Texas A&M Aggies
2026 Team Stats (24 games)
63.2
PPG
68.8
Opp
-5.6
Margin
37.8%
FG%
29.0%
3P%
67.6%
FT%
36.7
RPG
12.8
APG
17.2
TO
84.2
Pace
69.1
AdjO
55.4
AdjD
#57
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 → | 1048 (#149) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1197 (#69) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1000 (#190) | HCA +113 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +14.1 (#57) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +25.1 (#61) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.369 (#220) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.365 (#213) | NetEff -4.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.898 (#63) | AdjNet +18.9 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.906 (#63) | AdjNet +19.5 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.776 (#57) | AdjO 69.1 | AdjD 55.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.597 (#129) | AdjO 64.3 | AdjD 60.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.885 (#79) | 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 → | 0.848 (#87) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1146 (#101) | RD 130 | GP 24 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
N. Pryor
|
G | 24 | 33.1 | 15.7 | 3.8 | 6.6 | 3.4 | 0.2 | 3.4 | 13.1 | 13.2 | 78 | 4.6 | 5.3 | 41.1 | 34.0 | 62.8 | 4.36 | 48.8 | 43.6 |
F. Janneh
|
F | 24 | 26.4 | 11.5 | 8.8 | 1.1 | 1.3 | 0.5 | 2.5 | 9.2 | 11.5 | 27 | 1.6 | 2.2 | 43.0 | 34.1 | 82.6 | 0.22 | 54.7 | 49.3 |
J. Kent
|
G | 24 | 26.9 | 8.3 | 3.0 | 0.9 | 0.4 | 0.3 | 1.4 | 8.1 | 3.5 | 45 | 2.6 | 3.5 | 34.5 | 28.9 | 76.4 | 1.79 | 45.8 | 40.7 |
L. Ware
|
F | 23 | 24.3 | 6.7 | 5.3 | 0.9 | 0.8 | 1.3 | 1.4 | 5.1 | 8.4 | 4 | 0.3 | 0.4 | 49.2 | 0.0 | 65.0 | -0.02 | 53.7 | 49.2 |
L. Hylton
|
G | 24 | 22.8 | 5.8 | 1.8 | 1.6 | 0.8 | 0.1 | 2.3 | 6.0 | 1.8 | 20 | 1.2 | 1.9 | 37.1 | 31.7 | 54.5 | 0.69 | 45.2 | 44.1 |
S. Blow
|
G | 24 | 19.8 | 5.7 | 1.3 | 0.6 | 0.4 | 0.0 | 1.1 | 5.5 | 1.4 | -17 | -1.0 | -1.7 | 33.3 | 32.3 | 72.2 | -2.05 | 44.0 | 37.1 |
J. Webster
|
G | 24 | 16.1 | 4.2 | 2.5 | 0.3 | 1.1 | 0.2 | 0.9 | 5.0 | 2.6 | -19 | -1.1 | -2.3 | 25.2 | 22.9 | 63.3 | -0.66 | 38.2 | 34.5 |
E. Parker
|
C | 23 | 11.0 | 2.5 | 2.8 | 0.2 | 0.2 | 0.3 | 0.7 | 1.8 | 3.5 | 0 | 0.0 | 0.0 | 54.8 | 0 | 50.0 | 0.98 | 55.1 | 54.8 |
P. Steenbergen
|
G | 15 | 9.3 | 2.1 | 1.3 | 0.1 | 0.1 | 0.3 | 0.6 | 2.7 | 0.7 | 1 | 0.1 | 0.3 | 26.8 | 20.7 | 100.0 | 0.08 | 37.4 | 34.1 |
A. Franchini
|
F | 14 | 11.0 | 1.5 | 2.5 | 0.0 | 0.6 | 0.1 | 0.7 | 1.2 | 2.8 | -1 | -0.2 | -0.5 | 41.2 | 50.0 | 60.0 | 0.47 | 49.1 | 44.1 |
C. Spencer
|
G | 24 | 5.9 | 0.8 | 0.4 | 0.5 | 0.0 | 0.0 | 0.6 | 1.4 | -0.4 | 16 | 0.7 | 1.5 | 20.6 | 26.7 | 50.0 | 1.45 | 27.2 | 26.5 |
V. Saidu
|
F | 12 | 5.8 | 0.7 | 1.6 | 0.0 | 0.1 | 0.1 | 0.8 | 1.0 | 0.6 | 2 | 0.2 | 0.5 | 25.0 | 100.0 | 50.0 | -0.11 | 31.1 | 29.2 |
T. Kavoka
|
G | 8 | 3.0 | 0.0 | 0.1 | 0.1 | 0.1 | 0.0 | 1.0 | 0.5 | -1.1 | 27 | 3.9 | 16.5 | 0.0 | 0.0 | 0 | 1.25 | 0.0 | 0.0 |
Ibifaa Azogu
|
F | 1 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | -2.0 | -2 | -2.0 | -53.3 | 0.0 | 0.0 | 0 | -0.47 | 0.0 | 0.0 |
Gianna Gentry
|
G | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2 | -2.0 | -53.3 | 0 | 0 | 0 | -0.47 | 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