Wisconsin
2023 Team Stats (27 games)
64.6
PPG
65.3
Opp
+0.4
Margin
41.4%
FG%
33.4%
3P%
68.2%
FT%
31.0
RPG
11.2
APG
7.9
TO
71.2
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 → | 1457 (#21) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1388 (#35) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +38.8 (#28) | HCA +2.8 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.548 (#47) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.504 (#171) | NetEff +0.1 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.703 (#38) | AdjNet +7.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.704 (#38) | AdjNet +7.5 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Steven Crowl
|
- | 27 | 31.1 | 13.0 | 7.0 | 2.5 | 0.4 | 0.4 | 1.7 | 9.2 | 12.4 | - | - | - | 53.6 | 32.8 | 63.0 | 0.16 | 64.6 | 57.5 |
Chucky Hepburn
|
- | 27 | 32.0 | 12.6 | 2.4 | 2.9 | 1.4 | 0.1 | 1.5 | 9.9 | 8.0 | - | - | - | 37.6 | 41.3 | 74.1 | - | 58.1 | 45.7 |
C. Essegian
|
G | 27 | 28.4 | 12.3 | 3.8 | 0.8 | 0.5 | 0.0 | 1.0 | 8.8 | 7.6 | - | - | - | 41.4 | 35.6 | 87.5 | - | 62.6 | 51.5 |
Tyler Wahl
|
- | 24 | 31.1 | 11.3 | 5.7 | 2.4 | 1.2 | 0.5 | 1.9 | 8.5 | 10.8 | - | - | - | 41.4 | 38.9 | 58.5 | - | 56.9 | 43.1 |
Max Klesmit
|
- | 25 | 32.3 | 8.8 | 2.5 | 1.4 | 1.4 | 0.2 | 0.8 | 6.4 | 7.0 | - | - | - | 42.5 | 37.9 | 67.3 | 0.16 | 59.9 | 52.8 |
J. Davis
|
G | 27 | 19.8 | 4.6 | 3.4 | 0.4 | 0.3 | 0.1 | 0.3 | 3.8 | 4.7 | 111 | 5.0 | 8.4 | 37.9 | 28.8 | 50.0 | 2.04 | 58.7 | 47.1 |
Carter Gilmore
|
- | 27 | 19.4 | 2.6 | 2.5 | 1.0 | 0.5 | 0.2 | 0.3 | 2.3 | 4.2 | - | - | - | 41.9 | 23.5 | 54.5 | - | 48.8 | 45.2 |
I. Lindsey
|
- | 17 | 6.1 | 1.2 | 0.8 | 0.0 | 0.1 | 0.1 | 0.1 | 1.4 | 0.6 | - | - | - | 26.1 | 33.3 | 50.0 | - | 41.9 | 34.8 |
Markus Ilver
|
- | 12 | 6.8 | 1.2 | 0.9 | 0.2 | 0.0 | 0.0 | 0.0 | 2.2 | 0.0 | - | - | - | 22.2 | 14.3 | 0 | - | 25.9 | 25.9 |
Kamari Mcgee
|
- | 25 | 7.1 | 1.2 | 0.6 | 0.4 | 0.2 | 0.0 | 0.2 | 1.5 | 0.8 | - | - | - | 24.3 | 5.9 | 87.5 | - | 38.3 | 25.7 |
C. Hodges
|
- | 10 | 2.4 | 0.2 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2 | 0.3 | -71 | -5.9 | -7.9 | 50.0 | 0 | 0 | -0.13 | 50.0 | 50.0 |
L. Haertle
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | -6 | -0.8 | -4.0 | - | - | - | -0.04 | - | - |
I. Gard
|
- | 3 | 1.3 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3 | -0.3 | - | - | - | 0.0 | 0.0 | 0 | - | 0.0 | 0.0 |
R. Candelino
|
- | 2 | 1.5 | 0.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | 52 | 4.3 | 8.2 | 0 | 0 | 0 | 1.28 | 0 | 0 |
J. Taphorn
|
- | 3 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 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