Yale
2024 Team Stats (33 games)
74.7
PPG
67.5
Opp
+7.2
Margin
46.7%
FG%
35.1%
3P%
70.7%
FT%
36.5
RPG
15.0
APG
9.6
TO
76.5
Pace
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 → | 1295 (#52) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1284 (#73) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +30.2 (#89) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.686 (#19) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.665 (#92) | NetEff +6.4 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.439 (#75) | AdjNet -2.1 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.439 (#75) | AdjNet -2.1 |
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/G | PM/40 | FG% | 3P% | FT% | RAPM | TS% | eFG% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Danny Wolf
|
- | 32 | 30.8 | 14.1 | 9.7 | 2.4 | 1.0 | 1.3 | 2.3 | 11.7 | 14.6 | 26 | 2.4 | 5.1 | 47.2 | 34.5 | 71.7 | -0.18 | 54.3 | 51.1 |
John Poulakidas
|
- | 33 | 31.0 | 13.4 | 2.3 | 1.9 | 0.5 | 0.4 | 0.9 | 10.5 | 7.1 | 122 | 8.7 | 24.2 | 44.7 | 40.5 | 76.6 | 0.08 | 58.9 | 56.6 |
Matt Knowling
|
- | 28 | 28.2 | 11.6 | 4.9 | 2.6 | 0.5 | 0.3 | 0.9 | 8.8 | 10.2 | 16 | 1.8 | 4.2 | 56.7 | 14.3 | 60.8 | -0.01 | 58.4 | 56.9 |
Bez Mbeng
|
- | 33 | 32.4 | 11.1 | 4.2 | 4.1 | 1.9 | 0.3 | 1.8 | 9.4 | 10.3 | 34 | 2.6 | 6.3 | 42.1 | 25.2 | 68.6 | -0.34 | 51.4 | 47.4 |
August Mahoney
|
- | 33 | 27.1 | 10.3 | 2.5 | 1.3 | 0.6 | 0.1 | 0.9 | 6.9 | 7.0 | 38 | 3.5 | 8.5 | 47.8 | 45.3 | 85.0 | -0.1 | 67.0 | 63.6 |
N. Townsend
|
- | 33 | 17.7 | 6.0 | 3.9 | 1.1 | 0.4 | 0.1 | 0.7 | 5.0 | 5.8 | 89 | 4.0 | 36.2 | 44.8 | 29.6 | 79.6 | -0.41 | 52.7 | 47.3 |
C. Simmons
|
- | 32 | 13.3 | 3.5 | 2.0 | 0.2 | 0.5 | 0.2 | 0.5 | 2.8 | 3.1 | 48 | 2.5 | 40.4 | 51.1 | 23.5 | 56.7 | -0.22 | 54.8 | 53.4 |
L. Kolaja
|
- | 2 | 5.0 | 3.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | 2.0 | 0.5 | - | - | - | 75.0 | 0.0 | 0 | - | 75.0 | 75.0 |
Y. Gharram
|
- | 33 | 13.9 | 2.5 | 2.1 | 1.3 | 0.3 | 0.1 | 0.7 | 2.5 | 3.2 | 34 | 2.4 | 19.4 | 39.5 | 15.8 | 59.3 | -0.25 | 44.7 | 41.4 |
S. Aletan
|
- | 21 | 7.2 | 2.2 | 1.5 | 0.2 | 0.2 | 0.5 | 0.4 | 1.3 | 3.0 | 68 | 4.2 | 214.7 | 63.0 | 0 | 63.2 | -0.05 | 65.0 | 63.0 |
Jack Molloy
|
- | 18 | 5.9 | 1.7 | 1.4 | 0.1 | 0.1 | 0.1 | 0.2 | 1.8 | 1.4 | 9 | 1.5 | 26.7 | 36.4 | 26.7 | 100.0 | 0.16 | 45.2 | 42.4 |
D. Arlington
|
- | 7 | 3.1 | 1.6 | 0.3 | 0.1 | 0.3 | 0.0 | 0.3 | 1.6 | 0.4 | - | - | - | 45.5 | 33.3 | 0.0 | - | 48.1 | 50.0 |
Teo Rice
|
- | 11 | 4.2 | 1.5 | 0.9 | 0.5 | 0.3 | 0.1 | 0.2 | 1.5 | 1.5 | 1 | 0.2 | 15.6 | 35.3 | 14.3 | 75.0 | 0.01 | 42.6 | 38.2 |
T. Mullin
|
- | 10 | 3.7 | 1.5 | 0.4 | 0.1 | 0.2 | 0.0 | 0.1 | 1.7 | 0.4 | 17 | 1.4 | 370.9 | 29.4 | 28.6 | 75.0 | -0.02 | 40.0 | 35.3 |
Y. Basa-Ama
|
F | 14 | 4.1 | 1.1 | 1.1 | 0.4 | 0.3 | 0.1 | 0.0 | 1.0 | 1.9 | 6 | 1.0 | 65.2 | 50.0 | 0.0 | 50.0 | 0.01 | 50.4 | 50.0 |
E. Buyukhanli
|
- | 8 | 4.6 | 0.8 | 0.9 | 0.1 | 0.5 | 0.0 | 0.2 | 1.0 | 1.0 | -4 | -1.3 | -74.4 | 37.5 | 0.0 | 0 | 0.01 | 37.5 | 37.5 |
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