Pacific Tigers
2026 Team Stats (27 games)
65.7
PPG
69.1
Opp
-3.4
Margin
39.8%
FG%
31.9%
3P%
76.7%
FT%
36.0
RPG
14.3
APG
16.4
TO
82.0
Pace
64.5
AdjO
67.2
AdjD
#195
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 → | 807 (#300) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 928 (#227) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 906 (#522) | HCA +113 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | -3.2 (#202) | HCA +2.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +9.4 (#207) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.277 (#248) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.218 (#258) | NetEff -10.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.388 (#196) | AdjNet -4.0 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.386 (#195) | AdjNet -4.0 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More → | 0.439 (#195) | AdjO 64.5 | AdjD 67.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.458 (#324) | AdjO 64.3 | AdjD 66.1 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.628 (#231) | 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 → | 0.584 (#233) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 919 (#354) | RD 150 | GP 27 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
W. Bartholomew
|
F | 26 | 24.5 | 13.6 | 5.2 | 1.0 | 0.5 | 0.1 | 2.0 | 11.9 | 6.5 | -83 | -3.8 | -5.6 | 44.3 | 25.0 | 79.8 | 2.47 | 50.2 | 44.5 |
S. Ward
|
G | 27 | 27.5 | 11.1 | 7.0 | 1.7 | 1.1 | 1.0 | 2.0 | 7.1 | 12.8 | -132 | -6.0 | -8.0 | 52.1 | 41.4 | 81.9 | -3.67 | 64.5 | 58.3 |
D. Nestorov
|
G | 27 | 29.7 | 10.5 | 2.6 | 5.0 | 1.7 | 0.0 | 3.0 | 10.5 | 6.3 | -103 | -4.7 | -6.3 | 37.7 | 30.3 | 83.0 | -0.43 | 46.4 | 43.0 |
S. Mindermann
|
G | 27 | 23.0 | 9.3 | 1.9 | 1.0 | 0.7 | 0.0 | 1.3 | 7.6 | 4.0 | -56 | -2.5 | -4.8 | 40.2 | 37.3 | 84.8 | 1.99 | 57.4 | 54.7 |
N. Lowery
|
G | 27 | 21.7 | 5.7 | 3.5 | 1.2 | 0.8 | 0.0 | 1.5 | 6.6 | 3.2 | -102 | -4.6 | -8.8 | 31.6 | 27.5 | 71.4 | -3.97 | 41.6 | 39.5 |
M. Radocaj
|
G | 24 | 18.7 | 4.1 | 4.1 | 1.1 | 0.5 | 1.1 | 1.7 | 3.9 | 5.2 | -54 | -2.7 | -5.4 | 46.8 | 0.0 | 37.0 | -3.42 | 46.3 | 46.8 |
S. Szabo
|
G | 27 | 21.9 | 3.9 | 2.7 | 0.7 | 0.8 | 0.1 | 1.1 | 4.2 | 3.0 | -66 | -3.0 | -5.0 | 31.0 | 32.0 | 54.5 | 0.68 | 43.2 | 41.6 |
L. Yergensen
|
G | 25 | 16.2 | 3.5 | 1.6 | 1.2 | 0.2 | 0.1 | 1.6 | 3.3 | 1.6 | -53 | -2.6 | -5.2 | 31.7 | 21.4 | 81.2 | -0.48 | 45.3 | 37.2 |
L. Anderegg
|
F | 26 | 9.0 | 2.7 | 1.4 | 0.8 | 0.2 | 0.1 | 0.6 | 2.6 | 2.0 | -16 | -0.8 | -2.8 | 35.3 | 31.8 | 88.9 | -0.32 | 48.6 | 45.6 |
M. Ennis
|
G | 7 | 5.3 | 2.4 | 0.7 | 0.4 | 0.1 | 0.0 | 0.4 | 2.1 | 1.1 | 32 | 16.0 | 267.6 | 40.0 | 37.5 | 100.0 | 0.76 | 53.5 | 50.0 |
H. Burg
|
G | 19 | 7.5 | 1.6 | 1.3 | 0.7 | 0.4 | 0.0 | 0.9 | 1.7 | 1.4 | 16 | 1.0 | 4.4 | 37.5 | 20.0 | 80.0 | 1.62 | 45.3 | 42.2 |
L. Lebon
|
F | 12 | 9.3 | 1.5 | 1.6 | 0.4 | 0.2 | 0.2 | 0.7 | 1.0 | 2.2 | 9 | 1.8 | 6.5 | 33.3 | 0 | 71.4 | 0.3 | 49.6 | 33.3 |
K. Durrill
|
G | 5 | 5.4 | 0.4 | 0.6 | 0.6 | 0.0 | 0.0 | 0.4 | 1.4 | -0.2 | 18 | 4.5 | 33.4 | 0.0 | 0.0 | 100.0 | -0.94 | 12.7 | 0.0 |
T. Fautua
|
F | 2 | 6.5 | 0.0 | 1.0 | 0.5 | 0.5 | 0.0 | 0.0 | 1.5 | 0.5 | 10 | 3.3 | 32.1 | 0.0 | 0 | 0 | -1.01 | 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