San Diego
2013 Team Stats (4 games)
58.8
PPG
66.5
Opp
-1.4
Margin
41.7%
FG%
31.3%
3P%
62.5%
FT%
29.8
RPG
11.3
APG
13.0
TO
73.2
Pace
Model Outputs
2012-2013
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 → | 1156 (#248) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1283 (#142) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 996 (#311) | HCA +147 elo |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 994 (#350) | HCA +147 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +20.2 (#226) | HCA +3.0 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +12.5 (#109) | HCA +3.3 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | -24.8 (#571) | HCA +3.3 |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.098 (#217) | NetEff -19.4 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.594 (#109) | AdjO 66.2 | AdjD 62.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.414 (#497) | AdjO 63.6 | AdjD 67.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.700 (#153) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.179 (#546) | 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 → | 0.683 (#150) | 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 → | 0.216 (#542) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1047 (#179) | RD 148 | GP 33 |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 933 (#292) | RD 350 | GP 1 |
2013 Schedule & Results
2013 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
J. Dee
|
G | 34 | 31.2 | 15.0 | 3.1 | 0.9 | 0.8 | 0.0 | 1.3 | 2.3 | 16.2 | -91 | -2.7 | -3.7 | 44.3 | 40.5 | 75.0 | -0.3 | 297.0 | 53.8 |
K. Rancifer
|
F | 34 | 26.9 | 10.2 | 3.7 | 1.2 | 0.5 | 0.3 | 1.6 | 1.6 | 12.6 | -39 | -1.1 | -2.0 | 32.7 | 31.6 | 87.5 | -0.43 | 296.5 | 38.2 |
C. Anderson
|
G | 33 | 32.3 | 9.4 | 3.8 | 5.7 | 2.1 | 0.2 | 2.8 | 2.0 | 16.4 | 160 | 2.4 | 4.3 | 47.0 | 38.5 | 65.0 | 1.56 | 207.9 | 50.8 |
C. Manresa
|
F | 27 | 24.7 | 9.0 | 7.1 | 1.1 | 0.5 | 0.6 | 1.6 | 1.1 | 15.6 | -8 | -0.3 | -0.5 | 58.6 | 0 | 76.5 | 0.4 | 331.7 | 58.6 |
M. Davis
|
G | 24 | 16.9 | 6.2 | 1.6 | 0.6 | 0.8 | 0.0 | 0.7 | 1.0 | 7.6 | 12 | 0.4 | 0.6 | 39.1 | 50.0 | 70.0 | -0.25 | 270.1 | 41.3 |
C. Miles
|
G | 34 | 17.5 | 4.9 | 1.6 | 1.7 | 0.8 | 0.0 | 1.3 | 0.6 | 7.0 | -50 | -1.5 | -2.7 | 27.3 | 40.0 | 83.3 | -0.21 | 334.8 | 31.8 |
D. Kramer
|
F | 32 | 14.6 | 4.2 | 2.7 | 0.2 | 0.2 | 0.4 | 1.1 | 0.8 | 5.8 | 14 | 0.4 | 1.4 | 44.0 | 41.7 | 66.7 | 0.01 | 254.6 | 54.0 |
J. Sinis
|
G-F | 33 | 15.3 | 4.1 | 2.5 | 0.3 | 0.3 | 0.3 | 0.8 | 0.8 | 6.0 | -95 | -2.9 | -6.3 | 32.0 | 31.6 | 0.0 | -0.86 | 267.3 | 44.0 |
J. Kok
|
C | 34 | 18.3 | 3.2 | 3.2 | 0.0 | 0.2 | 1.6 | 1.1 | 0.6 | 6.5 | -77 | -2.3 | -4.3 | 38.1 | 0.0 | 58.3 | 0.16 | 205.5 | 38.1 |
S. Fajemisin
|
F | 34 | 10.5 | 2.1 | 2.0 | 0.1 | 0.1 | 0.4 | 0.9 | 0.3 | 3.5 | 30 | 0.9 | 3.3 | 45.5 | 0 | 20.0 | 0.17 | 265.2 | 45.5 |
T. Guidry
|
F | 14 | 4.8 | 1.4 | 0.6 | 0.1 | 0.1 | 0.1 | 0.3 | 0.3 | 1.8 | - | - | - | 25.0 | 33.3 | 50.0 | 0.11 | 133.0 | 37.5 |
K. Stackhouse
|
G | 21 | 5.8 | 1.1 | 0.6 | 0.3 | 0.3 | 0.0 | 0.6 | 0.3 | 1.3 | 32 | 1.5 | 8.7 | 42.9 | 33.3 | 50.0 | 0.51 | 145.9 | 50.0 |
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