Tennessee Lady Volunteers
2025 Team Stats (28 games)
84.8
PPG
70.9
Opp
+13.9
Margin
44.0%
FG%
33.5%
3P%
67.3%
FT%
39.5
RPG
15.1
APG
14.0
TO
93.9
Pace
Model Outputs
2025-2026 latest available
No materialized model snapshot for 2025 yet, so this section is showing the latest available team-model rows.
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 → | 985 (#430) | HCA +113 elo |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +34.3 (#29) | HCA +2.8 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.740 (#43) | AdjO 74.9 | AdjD 63.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.955 (#30) | 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 → | 0.933 (#35) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1178 (#80) | RD 119 | GP 30 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
T. Cooper
|
G | 28 | 23.8 | 15.9 | 5.5 | 3.0 | 3.1 | 0.7 | 3.4 | 16.0 | 8.8 | 81 | 2.4 | 2.9 | 42.2 | 24.8 | 63.3 | 1.47 | 46.9 | 45.4 |
J. Spear
|
G | 27 | 24.8 | 12.9 | 2.8 | 1.9 | 0.8 | 0.1 | 1.1 | 9.4 | 8.1 | 73 | 2.3 | 2.7 | 42.7 | 39.6 | 87.0 | 1.53 | 60.7 | 55.5 |
Z. Spearman
|
F | 28 | 21.5 | 11.9 | 6.3 | 0.8 | 0.6 | 0.8 | 1.9 | 8.8 | 9.6 | 51 | 1.5 | 2.1 | 51.0 | 31.1 | 72.4 | 1.0 | 58.5 | 54.9 |
R. Whitehorn
|
G | 28 | 23.4 | 11.6 | 3.4 | 1.7 | 0.8 | 0.4 | 1.8 | 10.6 | 5.4 | 51 | 1.5 | 1.8 | 46.6 | 31.3 | 71.8 | 1.58 | 51.9 | 50.2 |
S. Spencer
|
G | 28 | 25.7 | 10.5 | 3.7 | 4.5 | 1.4 | 0.1 | 2.1 | 9.1 | 9.0 | 52 | 1.5 | 1.9 | 39.2 | 34.8 | 52.6 | 1.27 | 51.0 | 49.8 |
T. Darby
|
G | 27 | 15.3 | 5.9 | 1.7 | 0.6 | 0.5 | 0.1 | 0.2 | 5.9 | 2.8 | 36 | 1.0 | 2.9 | 36.1 | 34.1 | 0 | 0.33 | 50.3 | 50.3 |
K. Boyd
|
G | 27 | 17.4 | 4.1 | 1.6 | 1.2 | 1.1 | 0.1 | 0.6 | 2.8 | 4.7 | 26 | 0.8 | 1.8 | 53.9 | 26.7 | 70.3 | 0.33 | 60.7 | 56.6 |
S. Puckett
|
G | 28 | 13.9 | 4.0 | 2.9 | 0.4 | 0.5 | 0.2 | 0.7 | 3.7 | 3.6 | 74 | 2.0 | 4.6 | 40.8 | 33.3 | 81.8 | 0.83 | 51.5 | 49.5 |
J. Hollingshead
|
F | 28 | 15.7 | 3.5 | 3.2 | 0.5 | 0.3 | 0.4 | 0.8 | 2.6 | 4.5 | 97 | 2.6 | 7.2 | 47.9 | 30.0 | 64.9 | 0.81 | 54.3 | 50.0 |
A. Latham
|
F | 28 | 14.2 | 3.5 | 3.5 | 0.4 | 0.8 | 0.2 | 0.6 | 3.0 | 4.8 | 12 | 0.4 | 1.0 | 48.8 | 35.3 | 41.7 | 0.42 | 51.8 | 52.4 |
D. Wells
|
G | 6 | 3.7 | 2.0 | 0.8 | 0.2 | 0.2 | 0.0 | 0.5 | 1.3 | 1.3 | -2 | -0.2 | -3.2 | 50.0 | 57.1 | 0.0 | -1.27 | 67.6 | 75.0 |
E. Darby
|
G | 8 | 4.2 | 1.8 | 0.4 | 0.4 | 0.4 | 0.0 | 0.4 | 1.8 | 0.8 | 34 | 3.4 | 38.6 | 35.7 | 33.3 | 0 | -1.02 | 50.0 | 50.0 |
A. Strickland
|
G | 15 | 5.1 | 1.6 | 1.1 | 0.2 | 0.2 | 0.1 | 0.3 | 1.2 | 1.6 | 12 | 0.7 | 3.4 | 50.0 | 30.8 | 66.7 | -0.4 | 62.1 | 61.1 |
F. Ayodele
|
F | 10 | 4.7 | 0.1 | 1.6 | 0.1 | 0.6 | 0.1 | 0.3 | 0.2 | 2.0 | 24 | 1.7 | 13.5 | 0.0 | 0.0 | 25.0 | -0.66 | 13.3 | 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