San Francisco
2018 Team Stats (7 games)
63.1
PPG
74.7
Opp
-11.6
Margin
39.9%
FG%
34.9%
3P%
61.1%
FT%
31.1
RPG
12.1
APG
11.9
TO
-
Est. poss./game
67.4
Adj PPG
67.2
Adj Opp PPG
#163
Scoring Rank
Model Outputs
2017-2018
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 โ | 1090 (#118) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 1026 (#156) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 1045 (#105) | HCA +95 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | +0.5 (#161) | HCA +2.9 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | +0.5 (#161) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.479 (#184) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.557 (#145) | AdjNet +2.0 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.556 (#145) | AdjNet +2.0 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.506 (#163) | AdjO 67.4 | AdjD 67.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.500 (#167) | AdjO 68.4 | AdjD 68.4 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.562 (#138) | 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 โ | 0.561 (#136) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More โ | 1084 (#110) | RD 85 | GP 38 |
2018 Schedule & Results
2018 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 GP | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Souley Boum
|
- | 32 | 20.9 | 11.7 | 2.8 | 1.1 | 0.6 | 0.2 | 1.9 | 2.0 | 12.3 | -24 | 25 | -1.0 | -2.1 | 33.8 | 42.9 | 90.5 | -1.37 | 251.2 | 43.1 |
Frankie Ferrari
|
G | 35 | 27.9 | 11.1 | 2.4 | 4.0 | 0.9 | 0.0 | 1.7 | 3.0 | 13.7 | 61 | 28 | 2.2 | 3.4 | 42.9 | 40.4 | 79.2 | 3.13 | 167.9 | 51.9 |
Chase Foster
|
F | 32 | 26.6 | 10.5 | 4.2 | 1.8 | 0.6 | 0.2 | 1.7 | 2.3 | 13.3 | 4 | 25 | 0.2 | 0.3 | 36.0 | 37.1 | 55.0 | 0.21 | 199.9 | 44.7 |
Jordan Ratinho
|
G | 35 | 30.6 | 10.1 | 3.5 | 1.2 | 0.8 | 0.3 | 0.9 | 2.6 | 12.4 | 65 | 28 | 2.3 | 3.3 | 41.3 | 37.3 | 77.8 | 3.74 | 170.4 | 53.3 |
Matthew McCarthy
|
F | 33 | 23.0 | 8.2 | 5.6 | 1.2 | 0.6 | 0.5 | 1.5 | 1.8 | 12.9 | 29 | 26 | 1.1 | 2.1 | 44.8 | 30.0 | 52.6 | -0.26 | 204.9 | 47.4 |
Nate Renfro
|
F | 35 | 22.7 | 5.9 | 5.1 | 1.3 | 0.6 | 1.1 | 1.5 | 0.9 | 11.6 | 17 | 28 | 0.6 | 1.1 | 48.4 | 23.1 | 36.4 | -1.76 | 252.0 | 53.2 |
Remu Raitanen
|
F | 30 | 14.1 | 3.7 | 2.4 | 0.5 | 0.3 | 0.1 | 0.5 | 0.9 | 5.5 | -73 | 24 | -3.0 | -8.7 | 35.7 | 27.8 | 75.0 | -5.89 | 184.8 | 44.6 |
Jimbo Lull
|
C | 27 | 9.8 | 3.5 | 2.9 | 0.3 | 0.1 | 0.6 | 1.0 | 1.1 | 5.3 | -27 | 23 | -1.2 | -5.6 | 48.3 | 0.0 | 60.0 | -2.65 | 150.6 | 48.3 |
Erik Poulsen
|
C | 25 | 9.0 | 3.5 | 1.9 | 0.3 | 0.1 | 0.2 | 0.6 | 1.1 | 4.3 | 26 | 19 | 1.4 | 6.5 | 32.1 | 31.2 | 57.1 | 2.13 | 141.6 | 41.1 |
Jamaree Bouyea
|
- | 33 | 13.7 | 2.5 | 1.6 | 0.9 | 0.7 | 0.3 | 0.8 | 0.8 | 4.5 | -32 | 26 | -1.2 | -3.7 | 34.6 | 11.1 | 50.0 | -2.02 | 149.5 | 36.5 |
Nick Loew
|
F | 9 | 8.4 | 1.8 | 1.6 | 0.3 | 0.2 | 0.1 | 0.2 | 0.0 | 3.8 | -11 | 7 | -1.6 | -11.2 | 0 | 0 | 0 | -2.66 | 0 | 0 |
Mladen Djordjevic
|
G | 16 | 8.6 | 1.6 | 1.1 | 1.1 | 0.2 | 0.1 | 0.8 | 0.3 | 2.9 | -7 | 11 | -0.6 | -4.1 | 60.0 | 50.0 | 25.0 | -0.48 | 184.9 | 70.0 |
Taavi Jurkatamm
|
F | 27 | 12.0 | 1.5 | 2.0 | 0.6 | 0.3 | 0.6 | 0.4 | 0.5 | 4.0 | -3 | 20 | -0.1 | -0.5 | 35.7 | 0.0 | 0.0 | -2.22 | 130.5 | 35.7 |
Michael Orlich
|
- | 1 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | -1.0 | - | - | - | - | 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