Wisconsin
2024 Team Stats (36 games)
74.7
PPG
70.0
Opp
+4.7
Margin
46.1%
FG%
34.9%
3P%
75.5%
FT%
34.0
RPG
12.7
APG
9.9
TO
-
Est. poss./game
78.1
Adj PPG
64.2
Adj Opp PPG
#23
Scoring Rank
Model Outputs
2023-2024
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 โ | 1229 (#50) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 1213 (#38) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 1055 (#89) | HCA +77 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | +15.1 (#22) | HCA +2.6 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | +14.5 (#23) | HCA +2.3 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.677 (#80) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.924 (#21) | AdjNet +21.7 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.926 (#21) | AdjNet +21.9 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.779 (#23) | AdjO 78.1 | AdjD 64.2 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.679 (#29) | AdjO 75.9 | AdjD 67.7 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.804 (#29) | 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 โ | 0.788 (#31) | Blend of Elo, BT, Margin, PythLog, PtsOD |
| Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. More โ | 1189 (#57) | RD 106 | GP 36 |
2024 Schedule & Results
2024 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 GP | PM/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
AJ Storr
|
G | 36 | 28.8 | 16.8 | 3.9 | 0.9 | 0.6 | 0.1 | 1.6 | 13.8 | 7.0 | 136 | 35 | 3.9 | 5.4 | 43.4 | 32.0 | 81.2 | 2.07 | 53.5 | 48.2 |
Steven Crowl
|
- | 36 | 29.0 | 11.2 | 7.2 | 2.1 | 0.3 | 0.5 | 1.7 | 7.8 | 11.9 | 156 | 35 | 4.5 | 6.1 | 55.6 | 44.8 | 74.2 | -0.29 | 63.2 | 60.2 |
Tyler Wahl
|
- | 36 | 28.4 | 10.6 | 5.4 | 1.9 | 1.1 | 0.6 | 1.7 | 7.6 | 10.3 | 130 | 35 | 3.7 | 5.3 | 53.5 | 18.8 | 65.9 | 2.23 | 57.7 | 54.0 |
Max Klesmit
|
- | 36 | 28.6 | 9.9 | 2.1 | 1.9 | 0.9 | 0.1 | 1.1 | 7.5 | 6.3 | 141 | 35 | 4.0 | 5.7 | 43.7 | 39.8 | 82.4 | 3.25 | 59.7 | 55.9 |
Chucky Hepburn
|
- | 35 | 33.3 | 9.2 | 3.3 | 3.9 | 2.1 | 0.1 | 1.2 | 7.7 | 9.8 | 156 | 34 | 4.6 | 5.6 | 42.9 | 32.2 | 73.7 | 3.26 | 53.6 | 49.8 |
John Blackwell
|
- | 34 | 18.5 | 8.0 | 3.2 | 0.6 | 0.4 | 0.1 | 0.8 | 5.4 | 6.1 | 83 | 33 | 2.5 | 5.5 | 44.6 | 45.5 | 82.1 | 0.37 | 60.2 | 52.7 |
Connor Essegian
|
G | 33 | 7.3 | 3.2 | 0.8 | 0.2 | 0.1 | 0.0 | 0.4 | 2.9 | 1.1 | 16 | 32 | 0.5 | 2.7 | 38.5 | 30.3 | 90.9 | -0.81 | 51.6 | 49.0 |
Nolan Winter
|
- | 36 | 9.4 | 2.4 | 1.8 | 0.3 | 0.2 | 0.0 | 0.3 | 2.0 | 2.5 | 2 | 35 | 0.1 | 0.2 | 42.3 | 30.8 | 69.6 | -2.98 | 54.2 | 50.7 |
Kamari Mcgee
|
- | 25 | 8.4 | 2.1 | 0.8 | 0.4 | 0.5 | 0.0 | 0.3 | 1.4 | 2.2 | 95 | 25 | 3.8 | 18.7 | 54.3 | 27.3 | 61.1 | 4.03 | 60.6 | 58.6 |
Carter Gilmore
|
- | 33 | 9.2 | 1.8 | 1.4 | 0.5 | 0.1 | 0.0 | 0.5 | 1.2 | 2.2 | 70 | 31 | 2.3 | 9.4 | 48.7 | 25.0 | 79.2 | 2.4 | 60.5 | 52.6 |
Markus Ilver
|
- | 27 | 5.9 | 1.1 | 1.3 | 0.2 | 0.2 | 0.1 | 0.2 | 1.3 | 1.4 | 1 | 26 | 0.0 | 0.3 | 31.4 | 25.0 | 66.7 | -2.12 | 42.7 | 41.4 |
Isaac Lindsey
|
- | 16 | 3.8 | 0.6 | 0.4 | 0.2 | 0.1 | 0.1 | 0.2 | 0.8 | 0.3 | -13 | 15 | -0.9 | -8.9 | 30.8 | 14.3 | 50.0 | -2.94 | 36.0 | 34.6 |
Chris Hodges
|
- | 11 | 2.0 | 0.1 | 0.5 | 0.2 | 0.0 | 0.3 | 0.0 | 0.4 | 0.7 | -21 | 10 | -2.1 | -40.6 | 0.0 | 0 | 25.0 | -4.27 | 8.7 | 0.0 |
Luke Haertle
|
- | 11 | 1.0 | 0.0 | 0.2 | 0.0 | 0.0 | 0.0 | 0.1 | 0.1 | 0.0 | -11 | 9 | -1.2 | -40.5 | 0.0 | 0 | 0 | -2.47 | 0.0 | 0.0 |
Isaac Gard
|
- | 6 | 0.8 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2 | -0.2 | -11 | 6 | -1.8 | -80.7 | 0.0 | 0 | 0 | -2.71 | 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