Manhattan
2022 Team Stats (3 games)
64.0
PPG
72.6
Opp
-1.7
Margin
40.0%
FG%
31.3%
3P%
72.9%
FT%
29.3
RPG
13.0
APG
12.0
TO
75.7
Pace
Model Outputs
2021-2022
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 → | 866 (#710) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1020 (#309) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 1080 (#81) | HCA +115 elo |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More → | 958 (#541) | HCA +115 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +13.5 (#351) | HCA +2.7 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +15.6 (#123) | HCA +2.4 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More → | +8.7 (#221) | HCA +2.4 |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.085 (#280) | NetEff -21.3 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.670 (#55) | AdjO 68.7 | AdjD 60.9 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More → | 0.454 (#452) | AdjO 69.9 | AdjD 72.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.780 (#136) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More → | 0.602 (#262) | 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 → | 0.771 (#123) | 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 → | 0.566 (#267) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 1095 (#150) | RD 136 | GP 31 |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More → | 962 (#248) | RD 137 | GP 30 |
2022 Schedule & Results
2022 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
D. Vaughn
|
F | 1 | 32.0 | 20.0 | 11.0 | 0.0 | 2.0 | 0.0 | 2.0 | 0.0 | 31.0 | -20 | -0.6 | -0.8 | 0 | 0 | 0 | 0.13 | 0 | 0 |
J. Perez
|
- | 16 | 34.6 | 19.8 | 3.2 | 4.9 | 0.9 | 0.3 | 3.4 | 4.1 | 21.7 | -81 | -16.2 | -35.5 | 41.5 | 42.9 | 95.8 | 0.61 | 209.8 | 48.5 |
Elijah Buchanan
|
- | 5 | 30.8 | 11.2 | 4.2 | 2.0 | 0.6 | 0.4 | 1.0 | 4.2 | 13.2 | -51 | -1.7 | -2.5 | 38.1 | 33.3 | 71.4 | -0.39 | 116.3 | 45.2 |
K. McDowell
|
G | 1 | 24.0 | 11.0 | 1.0 | 0.0 | 0.0 | 0.0 | 2.0 | 0.0 | 10.0 | 226 | 7.5 | 10.0 | 0 | 0 | 0 | 1.29 | 0 | 0 |
A. Nelson
|
- | 26 | 27.0 | 10.9 | 3.1 | 2.3 | 1.6 | 0.2 | 3.4 | 1.6 | 13.2 | -94 | -3.2 | -4.6 | 47.6 | 47.6 | 75.0 | 0.5 | 312.0 | 59.5 |
J. Roberts
|
- | 30 | 21.2 | 8.9 | 6.5 | 0.2 | 0.4 | 1.3 | 0.6 | 0.9 | 15.9 | 184 | 5.0 | 11.8 | 77.8 | 0 | 77.8 | 1.3 | 429.6 | 77.8 |
W. Williams
|
- | 3 | 21.7 | 8.3 | 3.7 | 0.0 | 1.0 | 0.3 | 1.7 | 6.3 | 5.3 | -50 | -1.7 | -3.5 | 57.9 | 0 | 37.5 | -0.01 | 55.5 | 57.9 |
S. Stewart
|
- | 16 | 24.4 | 7.8 | 1.8 | 0.9 | 1.1 | 0.1 | 1.3 | 0.3 | 10.0 | 4 | 0.2 | 0.4 | 20.0 | 25.0 | 66.7 | 0.65 | 981.0 | 30.0 |
S. Diallo
|
- | 3 | 28.3 | 6.7 | 5.3 | 1.3 | 1.0 | 0.0 | 0.7 | 5.3 | 8.3 | - | - | - | 43.8 | 25.0 | 71.4 | -0.25 | 52.4 | 46.9 |
M. Abii
|
F | 1 | 9.0 | 6.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 7.0 | 91 | 3.6 | 14.8 | 0 | 0 | 0 | 0.64 | 0 | 0 |
D. Moore
|
G | 1 | 18.0 | 6.0 | 3.0 | 3.0 | 1.0 | 0.0 | 3.0 | 0.0 | 10.0 | 31 | 1.2 | 8.1 | 0 | 0 | 0 | 0.19 | 0 | 0 |
R. Reid
|
G | 13 | 16.0 | 3.2 | 1.4 | 1.3 | 0.2 | 0.0 | 1.0 | 0.7 | 4.4 | -40 | -1.5 | -4.7 | 11.1 | 14.3 | 75.0 | -0.3 | 190.5 | 16.7 |
N. Brennen
|
- | 30 | 15.8 | 3.0 | 2.2 | 0.4 | 0.5 | 0.1 | 0.2 | 0.5 | 5.4 | 0 | 0.0 | 0.0 | 25.0 | 28.6 | 100.0 | 0.39 | 250.6 | 37.5 |
M. Watson
|
- | 23 | 14.2 | 2.9 | 1.5 | 0.8 | 0.5 | 0.0 | 0.8 | 0.3 | 4.6 | -52 | -1.8 | -2.7 | 14.3 | 0.0 | 100.0 | 0.08 | 376.7 | 14.3 |
M. Glassman
|
- | 8 | 1.9 | 0.1 | 0.4 | 0.2 | 0.0 | 0.0 | 0.2 | 0.0 | 0.5 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
A. Arora
|
- | 2 | 1.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | - | 0 | 0 |
J. Pope
|
G | 1 | 9.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 | -50 | -1.9 | -5.7 | 0 | 0 | 0 | -0.42 | 0 | 0 |
S. Altman
|
G | 1 | 16.0 | 0.0 | 1.0 | 0.0 | 1.0 | 0.0 | 0.0 | 0.0 | 2.0 | -14 | -0.5 | -1.3 | 0 | 0 | 0 | -0.02 | 0 | 0 |
A. Cisse
|
- | 1 | 2.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | - | - | - | 0 | 0 | 0 | -0.08 | 0 | 0 |
G. Hyland
|
- | 1 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | -1.0 | - | - | - | 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