4 | 0.1 | 0.6 | 6.2 | 6.5 | 181 | 4.5 | 6.8 | 48.0 | 41.1 | 71.4 | 1.31 | 59.4 | 58.6 |
K. Chen
|
- | 40 | 23.4 | 6.9 | 1.8 | 3.4 | 1.1 | 0.0 | 1.6 | 5.2 | 6.4 | 165 | 3.9 | 5.8 | 51.4 | 35.4 | 84.2 | 1.3 | 61.1 | 58.3 |
KK Arnold
|
G | 40 | 21.2 | 5.5 | 2.4 | 2.8 | 1.5 | 0.1 | 1.2 | 4.3 | 6.7 | 151 | 3.8 | 5.5 | 47.4 | 21.3 | 71.0 | 0.84 | 54.4 | 50.3 |
J. El Alfy
|
C | 40 | 16.0 | 5.0 | 5.1 | 1.0 | 0.6 | 0.6 | 1.2 | 4.1 | 6.9 | 117 | 2.9 | 5.8 | 52.4 | 25.0 | 50.9 | 0.91 | 53.4 | 52.7 |
A. Griffin
|
F | 16 | 11.2 | 4.4 | 3.4 | 0.9 | 0.5 | 0.4 | 0.4 | 2.6 | 6.5 | 36 | 1.9 | 9.3 | 59.5 | 0.0 | 83.3 | 0.07 | 66.6 | 59.5 |
I. Brady
|
F | 32 | 15.8 | 3.6 | 2.8 | 1.7 | 0.6 | 0.4 | 0.9 | 2.9 | 5.2 | 83 | 2.6 | 6.0 | 50.5 | 27.3 | 68.0 | 0.75 | 54.8 | 52.2 |
A. Ziebell
|
G | 33 | 8.2 | 2.8 | 0.5 | 0.3 | 0.2 | 0.1 | 0.2 | 2.5 | 1.2 | 9 | 0.3 | 1.5 | 39.5 | 34.4 | 50.0 | -0.16 | 53.3 | 53.1 |
M. Cheli
|
G | 24 | 13.3 | 2.5 | 2.4 | 1.2 | 0.4 | 0.0 | 0.6 | 2.7 | 3.3 | 10 | 0.4 | 1.1 | 39.1 | 37.0 | 100.0 | -0.07 | 47.3 | 46.9 |
Q. Samuels
|
G | 33 | 5.5 | 1.3 | 0.8 | 0.1 | 0.2 | 0.1 | 0.5 | 1.5 | 0.5 | 5 | 0.2 | 1.2 | 32.7 | 24.0 | 71.4 | -0.34 | 41.3 | 38.8 |
C. Ducharme
|
G | 9 | 3.7 | 1.2 | 0.7 | 0.2 | 0.1 | 0.0 | 0.4 | 1.9 | -0.1 | 27 | 2.2 | 36.2 | 29.4 | 14.3 | 0 | -1.2 | 32.4 | 32.4 |
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