Purdue
2022 Team Stats (28 games)
77.8
PPG
68.4
Opp
+11.0
Margin
48.4%
FG%
37.4%
3P%
71.6%
FT%
38.5
RPG
15.2
APG
12.0
TO
77.6
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 → | 1665 (#3) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1633 (#1) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +44.2 (#5) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.772 (#12) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.817 (#33) | NetEff +14.0 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.870 (#9) | AdjNet +16.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.872 (#9) | AdjNet +16.6 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
J. Ivey
|
- | 32 | 31.4 | 16.9 | 4.6 | 3.1 | 0.9 | 0.5 | 2.7 | 11.8 | 11.5 | - | - | - | 45.2 | 32.7 | 74.5 | - | 58.9 | 51.7 |
Zach Edey
|
- | 37 | 19.0 | 14.4 | 7.7 | 1.2 | 0.2 | 1.2 | 1.7 | 7.8 | 15.3 | - | - | - | 64.6 | 0 | 64.7 | - | 74.7 | 64.6 |
T. Williams
|
F | 33 | 20.0 | 11.6 | 7.5 | 2.9 | 0.9 | 0.5 | 2.1 | 8.9 | 12.5 | 40 | 13.3 | 19.4 | 52.2 | 38.5 | 60.0 | 0.87 | 55.8 | 53.1 |
S. Stefanovic
|
G | 33 | 30.8 | 10.0 | 2.5 | 2.7 | 0.4 | 0.2 | 1.2 | 7.8 | 6.9 | - | - | - | 37.0 | 35.7 | 83.9 | - | 58.6 | 50.6 |
E. Hunter Jr.
|
- | 32 | 26.5 | 6.7 | 2.3 | 2.1 | 0.6 | 0.0 | 1.2 | 4.9 | 5.6 | 69 | 6.9 | 36.3 | 46.8 | 47.1 | 70.0 | 1.02 | 59.8 | 57.1 |
Mason Gillis
|
F | 33 | 23.5 | 6.4 | 4.8 | 1.1 | 0.4 | 0.2 | 0.8 | 3.9 | 8.1 | - | - | - | 49.2 | 42.2 | 81.2 | - | 72.9 | 62.7 |
B. Newman
|
G | 21 | 12.8 | 4.9 | 1.8 | 0.5 | 0.4 | 0.2 | 0.5 | 3.9 | 3.4 | - | - | - | 33.3 | 36.1 | 80.0 | - | 58.2 | 46.9 |
Caleb Furst
|
F | 34 | 14.6 | 4.1 | 3.2 | 0.4 | 0.2 | 0.2 | 0.6 | 1.9 | 5.6 | - | - | - | 57.6 | 42.1 | 72.5 | - | 82.5 | 63.6 |
Isaiah Thompson
|
- | 32 | 15.8 | 3.7 | 1.0 | 0.8 | 0.1 | 0.1 | 0.4 | 2.8 | 2.5 | - | - | - | 40.9 | 38.2 | 77.8 | - | 59.6 | 55.7 |
Ethan Morton
|
G | 37 | 14.8 | 2.4 | 1.4 | 1.4 | 0.6 | 0.2 | 0.5 | 1.5 | 4.1 | - | - | - | 46.3 | 45.2 | 64.3 | - | 74.8 | 59.3 |
M. Frost
|
F | 7 | 2.0 | 0.6 | 0.4 | 0.0 | 0.1 | 0.0 | 0.1 | 0.7 | 0.3 | - | - | - | 20.0 | 0 | 100.0 | - | 34.0 | 20.0 |
C. Barrett
|
- | 9 | 2.1 | 0.4 | 0.7 | 0.1 | 0.0 | 0.0 | 0.4 | 0.8 | 0.0 | - | - | - | 28.6 | 0.0 | 0.0 | - | 26.9 | 28.6 |
J. Wulbrun
|
G | 9 | 2.0 | 0.2 | 0.1 | 0.0 | 0.0 | 0.0 | 0.2 | 0.2 | -0.1 | - | - | - | 0.0 | 0.0 | 100.0 | - | 34.7 | 0.0 |
C. Martin
|
G | 8 | 2.0 | 0.2 | 0.2 | 0.1 | 0.1 | 0.0 | 0.2 | 0.2 | 0.2 | -12 | -1.3 | -3.3 | 50.0 | 0 | 0.0 | 0.37 | 30.1 | 50.0 |
B. Waddell
|
F | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | -16 | -1.2 | -1.4 | - | - | - | 0.78 | - | - |
T. Kaufman-Renn
|
F | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | -8 | -0.7 | -1.1 | - | - | - | 0.69 | - | - |
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