Stanford Cardinal
2019 Team Stats (5 games)
67.6
PPG
78.6
Opp
-11.0
Margin
39.5%
FG%
33.3%
3P%
68.1%
FT%
36.8
RPG
12.2
APG
17.0
TO
-
Est. poss./game
72.4
Adj PPG
67.6
Adj Opp PPG
#103
Scoring Rank
Model Outputs
2018-2019
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 | Data withheld: source-integrity hold | Historical Elo fit predates the season cutoff fix and has no verified season-bounded input receipt. |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 1034 (#141) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 963 (#229) | HCA +83 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | +5.4 (#101) | HCA +2.8 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | +5.5 (#86) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.536 (#160) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.694 (#107) | AdjNet +7.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.697 (#106) | AdjNet +7.2 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.607 (#103) | AdjO 72.4 | AdjD 67.6 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.552 (#114) | AdjO 70.2 | AdjD 67.9 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.565 (#136) | 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 | 0.554 (#140) | 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 | 1003 (#172) | RD 135 | GP 31 |
2019 Schedule & Results
2019 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
KZ Okpala
|
- | 5 | 32.0 | 11.6 | 5.4 | 2.2 | 0.8 | 1.0 | 2.4 | 10.2 | 8.4 | 2 | 27 | 0.1 | 0.1 | 39.2 | 37.5 | 57.1 | 0.91 | 48.1 | 45.1 |
D. Davis
|
G | 23 | 29.5 | 10.9 | 3.0 | 4.0 | 1.3 | 0.3 | 3.1 | 2.4 | 13.9 | 39 | 24 | 1.6 | 2.2 | 42.9 | 26.3 | 59.1 | 2.6 | 190.3 | 47.3 |
C. Ryan
|
- | 5 | 29.2 | 10.4 | 3.2 | 2.0 | 1.2 | 0.2 | 2.2 | 9.0 | 5.8 | -33 | 23 | -1.4 | -2.1 | 35.6 | 35.1 | 77.8 | -0.93 | 53.1 | 50.0 |
J. Sharma
|
C | 27 | 22.2 | 10.0 | 6.9 | 0.3 | 0.5 | 1.4 | 1.3 | 2.6 | 15.1 | -23 | 29 | -0.8 | -1.5 | 66.2 | 0 | 61.5 | 0.04 | 163.1 | 66.2 |
O. da Silva
|
F | 27 | 27.5 | 9.6 | 6.0 | 1.8 | 0.6 | 1.3 | 1.9 | 2.7 | 14.7 | 32 | 29 | 1.1 | 1.6 | 46.6 | 27.6 | 57.9 | 1.68 | 158.6 | 52.1 |
M. Sheffield II
|
G | 23 | 16.4 | 5.5 | 1.3 | 0.6 | 0.5 | 0.1 | 0.7 | 2.2 | 5.0 | 46 | 25 | 1.8 | 4.9 | 49.0 | 46.7 | 100.0 | 3.21 | 120.4 | 62.7 |
B. Wills
|
G | 26 | 24.7 | 5.4 | 3.4 | 2.0 | 1.0 | 0.6 | 2.3 | 1.8 | 8.2 | -94 | 28 | -3.4 | -5.6 | 36.2 | 45.5 | 52.2 | -2.75 | 123.4 | 41.5 |
J. Delaire
|
- | 27 | 12.9 | 4.0 | 2.0 | 0.4 | 0.2 | 0.3 | 0.6 | 1.8 | 4.5 | -1 | 29 | 0.0 | -0.1 | 33.3 | 0.0 | 90.0 | -1.41 | 103.1 | 33.3 |
I. White
|
G | 26 | 7.9 | 2.8 | 1.0 | 0.3 | 0.2 | 0.0 | 0.5 | 1.3 | 2.4 | -2 | 27 | -0.1 | -0.4 | 45.7 | 46.2 | 33.3 | -0.34 | 97.0 | 62.9 |
K. Pugh
|
F | 18 | 6.7 | 2.1 | 0.9 | 0.4 | 0.1 | 0.0 | 0.6 | 0.6 | 2.4 | -9 | 19 | -0.5 | -3.3 | 50.0 | 100.0 | 50.0 | -1.27 | 150.3 | 55.0 |
L. Kisunas
|
- | 24 | 6.5 | 1.5 | 1.8 | 0.1 | 0.0 | 0.3 | 0.4 | 0.6 | 2.7 | -16 | 25 | -0.6 | -4.3 | 64.3 | 0 | 40.0 | -1.22 | 114.2 | 64.3 |
R. Herenton
|
G | 5 | 2.0 | 1.2 | 0.0 | 0.0 | 0.2 | 0.0 | 0.0 | 0.8 | 0.6 | - | - | - | - | 75.0 | 0.0 | 0 | -2.17 | 75.0 | 75.0 |
T. Stanback
|
F | 11 | 6.2 | 1.2 | 1.5 | 0.1 | 0.0 | 0.4 | 0.6 | 0.5 | 2.0 | -51 | 12 | -4.2 | -25.0 | 60.0 | 0 | 50.0 | -7.31 | 96.2 | 60.0 |
S. Beskind
|
G | 1 | 1.0 | 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