Kansas State
2014 Team Stats (13 games)
70.6
PPG
71.5
Opp
-0.8
Margin
44.1%
FG%
36.6%
3P%
70.7%
FT%
33.5
RPG
13.9
APG
11.5
TO
-
Est. poss./game
69.3
Adj PPG
59.2
Adj Opp PPG
#45
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 | 1150 (#67) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 1177 (#58) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 1018 (#146) | HCA +92 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | +11.1 (#45) | HCA +2.8 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | +10.6 (#42) | HCA +2.9 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.652 (#85) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.889 (#36) | AdjNet +18.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.892 (#35) | AdjNet +18.2 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.715 (#45) | AdjO 69.3 | AdjD 59.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.618 (#64) | AdjO 68.8 | AdjD 63.5 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.753 (#48) | 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 | 0.736 (#54) | 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 | 1199 (#51) | RD 111 | 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Marcus Foster
|
G | 29 | 29.9 | 16.0 | 3.4 | 2.4 | 0.6 | 0.2 | 2.3 | 5.5 | 14.9 | 74 | 29 | 2.6 | 3.8 | 45.0 | 42.1 | 75.9 | -1.77 | 126.3 | 55.0 |
Thomas Gipson
|
F | 27 | 26.6 | 11.4 | 6.5 | 0.4 | 0.4 | 0.5 | 2.2 | 4.1 | 12.9 | 134 | 27 | 5.0 | 7.9 | 51.8 | 0 | 69.4 | 3.53 | 115.7 | 51.8 |
Shane Southwell
|
G | 28 | 27.1 | 8.9 | 4.1 | 2.8 | 0.8 | 1.1 | 1.6 | 4.0 | 12.0 | 153 | 28 | 5.5 | 8.8 | 38.1 | 34.0 | 80.0 | 2.87 | 98.3 | 46.0 |
Will Spradling
|
G | 29 | 30.0 | 7.9 | 2.9 | 2.8 | 1.2 | 0.0 | 1.1 | 2.4 | 11.4 | 152 | 29 | 5.2 | 7.7 | 42.9 | 40.0 | 71.4 | 4.38 | 139.1 | 58.6 |
Wesley Iwundu
|
F | 29 | 23.9 | 6.8 | 4.2 | 1.8 | 0.5 | 0.3 | 1.3 | 2.3 | 10.1 | 106 | 29 | 3.7 | 6.5 | 42.6 | 42.9 | 68.9 | 2.25 | 112.8 | 44.9 |
Nino Williams
|
F | 29 | 15.2 | 5.8 | 3.1 | 0.6 | 0.4 | 0.1 | 0.8 | 1.8 | 7.5 | -18 | 29 | -0.6 | -1.7 | 45.1 | 0 | 82.8 | -2.49 | 131.7 | 45.1 |
Nigel Johnson
|
G | 26 | 13.9 | 4.0 | 1.4 | 1.7 | 0.7 | 0.0 | 0.8 | 1.4 | 5.6 | 13 | 26 | 0.5 | 1.7 | 38.9 | 25.0 | 91.7 | -1.68 | 126.0 | 45.8 |
Omari Lawrence
|
G | 29 | 12.7 | 3.3 | 1.9 | 0.8 | 0.6 | 0.2 | 0.7 | 1.1 | 4.9 | 43 | 29 | 1.5 | 5.1 | 35.5 | 0.0 | 53.3 | 1.32 | 126.3 | 35.5 |
D.J. Johnson
|
F | 29 | 13.8 | 3.2 | 3.4 | 0.1 | 0.3 | 0.6 | 0.7 | 0.9 | 6.0 | -7 | 29 | -0.2 | -0.8 | 73.1 | 0 | 53.8 | -1.74 | 148.2 | 73.1 |
John David Thomas
|
G | 18 | 15.1 | 2.7 | 2.0 | 2.1 | 0.4 | 0.0 | 1.2 | 2.4 | 3.7 | 18 | 18 | 1.0 | 2.6 | 32.6 | 33.3 | 45.5 | 0.37 | 45.6 | 34.9 |
Ryan Schultz
|
F | 11 | 2.5 | 0.9 | 0.5 | 0.2 | 0.3 | 0.0 | 0.5 | 0.0 | 1.5 | -9 | 11 | -0.8 | -12.1 | 0 | 0 | 0 | -2.21 | 0 | 0 |
Brian Rohleder
|
G | 12 | 1.8 | 0.2 | 0.2 | 0.1 | 0.1 | 0.0 | 0.1 | 0.0 | 0.4 | -5 | 12 | -0.4 | -8.2 | 0 | 0 | 0 | -0.88 | 0 | 0 |
Shawn Meyer
|
G | 9 | 1.2 | 0.1 | 0.3 | 0.0 | 0.0 | 0.0 | 0.1 | 0.0 | 0.3 | -3 | 10 | -0.3 | -9.0 | 0 | 0 | 0 | -1.12 | 0 | 0 |
Jack Karapetyan
|
F | 5 | 3.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -1 | 5 | -0.2 | -2.4 | 0 | 0 | 0 | -0.92 | 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