Pittsburgh
2023 Team Stats (17 games)
76.8
PPG
70.0
Opp
+3.8
Margin
45.7%
FG%
35.8%
3P%
78.2%
FT%
34.8
RPG
14.3
APG
9.8
TO
75.9
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 → | 1235 (#96) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1366 (#41) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +37.1 (#40) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.664 (#21) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.774 (#33) | NetEff +11.6 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.622 (#50) | AdjNet +4.3 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.622 (#50) | AdjNet +4.3 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
J. Hugley IV
|
F | 1 | 19.0 | 17.0 | 5.0 | 0.0 | 0.0 | 2.0 | 3.0 | 10.0 | 11.0 | 35 | 5.0 | 12.1 | 70.0 | 33.3 | 100.0 | 0.93 | 78.1 | 75.0 |
Blake Hinson
|
- | 24 | 31.3 | 13.9 | 5.3 | 1.0 | 0.5 | 0.5 | 1.4 | 11.0 | 8.8 | - | - | - | 40.4 | 40.2 | 60.0 | - | 56.3 | 54.0 |
N. Cummings
|
- | 24 | 32.4 | 11.0 | 2.3 | 4.6 | 0.8 | 0.0 | 2.1 | 8.9 | 7.7 | - | - | - | 40.2 | 34.6 | 88.7 | - | 55.4 | 48.6 |
G. Elliott
|
- | 24 | 29.6 | 9.7 | 3.8 | 1.2 | 0.8 | 0.1 | 0.8 | 6.5 | 8.4 | - | - | - | 41.0 | 42.2 | 87.0 | - | 64.8 | 55.8 |
N. Sibande
|
- | 24 | 23.5 | 9.3 | 4.2 | 1.0 | 0.5 | 0.2 | 1.0 | 6.9 | 7.4 | - | - | - | 46.7 | 38.6 | 72.5 | - | 59.5 | 56.4 |
F. Federiko
|
- | 23 | 24.8 | 6.3 | 5.0 | 0.4 | 0.5 | 1.7 | 0.8 | 3.7 | 9.3 | 20 | 1.8 | 5.3 | 65.1 | 0 | 67.5 | 0.78 | 69.5 | 65.1 |
G. Diaz Graham
|
F | 23 | 12.9 | 3.7 | 3.1 | 0.7 | 0.4 | 1.0 | 0.5 | 2.7 | 5.8 | 51 | 2.8 | 4.3 | 44.3 | 28.6 | 71.4 | 1.37 | 56.3 | 49.2 |
J. Diaz Graham
|
F | 20 | 6.7 | 2.4 | 1.8 | 0.2 | 0.2 | 0.4 | 0.2 | 1.4 | 3.4 | 81 | 6.8 | 11.0 | 44.4 | 28.6 | 90.0 | 1.78 | 67.0 | 51.9 |
Nate Santos
|
F | 17 | 6.5 | 1.4 | 0.9 | 0.2 | 0.2 | 0.1 | 0.2 | 1.4 | 1.3 | - | - | - | 34.8 | 15.4 | 83.3 | - | 44.9 | 39.1 |
KJ Marshall
|
- | 4 | 3.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.8 | 0.2 | - | - | - | 0.0 | 0.0 | 66.7 | - | 35.5 | 0.0 |
A. Fisch
|
- | 5 | 2.6 | 0.8 | 0.4 | 0.0 | 0.0 | 0.0 | 0.2 | 1.0 | 0.0 | - | - | - | 40.0 | 0.0 | 0 | - | 40.0 | 40.0 |
N. Collier
|
F | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | 0.05 | - | - |
D. Johnson
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | 20 | 1.8 | 4.8 | - | - | - | 0.94 | - | - |
W. Jeffress
|
F | 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