San Francisco
2014 Team Stats (5 games)
73.0
PPG
77.0
Opp
-4.0
Margin
45.4%
FG%
31.3%
3P%
56.1%
FT%
37.0
RPG
12.0
APG
14.2
TO
83.6
Pace
Model Outputs
2013-2014
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 → | 1379 (#118) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1342 (#118) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 927 (#857) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +31.4 (#78) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.154 (#88) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.081 (#104) | AdjNet -21.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.078 (#104) | AdjNet -21.1 |
2014 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2013-11-22 | @ | Montana Grizzlies | W | 75 - 74 |
| 2013-11-27 | vs | Sonoma State Seawolves | W | 96 - 73 |
| 2013-11-30 | vs | Illinois State Redbirds | L | 76 - 90 |
| 2013-12-30 | @ | Gonzaga Bulldogs | L | 41 - 69 |
| 2014-03-10 | @ | BYU Cougars | L | 77 - 79 |
2014 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
C. Dickerson
|
F | 5 | 30.6 | 15.4 | 9.2 | 2.4 | 0.2 | 0.2 | 2.2 | 11.4 | 13.8 | - | - | - | 49.1 | 33.3 | 48.3 | - | 55.2 | 55.3 |
T. Derksen
|
G | 5 | 24.2 | 11.4 | 2.4 | 0.8 | 1.2 | 0.4 | 1.6 | 7.4 | 7.2 | - | - | - | 56.8 | 50.0 | 64.3 | - | 66.0 | 64.9 |
A. Holmes
|
G | 5 | 30.0 | 10.4 | 1.6 | 2.6 | 2.2 | 0.4 | 2.2 | 9.2 | 5.8 | - | - | - | 41.3 | 33.3 | 77.8 | - | 52.0 | 48.9 |
K. Pinkins
|
F | 5 | 25.8 | 10.4 | 7.0 | 1.0 | 0.8 | 1.2 | 1.4 | 8.4 | 10.6 | - | - | - | 47.6 | 0.0 | 54.5 | - | 50.3 | 47.6 |
M. Tollefsen
|
F | 5 | 28.8 | 10.2 | 4.4 | 0.8 | 0.6 | 1.0 | 1.0 | 7.2 | 8.8 | - | - | - | 52.8 | 31.2 | 53.3 | - | 59.9 | 59.7 |
M. Glover
|
G | 5 | 28.8 | 9.6 | 4.8 | 2.8 | 1.2 | 0.2 | 2.2 | 7.0 | 9.4 | - | - | - | 42.9 | 16.7 | 56.7 | 0.53 | 49.8 | 44.3 |
C. Hilliard
|
G | 3 | 13.0 | 2.7 | 1.7 | 0.7 | 0.3 | 0.3 | 1.3 | 3.3 | 1.0 | - | - | - | 30.0 | 33.3 | 50.0 | - | 36.8 | 35.0 |
C. Adams
|
G | 5 | 21.4 | 2.6 | 1.6 | 1.2 | 0.8 | 0.0 | 1.2 | 4.8 | 0.2 | - | - | - | 20.8 | 18.8 | 0 | - | 27.1 | 27.1 |
M. Christiansen
|
F | 4 | 6.0 | 1.2 | 0.8 | 0.0 | 0.0 | 0.0 | 1.0 | 1.0 | 0.0 | - | - | - | 50.0 | 0 | 50.0 | - | 51.2 | 50.0 |
T. Xu
|
C | 3 | 2.3 | 0.7 | 0.7 | 0.0 | 0.0 | 0.0 | 0.7 | 0.7 | 0.0 | - | - | - | 50.0 | 0 | 0 | - | 50.0 | 50.0 |
G. Hoffmann
|
G | 2 | 3.5 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.5 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
Numbers/Game vs RAPM
Not enough players with both Numbers/Game and RAPM to plot.
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