Gonzaga
2024 Team Stats (35 games)
84.5
PPG
69.1
Opp
+15.4
Margin
51.8%
FG%
36.1%
3P%
72.1%
FT%
38.7
RPG
16.7
APG
9.8
TO
79.8
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 → | 1487 (#12) | - |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → | 1474 (#11) | - |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More → | +45.1 (#8) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → | 0.827 (#5) | - |
| Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. More → | 0.891 (#8) | NetEff +19.7 |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More → | 0.826 (#11) | AdjNet +13.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More → | 0.828 (#11) | AdjNet +13.6 |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
G. Ike
|
- | 35 | 24.2 | 16.5 | 7.4 | 0.9 | 0.6 | 0.7 | 1.6 | 10.9 | 13.6 | 171 | 6.8 | 33.1 | 60.9 | 36.8 | 78.4 | 0.92 | 65.5 | 61.8 |
Anton Watson
|
- | 35 | 31.4 | 14.5 | 7.1 | 2.6 | 1.5 | 0.7 | 1.4 | 10.0 | 15.0 | 100 | 10.0 | 16.0 | 57.8 | 41.2 | 65.3 | 1.04 | 62.6 | 60.8 |
Nolan Hickman
|
- | 35 | 35.3 | 14.0 | 2.3 | 2.7 | 1.0 | 0.3 | 1.3 | 10.9 | 8.0 | 89 | 6.8 | 13.3 | 47.1 | 41.3 | 88.3 | 0.95 | 60.2 | 57.4 |
Ryan Nembhard
|
- | 35 | 35.8 | 12.6 | 4.0 | 6.9 | 1.2 | 0.0 | 2.3 | 10.6 | 11.8 | 107 | 8.2 | 15.6 | 44.5 | 32.1 | 75.2 | 0.92 | 53.1 | 49.2 |
B. Huff
|
- | 35 | 13.3 | 9.3 | 3.4 | 0.5 | 0.3 | 0.7 | 0.4 | 6.5 | 7.3 | -2 | -0.2 | -1.3 | 59.8 | 33.8 | 55.4 | 0.02 | 64.5 | 64.6 |
Ben Gregg
|
- | 35 | 23.6 | 9.0 | 5.7 | 1.2 | 1.2 | 0.7 | 0.7 | 5.6 | 11.4 | 86 | 8.6 | 15.8 | 54.1 | 37.7 | 72.9 | 0.73 | 67.3 | 64.3 |
D. Stromer
|
- | 35 | 23.5 | 4.8 | 3.3 | 1.1 | 0.6 | 0.5 | 0.9 | 4.0 | 5.5 | 69 | 6.9 | 20.3 | 37.1 | 35.8 | 81.1 | 0.41 | 53.7 | 49.3 |
L. Krajnovic
|
- | 16 | 8.2 | 2.9 | 1.3 | 0.6 | 0.4 | 0.1 | 0.9 | 1.9 | 2.4 | -17 | -3.4 | -31.4 | 46.7 | 33.3 | 78.9 | -0.38 | 60.0 | 51.7 |
J. Yeo
|
- | 25 | 6.9 | 2.3 | 1.2 | 0.2 | 0.1 | 0.2 | 0.3 | 1.8 | 1.9 | -14 | -2.8 | -71.2 | 43.5 | 13.6 | 66.7 | -0.25 | 51.6 | 46.7 |
P. Stošic
|
- | 14 | 3.3 | 1.0 | 0.8 | 0.1 | 0.1 | 0.2 | 0.4 | 1.1 | 0.7 | - | - | - | 37.5 | 0.0 | 50.0 | - | 39.4 | 37.5 |
C. Brooks
|
- | 14 | 2.9 | 1.0 | 1.2 | 0.1 | 0.0 | 0.0 | 0.1 | 1.1 | 1.1 | -12 | -2.4 | -64.1 | 33.3 | 0.0 | 44.4 | -0.2 | 36.9 | 33.3 |
Joe Few
|
- | 15 | 3.9 | 0.3 | 0.3 | 0.5 | 0.2 | 0.1 | 0.2 | 0.5 | 0.8 | -14 | -2.8 | -71.2 | 14.3 | 0.0 | 30.0 | -0.25 | 21.9 | 14.3 |
D. Harris
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | -28 | -3.1 | -12.9 | - | - | - | -0.24 | - | - |
S. Venters
|
G | 0 | - | 0.0 | 0.0 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
J. ArauzMoore
|
G | 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