Miami
2023 Team Stats (24 games)
80.1
PPG
72.7
Opp
+6.0
Margin
47.9%
FG%
37.3%
3P%
78.8%
FT%
34.8
RPG
14.0
APG
10.5
TO
78.8
Pace
Model Outputs
2022-2023
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 → | 1227 (#102) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1312 (#75) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +36.4 (#48) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.677 (#19) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.721 (#52) | NetEff +9.0 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.737 (#32) | AdjNet +8.9 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.738 (#32) | AdjNet +9.0 |
2023 Schedule & Results
2023 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Isaiah Wong
|
- | 29 | 33.9 | 15.8 | 4.2 | 2.9 | 1.2 | 0.4 | 2.4 | 10.2 | 11.8 | - | - | - | 43.8 | 38.2 | 86.1 | - | 64.2 | 50.8 |
J. Miller
|
- | 29 | 35.4 | 15.2 | 6.3 | 2.9 | 1.1 | 0.4 | 1.4 | 9.6 | 15.0 | -56 | -4.7 | -5.9 | 54.7 | 34.6 | 76.8 | 0.09 | 69.1 | 57.9 |
N. Pack
|
G | 27 | 32.4 | 14.5 | 2.7 | 2.1 | 1.1 | 0.1 | 1.6 | 10.0 | 9.0 | -94 | -7.2 | -11.3 | 46.1 | 43.2 | 90.0 | -0.18 | 67.7 | 58.5 |
Norchad Omier
|
- | 28 | 28.6 | 12.5 | 10.2 | 1.3 | 1.0 | 1.1 | 1.9 | 8.2 | 16.0 | - | - | - | 54.8 | 40.0 | 75.2 | 0.18 | 63.5 | 55.7 |
W. Poplar
|
G | 29 | 24.6 | 8.9 | 3.4 | 1.4 | 1.2 | 0.3 | 1.1 | 6.4 | 7.6 | - | - | - | 46.8 | 39.7 | 87.1 | - | 64.4 | 55.1 |
B. Joseph
|
- | 29 | 19.0 | 5.1 | 1.9 | 2.0 | 0.6 | 0.3 | 1.0 | 3.7 | 5.2 | - | - | - | 40.6 | 41.0 | 65.6 | 0.03 | 61.6 | 52.4 |
Harlond Beverly
|
G | 28 | 13.1 | 4.0 | 1.5 | 1.4 | 0.6 | 0.0 | 0.8 | 2.8 | 3.9 | - | - | - | 46.8 | 27.6 | 79.3 | 0.05 | 62.4 | 51.9 |
A. Walker
|
- | 28 | 10.6 | 3.1 | 1.2 | 0.3 | 0.3 | 0.1 | 0.5 | 2.6 | 2.0 | 17 | 1.4 | 2.7 | 47.2 | 14.3 | 60.0 | 1.0 | 53.2 | 48.6 |
J. Robinson
|
G | 3 | 2.0 | 1.3 | 0.7 | 0.0 | 0.0 | 0.3 | 0.3 | 0.7 | 1.3 | 9 | 1.0 | 2.3 | 50.0 | 0 | 100.0 | 0.45 | 69.4 | 50.0 |
A.J. Casey
|
- | 22 | 6.2 | 0.5 | 0.8 | 0.1 | 0.0 | 0.1 | 0.1 | 0.7 | 0.8 | -13 | -1.3 | -1.9 | 20.0 | 0.0 | 66.7 | 0.73 | 34.0 | 20.0 |
C. Watson
|
G | 5 | 2.4 | 0.4 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8 | -0.2 | - | - | - | 25.0 | 0.0 | 0.0 | - | 22.5 | 25.0 |
F. Aire
|
- | 8 | 2.0 | 0.0 | 0.4 | 0.0 | 0.0 | 0.2 | 0.0 | 0.4 | 0.2 | 20 | 2.2 | 11.2 | 0.0 | 0 | 0.0 | 0.47 | 0.0 | 0.0 |
D. Jovanovich
|
F | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | 24 | 2.7 | 3.2 | - | - | - | 1.36 | - | - |
F. Gkogkos
|
- | 1 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | -1.0 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
J. White
|
F | 1 | 13.0 | 0.0 | 0.0 | 2.0 | 1.0 | 0.0 | 0.0 | 0.0 | 3.0 | 27 | 3.9 | 9.8 | 0 | 0 | 0 | 0.72 | 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