Kansas
2018 Team Stats (31 games)
80.8
PPG
73.5
Opp
+7.3
Margin
49.2%
FG%
40.1%
3P%
70.3%
FT%
35.1
RPG
16.1
APG
11.8
TO
78.9
Pace
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 → | 1588 (#29) | - |
| Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → | 946 (#664) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1568 (#13) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 934 (#730) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +40.6 (#12) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.627 (#24) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.676 (#15) | NetEff +6.9 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.856 (#11) | AdjNet +15.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.859 (#11) | AdjNet +15.6 |
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/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Devonte' Graham
|
- | 31 | 38.2 | 17.2 | 4.1 | 7.4 | 1.5 | 0.0 | 2.8 | 12.6 | 14.9 | - | - | - | 39.4 | 40.0 | 82.8 | - | 57.4 | 50.4 |
M. Newman
|
G | 31 | 31.7 | 15.2 | 4.9 | 2.0 | 1.0 | 0.2 | 1.4 | 10.5 | 11.3 | - | - | - | 47.7 | 43.2 | 83.7 | - | 63.3 | 58.9 |
S. Mykhailiuk
|
- | 31 | 34.8 | 14.4 | 4.0 | 2.8 | 1.2 | 0.4 | 1.7 | 11.9 | 9.2 | - | - | - | 43.2 | 44.3 | 80.9 | - | 57.4 | 55.4 |
Udoka Azubuike
|
- | 28 | 23.2 | 12.5 | 6.6 | 0.6 | 0.6 | 1.7 | 2.0 | 7.1 | 13.0 | - | - | - | 78.8 | 0 | 41.9 | - | 73.5 | 78.8 |
L. Vick
|
G | 31 | 32.7 | 11.4 | 4.4 | 1.5 | 0.7 | 0.3 | 1.6 | 9.1 | 7.6 | - | - | - | 49.1 | 36.9 | 65.9 | - | 58.6 | 57.6 |
S. De Sousa
|
F | 19 | 9.1 | 4.2 | 3.9 | 0.2 | 0.1 | 0.1 | 0.9 | 2.5 | 5.0 | - | - | - | 68.1 | 0 | 71.4 | - | 70.2 | 68.1 |
M. Garrett
|
- | 31 | 19.4 | 4.0 | 3.0 | 1.0 | 0.7 | 0.2 | 0.7 | 3.5 | 4.8 | - | - | - | 43.9 | 21.9 | 47.9 | - | 48.4 | 47.2 |
M. Lightfoot
|
F | 30 | 13.7 | 3.3 | 3.0 | 0.3 | 0.3 | 1.5 | 0.8 | 2.7 | 4.9 | - | - | - | 54.3 | 27.3 | 60.0 | - | 57.1 | 56.2 |
S. Cunliffe
|
G | 14 | 5.1 | 2.0 | 0.6 | 0.3 | 0.1 | 0.1 | 0.4 | 1.8 | 1.0 | - | - | - | 48.0 | 25.0 | 100.0 | - | 54.1 | 52.0 |
J. Sosinski
|
F | 7 | 1.3 | 0.9 | 0.6 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4 | 1.0 | - | - | - | 100.0 | 0 | 0 | - | 100.0 | 100.0 |
C. Teahan
|
G | 8 | 1.9 | 0.8 | 0.6 | 0.1 | 0.0 | 0.0 | 0.2 | 0.8 | 0.5 | - | - | - | 33.3 | 40.0 | 0 | - | 50.0 | 50.0 |
C. Young
|
G | 8 | 4.4 | 0.6 | 0.0 | 0.8 | 0.1 | 0.0 | 0.4 | 0.5 | 0.6 | - | - | - | 50.0 | 0.0 | 50.0 | - | 51.2 | 50.0 |
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