Rice Owls
2026 Team Stats (32 games)
69.4
PPG
59.9
Opp
+9.5
Margin
39.8%
FG%
32.3%
3P%
81.7%
FT%
38.6
RPG
13.8
APG
13.7
TO
82.6
Pace
Model Outputs
2025-2026
Output is shown as model rating with league rank in parentheses when available.
| Model | Output | Notes |
|---|---|---|
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1130 (#39) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +23.7 (#68) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.699 (#68) | AdjO 67.6 | AdjD 58.3 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.914 (#59) | 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 → | 0.894 (#58) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1273 (#34) | RD 108 | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
D. Ennis
|
G | 32 | 31.5 | 12.8 | 3.3 | 1.5 | 1.5 | 0.3 | 1.0 | 11.8 | 6.6 | 107 | 4.7 | 5.9 | 39.0 | 33.9 | 88.6 | 0.2 | 51.8 | 49.3 |
V. Flores
|
G | 30 | 31.0 | 12.3 | 3.2 | 2.7 | 1.7 | 0.2 | 2.8 | 9.9 | 7.4 | 148 | 6.7 | 8.6 | 34.5 | 30.5 | 88.6 | 5.8 | 51.5 | 41.2 |
S. Hayes
|
C | 32 | 28.1 | 12.0 | 5.9 | 1.2 | 0.6 | 0.5 | 1.5 | 9.2 | 9.5 | 134 | 5.8 | 8.9 | 50.8 | 50.0 | 79.8 | 2.16 | 56.5 | 51.2 |
A. Alexis
|
G | 32 | 31.3 | 10.0 | 5.8 | 1.5 | 1.1 | 0.4 | 1.4 | 9.8 | 7.6 | 68 | 3.1 | 4.0 | 35.5 | 31.7 | 89.2 | -0.63 | 46.7 | 41.7 |
H. Adams
|
G | 32 | 32.9 | 8.4 | 10.8 | 3.4 | 1.0 | 1.6 | 2.7 | 8.2 | 14.2 | 70 | 3.2 | 3.7 | 41.8 | 14.3 | 81.0 | -0.73 | 46.4 | 42.0 |
L. Battiston
|
G | 32 | 20.8 | 7.2 | 1.3 | 2.5 | 0.6 | 0.1 | 2.2 | 6.4 | 3.1 | 46 | 2.1 | 4.8 | 38.0 | 33.3 | 86.8 | 1.08 | 51.9 | 48.0 |
M. Guinn
|
G | 12 | 6.8 | 3.2 | 1.0 | 0.5 | 0.3 | 0.1 | 0.7 | 2.6 | 1.9 | -31 | -3.1 | -26.5 | 41.9 | 45.5 | 60.0 | -4.53 | 58.7 | 58.1 |
J. Blackmon
|
G | 32 | 11.0 | 3.1 | 1.5 | 0.4 | 0.2 | 0.0 | 0.6 | 2.8 | 1.8 | 23 | 1.0 | 3.4 | 36.3 | 25.0 | 66.7 | -0.28 | 45.8 | 40.1 |
L. Conley
|
G | 3 | 1.3 | 2.0 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.7 | 1.7 | -5 | -1.7 | -40.5 | 100.0 | 100.0 | 0 | -0.82 | 150.0 | 150.0 |
M. Hazelton
|
C | 32 | 8.0 | 2.0 | 1.4 | 0.1 | 0.3 | 0.3 | 0.4 | 2.0 | 1.8 | -27 | -1.2 | -4.7 | 42.2 | 0 | 47.8 | -2.77 | 43.8 | 42.2 |
K. Clifton
|
G | 16 | 8.1 | 1.4 | 1.5 | 0.4 | 0.6 | 0.3 | 0.9 | 1.2 | 2.1 | 2 | 0.4 | 2.0 | 42.1 | 28.6 | 57.1 | 0.75 | 49.8 | 47.4 |
J. Twiehaus
|
G | 7 | 4.6 | 1.1 | 0.3 | 0.3 | 0.1 | 0.0 | 0.1 | 2.3 | -0.6 | -15 | -1.9 | -17.6 | 25.0 | 0.0 | 0.0 | -0.82 | 24.3 | 25.0 |
P. Rickard
|
G | 7 | 1.9 | 0.0 | 0.0 | 0.3 | 0.0 | 0.0 | 0.1 | 0.1 | 0.0 | 5 | 1.0 | 18.5 | 0.0 | 0.0 | 0 | 0.72 | 0.0 | 0.0 |
Skyla Tuthill
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
Hanna Hilberth
|
C | 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