Miami
2019 Team Stats (9 games)
72.6
PPG
75.9
Opp
-5.1
Margin
45.3%
FG%
35.4%
3P%
70.7%
FT%
30.4
RPG
11.6
APG
12.9
TO
78.2
Pace
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 → | 1361 (#86) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1421 (#61) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +33.8 (#58) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.198 (#80) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.250 (#57) | NetEff -10.0 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.618 (#54) | AdjNet +4.2 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.622 (#54) | AdjNet +4.3 |
2019 Schedule & Results
| Date | Vs/At | Opponent | Result | Score |
|---|---|---|---|---|
| 2018-11-22 | vs | La Salle Explorers | W | 85 - 49 |
| 2018-11-25 | @ | Seton Hall Pirates | L | 81 - 83 |
| 2019-01-03 | vs | NC State Wolfpack | L | 82 - 87 |
| 2019-01-09 | @ | Florida State Seminoles | L | 62 - 68 |
| 2019-01-19 | vs | North Carolina Tar Heels | L | 76 - 85 |
| 2019-01-30 | vs | Virginia Tech Hokies | L | 70 - 82 |
| 2019-02-02 | @ | Virginia Cavaliers | L | 46 - 56 |
| 2019-02-09 | @ | North Carolina Tar Heels | L | 85 - 88 |
| 2019-03-02 | @ | Duke Blue Devils | L | 57 - 87 |
| 2019-03-08 | @ | Virginia Tech Hokies | L | 70 - 84 |
| 2019-03-12 | vs | Wake Forest Demon Deacons | W | 79 - 71 |
| 2019-03-13 | @ | Virginia Tech Hokies | L | 56 - 71 |
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/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
C. Lykes
|
G | 12 | 35.0 | 17.9 | 2.5 | 3.1 | 1.5 | 0.0 | 3.2 | 13.8 | 7.9 | - | - | - | 43.4 | 36.5 | 83.0 | - | 56.8 | 51.5 |
A. Lawrence II
|
G | 12 | 32.9 | 12.9 | 5.8 | 2.8 | 1.1 | 0.6 | 2.5 | 9.7 | 11.1 | 78 | 6.5 | 9.1 | 45.7 | 34.0 | 72.1 | 1.49 | 57.4 | 53.4 |
Z. Johnson
|
G | 12 | 31.3 | 11.6 | 3.3 | 2.3 | 1.3 | 0.3 | 2.3 | 10.2 | 6.4 | - | - | - | 36.9 | 31.7 | 63.2 | - | 47.3 | 42.2 |
E. Izundu
|
C | 12 | 28.0 | 10.2 | 7.1 | 0.9 | 0.9 | 0.8 | 1.8 | 6.4 | 11.8 | - | - | - | 70.1 | 50.0 | 58.3 | - | 70.2 | 70.8 |
D. Vasiljevic
|
G | 12 | 30.9 | 9.0 | 4.4 | 1.2 | 0.5 | 0.0 | 0.8 | 8.6 | 5.8 | - | - | - | 36.9 | 30.3 | 80.0 | - | 49.3 | 46.6 |
S. Waardenburg
|
F | 12 | 23.8 | 5.4 | 3.6 | 1.1 | 0.5 | 0.2 | 1.1 | 4.2 | 5.6 | - | - | - | 46.0 | 44.4 | 73.3 | - | 57.4 | 54.0 |
D. Gak
|
F | 2 | 15.0 | 4.0 | 5.0 | 0.5 | 0.0 | 0.5 | 0.5 | 3.5 | 6.0 | - | - | - | 57.1 | 0 | 0 | - | 57.1 | 57.1 |
A. Mack
|
G | 11 | 17.7 | 2.5 | 0.6 | 0.6 | 0.6 | 0.2 | 0.5 | 3.5 | 0.7 | - | - | - | 28.9 | 21.4 | 0 | - | 36.8 | 36.8 |
W. Herenton
|
G | 6 | 2.5 | 1.3 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.5 | - | - | - | 33.3 | 50.0 | 100.0 | - | 58.1 | 50.0 |
D. Proctor
|
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
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