Arizona State
2014 Team Stats (6 games)
68.3
PPG
78.2
Opp
-9.8
Margin
41.3%
FG%
37.3%
3P%
67.6%
FT%
31.5
RPG
12.8
APG
12.3
TO
-
Est. poss./game
76.6
Adj PPG
65.7
Adj Opp PPG
#38
Scoring Rank
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 โ | 1062 (#128) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 1178 (#57) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 1006 (#164) | HCA +92 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | +11.9 (#36) | HCA +2.8 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | +8.2 (#64) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.719 (#50) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.892 (#34) | AdjNet +18.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.894 (#34) | AdjNet +18.4 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.730 (#38) | AdjO 76.6 | AdjD 65.7 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.587 (#81) | AdjO 73.5 | AdjD 69.6 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.723 (#59) | 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 | 0.696 (#69) | 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 | 1160 (#68) | RD 113 | GP 33 |
2014 Schedule & Results
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 GP | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Jahii Carson
|
G | 26 | 35.8 | 19.6 | 4.0 | 4.6 | 0.8 | 0.0 | 3.5 | 6.0 | 19.5 | 171 | 29 | 5.9 | 7.2 | 41.7 | 40.7 | 79.0 | 4.51 | 138.9 | 45.2 |
Jermaine Marshall
|
G | 5 | 31.8 | 13.4 | 3.8 | 1.2 | 0.4 | 0.2 | 1.2 | 11.0 | 6.8 | 114 | 28 | 4.1 | 5.7 | 43.6 | 41.4 | 50.0 | -0.73 | 54.8 | 54.5 |
Jordan Bachynski
|
C | 26 | 30.8 | 12.0 | 8.4 | 0.6 | 0.3 | 4.1 | 1.7 | 3.2 | 20.5 | 123 | 29 | 4.2 | 5.9 | 51.2 | 0 | 67.3 | 1.12 | 150.2 | 51.2 |
Shaquielle McKissic
|
F | 25 | 28.0 | 8.2 | 5.4 | 2.7 | 1.2 | 0.0 | 0.8 | 2.4 | 14.4 | 96 | 28 | 3.4 | 5.2 | 45.0 | 27.8 | 56.7 | 1.1 | 140.7 | 49.2 |
Jonathan Gilling
|
F | 26 | 29.2 | 7.3 | 4.0 | 2.9 | 0.5 | 0.1 | 1.3 | 2.6 | 11.0 | 116 | 29 | 4.0 | 6.2 | 41.8 | 43.1 | 55.0 | 1.56 | 126.0 | 58.2 |
Richie Edwards
|
F | 3 | 11.3 | 6.0 | 1.3 | 1.0 | 0.3 | 0.3 | 0.3 | 4.0 | 4.7 | 26 | 14 | 1.9 | 12.1 | 50.0 | 44.4 | 66.7 | -1.46 | 67.6 | 66.7 |
Bo Barnes
|
G | 20 | 13.1 | 4.5 | 1.9 | 0.5 | 0.2 | 0.1 | 0.6 | 1.6 | 4.9 | 14 | 21 | 0.7 | 2.1 | 51.5 | 52.2 | 66.7 | -0.57 | 117.6 | 69.7 |
Chance Murray
|
G | 17 | 8.7 | 2.8 | 1.7 | 0.7 | 0.1 | 0.1 | 0.4 | 0.9 | 4.2 | 93 | 21 | 4.4 | 24.0 | 40.0 | 42.9 | 66.7 | 2.76 | 133.2 | 50.0 |
Egor Koulechov
|
G | 3 | 19.0 | 2.7 | 2.7 | 1.0 | 0.0 | 0.0 | 1.3 | 3.7 | 1.3 | 66 | 25 | 2.6 | 8.1 | 18.2 | 0.0 | 66.7 | -1.35 | 29.3 | 18.2 |
Eric Jacobsen
|
F | 25 | 10.9 | 2.6 | 2.2 | 0.2 | 0.2 | 0.4 | 0.7 | 0.6 | 4.4 | 67 | 28 | 2.4 | 10.2 | 80.0 | 0 | 50.0 | 1.24 | 175.5 | 80.0 |
Sai Tummala
|
G | 12 | 5.7 | 2.2 | 0.8 | 0.2 | 0.2 | 0.0 | 0.2 | 1.1 | 2.0 | 13 | 14 | 0.9 | 7.6 | 30.8 | 20.0 | 0 | -2.5 | 100.0 | 38.5 |
Calaen Robinson
|
G | 15 | 5.7 | 1.6 | 1.0 | 0.9 | 0.5 | 0.1 | 0.5 | 0.5 | 3.0 | 50 | 20 | 2.5 | 17.7 | 62.5 | 71.4 | 100.0 | 1.93 | 135.1 | 93.8 |
Brandan Kearney
|
G | 4 | 7.8 | 0.8 | 0.8 | 0.0 | 0.2 | 0.0 | 0.5 | 1.5 | -0.2 | -48 | 14 | -3.4 | -19.8 | 16.7 | 100.0 | 0 | -4.82 | 25.0 | 25.0 |
Jarett Upchurch
|
G | 5 | 1.2 | 0.6 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8 | 1 | 5 | 0.2 | 6.2 | 0 | 0 | 0 | -1.23 | 0 | 0 |
David Whitmore
|
- | 2 | 1.0 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | 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