Florida
2022 Team Stats (15 games)
70.1
PPG
66.0
Opp
+4.8
Margin
42.0%
FG%
27.6%
3P%
72.0%
FT%
33.8
RPG
12.4
APG
12.7
TO
79.7
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 → | 1554 (#16) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1441 (#30) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +41.2 (#13) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.587 (#45) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.561 (#106) | NetEff +2.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.740 (#28) | AdjNet +9.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.743 (#28) | AdjNet +9.2 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Colin Castleton
|
- | 25 | 30.4 | 16.6 | 8.8 | 1.6 | 0.8 | 2.4 | 2.2 | 7.4 | 20.6 | - | - | - | 57.8 | 0.0 | 70.3 | - | 92.0 | 57.8 |
T. Appleby
|
- | 18 | 26.7 | 10.4 | 2.0 | 3.2 | 1.4 | 0.1 | 2.8 | 6.1 | 8.3 | - | - | - | 35.5 | 30.8 | 77.6 | - | 69.4 | 46.4 |
P. Fleming Jr.
|
G | 18 | 25.8 | 9.5 | 4.1 | 2.3 | 1.4 | 0.5 | 1.7 | 7.5 | 8.6 | 4 | 0.7 | 5.2 | 34.1 | 26.4 | 76.2 | 0.4 | 55.7 | 39.3 |
A. Duruji
|
F | 24 | 24.8 | 9.0 | 3.9 | 1.1 | 1.0 | 0.5 | 1.7 | 3.9 | 9.9 | - | - | - | 52.1 | 36.4 | 72.0 | - | 102.9 | 58.5 |
M. Jones
|
- | 30 | 27.7 | 8.8 | 2.7 | 1.6 | 1.1 | 0.2 | 1.1 | 4.7 | 8.7 | 102 | 7.8 | 11.1 | 34.3 | 26.5 | 61.1 | 1.89 | 89.2 | 43.6 |
B. McKissic
|
G | 18 | 25.5 | 7.4 | 2.7 | 1.4 | 1.1 | 0.1 | 1.6 | 5.5 | 5.7 | - | - | - | 43.4 | 29.0 | 64.0 | - | 60.5 | 52.5 |
K. Reeves
|
- | 27 | 14.6 | 4.9 | 1.3 | 0.3 | 0.4 | 0.1 | 0.6 | 1.7 | 4.7 | - | - | - | 30.4 | 28.1 | 75.0 | - | 127.7 | 40.2 |
J. Jitoboh
|
- | 17 | 11.2 | 4.3 | 2.5 | 0.4 | 0.4 | 0.6 | 0.4 | 0.9 | 7.0 | - | - | - | 40.0 | 0.0 | 60.0 | - | 212.2 | 40.0 |
Niels Lane
|
G | 11 | 13.5 | 3.4 | 2.0 | 0.5 | 0.3 | 0.4 | 0.4 | 1.9 | 4.2 | - | - | - | 52.4 | 25.0 | 80.0 | - | 72.8 | 54.8 |
CJ Felder
|
- | 17 | 12.1 | 2.8 | 2.4 | 0.4 | 0.5 | 0.8 | 0.6 | 1.9 | 4.4 | - | - | - | 42.4 | 31.2 | 42.9 | - | 66.5 | 50.0 |
T. Gatkek
|
- | 15 | 8.2 | 1.5 | 1.9 | 0.1 | 0.3 | 0.9 | 0.4 | 0.5 | 3.9 | 43 | 3.1 | 3.2 | 25.0 | 0.0 | 0.0 | 1.29 | 129.5 | 25.0 |
E. Kennedy
|
- | 12 | 5.8 | 1.3 | 0.7 | 0.3 | 0.5 | 0.0 | 0.3 | 2.1 | 0.4 | 11 | 1.0 | 2.4 | 24.0 | 18.8 | 0 | 0.66 | 32.0 | 30.0 |
K. Johnson
|
- | 1 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 43 | 4.8 | 22.7 | 0 | 0 | 0 | 0.62 | 0 | 0 |
Alex Klatsky
|
- | 6 | 1.5 | 0.0 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2 | 0.0 | - | - | - | 0.0 | 0.0 | 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