San Diego Toreros
2026 Team Stats (30 games)
57.4
PPG
65.3
Opp
-7.9
Margin
35.8%
FG%
26.1%
3P%
69.8%
FT%
38.8
RPG
9.9
APG
17.4
TO
82.7
Pace
56.2
AdjO
64.3
AdjD
#261
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 → | 924 (#233) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 860 (#268) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 917 (#510) | HCA +113 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -8.3 (#260) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +5.8 (#248) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.160 (#297) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.169 (#278) | NetEff -11.5 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.180 (#264) | AdjNet -13.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.173 (#265) | AdjNet -13.4 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.323 (#261) | AdjO 56.2 | AdjD 64.3 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.394 (#464) | AdjO 57.9 | AdjD 62.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.548 (#273) | 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 → | 0.510 (#273) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 909 (#370) | RD 150 | GP 30 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
K. Ray
|
G | 25 | 32.4 | 16.4 | 5.7 | 2.7 | 1.5 | 0.2 | 5.3 | 16.2 | 4.9 | -63 | -3.3 | -4.9 | 36.3 | 29.7 | 89.5 | -0.75 | 45.8 | 40.0 |
O. Owens
|
G | 29 | 31.7 | 11.7 | 6.0 | 2.7 | 1.6 | 0.2 | 3.4 | 12.2 | 6.5 | -60 | -2.4 | -3.3 | 33.8 | 25.6 | 71.7 | 1.03 | 42.9 | 38.5 |
H. Rhodes
|
G | 26 | 31.3 | 11.3 | 3.6 | 1.8 | 1.2 | 0.6 | 2.0 | 11.7 | 4.9 | -88 | -4.0 | -5.2 | 39.0 | 29.3 | 66.1 | 0.21 | 44.4 | 41.8 |
E. Ruse
|
F | 30 | 19.1 | 5.5 | 5.5 | 0.5 | 0.7 | 0.7 | 1.3 | 4.2 | 7.4 | -22 | -0.9 | -1.8 | 46.5 | 14.3 | 61.8 | 1.64 | 51.7 | 46.9 |
H. Holley
|
F | 29 | 18.0 | 3.2 | 4.0 | 0.5 | 0.7 | 0.5 | 1.0 | 3.1 | 4.8 | -54 | -2.2 | -5.1 | 41.1 | 18.8 | 58.6 | -2.08 | 45.7 | 42.8 |
D. Moore
|
F | 27 | 14.0 | 3.1 | 3.3 | 0.4 | 0.4 | 0.4 | 1.7 | 3.6 | 2.2 | -97 | -4.6 | -13.4 | 33.7 | 18.8 | 77.8 | -2.06 | 39.2 | 35.2 |
A. Williams
|
C | 30 | 11.1 | 2.9 | 4.1 | 0.5 | 0.5 | 0.6 | 0.9 | 1.9 | 5.8 | 157 | 6.0 | 18.5 | 33.9 | 0 | 64.5 | 2.74 | 48.6 | 33.9 |
L. Amor
|
G | 29 | 24.3 | 2.6 | 0.8 | 0.9 | 0.8 | 0.3 | 0.8 | 3.5 | 1.1 | -88 | -3.7 | -7.2 | 25.7 | 24.1 | 50.0 | -4.97 | 36.0 | 35.6 |
J. Ajayi
|
G | 21 | 11.4 | 2.5 | 1.0 | 0.3 | 0.5 | 0.1 | 0.8 | 3.3 | 0.3 | 32 | 2.3 | 10.5 | 27.5 | 24.4 | 60.0 | 0.18 | 36.5 | 35.5 |
J. Rhodes
|
G | 26 | 12.6 | 2.1 | 1.4 | 0.3 | 0.4 | 0.1 | 0.7 | 2.0 | 1.6 | -15 | -0.7 | -2.0 | 35.8 | 30.0 | 57.1 | 1.2 | 46.5 | 44.3 |
M. Tharpe
|
F | 21 | 12.9 | 2.1 | 1.8 | 0.4 | 0.6 | 0.1 | 0.7 | 3.3 | 0.9 | -32 | -1.9 | -5.1 | 25.7 | 12.5 | 54.5 | -0.67 | 29.4 | 27.1 |
Y. Von Seipler
|
G | 15 | 7.0 | 1.6 | 1.1 | 0.3 | 0.3 | 0.1 | 0.3 | 1.1 | 1.9 | 6 | 0.5 | 2.2 | 50.0 | 50.0 | 50.0 | -2.07 | 61.5 | 62.5 |
L. McCall
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
E. Carr
|
C | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | -1.0 | 12 | 6.0 | 347.0 | 0 | 0 | 0 | -0.06 | 0 | 0 |
Ryanne Bahnsen-Price
|
F | 1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 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