Weber State
2019 Team Stats (4 games)
74.3
PPG
-
Opp
-
Margin
45.5%
FG%
38.0%
3P%
70.8%
FT%
35.8
RPG
11.3
APG
13.3
TO
-
Est. poss./game
72.1
Adj PPG
75.0
Adj Opp PPG
#212
Scoring Rank
Model Outputs
2018-2019
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 | Data withheld: source-integrity hold | Historical Elo fit predates the season cutoff fix and has no verified season-bounded input receipt. |
| Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ | 969 (#197) | - |
| Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. More โ | 976 (#206) | HCA +83 elo |
| Margin Margin Linear team-strength model fit on point differential instead of binary wins. More โ | -3.6 (#215) | HCA +2.8 |
| Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. More โ | -4.8 (#246) | HCA +2.7 |
| Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ | 0.565 (#136) | - |
| Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. More โ | 0.348 (#219) | AdjNet -5.5 |
| Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. More โ | 0.345 (#220) | AdjNet -5.6 |
| Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. More โ | 0.435 (#212) | AdjO 72.1 | AdjD 75.0 |
| Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. More โ | 0.472 (#203) | AdjO 71.8 | AdjD 73.0 |
| Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. More โ | 0.406 (#222) | 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 | 0.414 (#221) | 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 | 933 (#225) | RD 129 | GP 31 |
2019 Schedule & Results
2019 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Jerrick Harding
|
G | 27 | 33.7 | 21.4 | 3.4 | 1.4 | 1.6 | 0.4 | 2.2 | 2.8 | 23.1 | 87 | 23 | 3.8 | 4.8 | 52.6 | 36.7 | 83.9 | -0.94 | 322.4 | 59.9 |
Cody John
|
G | 30 | 31.5 | 15.1 | 3.7 | 2.0 | 0.5 | 0.2 | 1.9 | 2.0 | 17.5 | 61 | 24 | 2.5 | 3.4 | 49.2 | 20.0 | 77.8 | -0.78 | 359.0 | 51.7 |
Brekkott Chapman
|
F | 30 | 29.3 | 12.8 | 8.4 | 2.1 | 1.0 | 1.6 | 1.9 | 1.9 | 22.1 | 142 | 24 | 5.9 | 8.2 | 56.1 | 56.7 | 60.0 | 3.73 | 301.9 | 71.1 |
Zach Braxton
|
C | 28 | 24.1 | 9.9 | 6.8 | 0.8 | 0.5 | 0.7 | 1.6 | 1.3 | 15.7 | 56 | 21 | 2.7 | 4.8 | 59.5 | 0 | 74.3 | -1.18 | 263.4 | 59.5 |
Israel Barnes
|
- | 30 | 24.1 | 6.5 | 2.2 | 1.5 | 0.7 | 0.2 | 1.2 | 1.1 | 8.6 | 68 | 24 | 2.8 | 5.1 | 38.2 | 21.4 | 28.6 | 0.26 | 261.6 | 42.6 |
Caleb Nero
|
- | 30 | 19.1 | 6.3 | 1.7 | 1.5 | 0.6 | 0.1 | 1.1 | 0.8 | 8.3 | 5 | 24 | 0.2 | 0.5 | 33.3 | 18.2 | 50.0 | -1.82 | 379.8 | 37.5 |
Michal Kozak
|
F | 30 | 18.3 | 4.5 | 4.1 | 0.8 | 0.3 | 0.9 | 0.7 | 0.8 | 9.1 | -3 | 24 | -0.1 | -0.3 | 54.2 | 36.4 | 80.0 | -0.62 | 259.5 | 62.5 |
Ricky Nelson
|
- | 20 | 18.8 | 3.5 | 0.9 | 2.0 | 0.5 | 0.0 | 0.9 | 0.7 | 5.2 | -11 | 14 | -0.8 | -2.0 | 28.6 | 33.3 | 78.6 | -2.74 | 171.1 | 32.1 |
Brenden Morris
|
F | 4 | 4.5 | 2.5 | 1.5 | 0.2 | 0.0 | 0.2 | 0.0 | 0.8 | 3.8 | - | - | - | - | 66.7 | 100.0 | 0 | -2.39 | 166.7 | 83.3 |
Dima Zdor
|
- | 25 | 5.8 | 2.3 | 2.0 | 0.0 | 0.0 | 0.4 | 0.2 | 0.1 | 4.5 | -20 | 19 | -1.1 | -9.2 | 100.0 | 0 | 75.0 | -4.85 | 598.7 | 100.0 |
Donatas Kupsas
|
F | 21 | 10.6 | 2.1 | 2.3 | 0.7 | 0.2 | 0.0 | 0.7 | 0.4 | 4.1 | 1 | 17 | 0.1 | 0.3 | 22.2 | 0.0 | 100.0 | -1.26 | 233.1 | 22.2 |
Caleb Leonhardt
|
G | 2 | 3.5 | 1.0 | 1.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.5 | 2.0 | - | - | - | - | 0.0 | 0 | 0 | - | 100.0 | 0.0 |
Alan Lang
|
F | 3 | 3.0 | 0.7 | 0.7 | 0.0 | 0.0 | 0.0 | 0.7 | 0.3 | 0.3 | - | - | - | - | 0.0 | 0 | 0 | -1.5 | 100.0 | 0.0 |
Jordan Dallas
|
C | 5 | 3.6 | 0.4 | 1.2 | 0.2 | 0.0 | 0.0 | 0.4 | 0.0 | 1.4 | - | - | - | - | 0 | 0 | 0 | -2.08 | 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