Texas Tech Lady Raiders
2026 Team Stats (31 games)
70.3
PPG
60.4
Opp
+9.9
Margin
43.8%
FG%
34.4%
3P%
76.6%
FT%
33.5
RPG
14.0
APG
15.9
TO
80.0
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 → | 1089 (#79) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +28.1 (#51) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.667 (#85) | AdjO 65.1 | AdjD 57.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.948 (#36) | 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 → | 0.924 (#38) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1284 (#26) | RD 116 | GP 31 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
B. Maupin
|
G | 31 | 33.0 | 15.7 | 3.5 | 2.5 | 1.5 | 0.3 | 3.2 | 12.0 | 8.2 | 99 | 4.0 | 5.1 | 41.0 | 35.1 | 83.9 | -0.09 | 56.3 | 50.0 |
S. Collins
|
G | 31 | 23.9 | 14.5 | 2.6 | 1.1 | 0.5 | 0.8 | 1.9 | 11.3 | 6.4 | 170 | 6.1 | 14.1 | 43.9 | 39.5 | 77.7 | 3.89 | 55.5 | 50.6 |
J. Bristow
|
G | 31 | 25.5 | 9.7 | 5.3 | 1.3 | 1.1 | 1.9 | 2.3 | 9.2 | 7.7 | 128 | 5.3 | 7.2 | 39.3 | 29.9 | 77.4 | 0.86 | 48.7 | 45.4 |
D. Fritz
|
G | 31 | 30.5 | 7.1 | 3.5 | 1.2 | 2.0 | 0.9 | 0.8 | 6.1 | 7.9 | 169 | 6.5 | 10.0 | 40.4 | 37.2 | 80.0 | 3.0 | 55.3 | 53.2 |
J. Malone
|
F | 31 | 15.4 | 6.8 | 3.4 | 0.7 | 0.5 | 0.2 | 1.5 | 4.2 | 5.9 | 25 | 1.0 | 3.0 | 59.5 | 0 | 80.0 | -0.45 | 65.5 | 59.5 |
S. Sanogo
|
F | 31 | 16.5 | 5.2 | 3.5 | 0.7 | 0.7 | 1.2 | 1.7 | 3.7 | 6.0 | 34 | 1.4 | 3.0 | 63.2 | 0 | 45.7 | 0.04 | 61.8 | 63.2 |
G. Nuñez
|
G | 31 | 30.4 | 5.0 | 4.5 | 4.6 | 1.9 | 0.1 | 2.3 | 4.9 | 9.0 | - | - | - | 40.1 | 22.8 | 62.5 | - | 46.7 | 44.4 |
S. Love
|
G | 27 | 17.7 | 4.1 | 2.2 | 1.7 | 1.0 | 0.1 | 1.1 | 3.5 | 4.5 | 22 | 1.2 | 2.4 | 40.0 | 30.2 | 76.7 | -2.25 | 51.8 | 46.8 |
A. Blacklock
|
G | 25 | 7.4 | 2.6 | 1.2 | 0.3 | 0.2 | 0.0 | 0.3 | 1.8 | 2.2 | 3 | 0.2 | 0.9 | 41.3 | 44.1 | 81.2 | 0.28 | 62.2 | 57.6 |
K. Martin
|
G | 4 | 6.8 | 1.2 | 1.0 | 0.5 | 0.2 | 0.2 | 0.5 | 1.0 | 1.8 | 108 | 7.2 | 15.4 | 25.0 | 25.0 | 100.0 | 3.49 | 51.2 | 37.5 |
M. Sanogo
|
F | 17 | 3.1 | 0.5 | 0.7 | 0.2 | 0.1 | 0.1 | 0.6 | 0.6 | 0.4 | -2 | -0.1 | -2.2 | 20.0 | 0 | 83.3 | -0.69 | 35.6 | 20.0 |
J. Nekolná
|
F | 11 | 2.6 | 0.4 | 0.3 | 0.2 | 0.2 | 0.1 | 0.3 | 0.5 | 0.4 | - | - | - | 40.0 | 0 | 0.0 | - | 34.0 | 40.0 |
Stephanie Okechukwu
|
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