🐻⬇️🏀

Wagner Seahawks

Also known as: Wagner Seahawks
Program History

2022 Team Stats (2 games)

53.0
PPG
64.9
Opp
+9.9
Margin
35.2%
FG%
19.5%
3P%
70.6%
FT%
29.5
RPG
11.0
APG
15.5
TO
80.2
Pace

Model Outputs

2021-2022
Catalog

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 → 856 (#719) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1062 (#269) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +115 elo More → 1084 (#72) HCA +115 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.7 More → +17.1 (#277) HCA +2.7
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.4 More → +10.9 (#190) HCA +2.4
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -33.7 More → 0.012 (#328) NetEff -33.7
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 70.1 | AdjD 65.2 More → 0.609 (#116) AdjO 70.1 | AdjD 65.2
Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.768 (#142) 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. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.741 (#141) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 151 | GP 24 More → 1119 (#131) RD 151 | GP 24

2022 Schedule & Results

2022 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%
R. Rogers R. Rogers F 2 23.5 13.5 4.0 0.0 0.5 0.0 2.0 8.5 7.5 218 8.1 14.2 76.5 0.0 50.0 1.63 75.5 76.5
E. Ford E. Ford G 1 30.0 12.0 5.0 1.0 2.0 0.0 3.0 13.0 4.0 196 10.9 16.0 46.2 0.0 0 1.53 46.2 46.2
D. Hunt D. Hunt - 22 30.7 9.0 2.8 2.6 1.1 0.0 1.0 2.8 11.7 152 6.1 8.0 50.0 41.9 66.7 0.0 140.9 60.5
W. Martinez W. Martinez G 1 31.0 7.0 5.0 2.0 2.0 0.0 3.0 8.0 5.0 191 7.3 10.9 37.5 0.0 50.0 1.15 39.4 37.5
Z. Williams Z. Williams - 24 22.3 6.1 2.3 1.0 1.4 0.2 1.1 3.0 6.8 117 4.3 7.7 34.2 31.4 75.0 0.76 91.2 45.2
J. Price-Noel J. Price-Noel - 16 22.2 5.9 3.0 1.2 0.4 0.0 0.5 3.0 7.0 10 0.6 1.1 37.5 32.3 75.0 -0.98 88.2 47.9
J. Fletcher J. Fletcher - 24 12.6 3.6 3.2 0.2 0.3 0.4 0.2 0.9 6.6 58 2.1 7.1 54.5 0.0 75.0 0.16 159.5 54.5
N. Jackson N. Jackson F 2 11.5 3.0 1.0 0.0 0.0 0.0 0.5 3.0 0.5 33 2.4 7.9 33.3 33.3 0 0.79 50.0 50.0
A. Morales A. Morales - 1 35.0 3.0 8.0 2.0 1.0 2.0 3.0 16.0 -3.0 220 8.5 10.4 0.0 0.0 60.0 0.8 8.2 0.0
R. Taylor II R. Taylor II - 17 4.2 2.6 1.3 0.1 0.1 0.1 0.2 0.5 3.5 -11 -0.6 -5.7 75.0 0 80.0 -0.36 181.5 75.0
Javier Ezquerra Javier Ezquerra - 24 11.8 1.8 1.2 1.2 0.5 0.0 1.1 1.1 2.5 81 3.4 11.2 18.5 18.8 0 0.75 77.8 24.1
J. Mason J. Mason - 10 2.0 0.6 0.1 0.0 0.0 0.0 0.3 0.2 0.2 - - - 0.0 0.0 0 - 150.0 0.0
A. Miller A. Miller G 1 22.0 0.0 5.0 3.0 2.0 0.0 4.0 2.0 4.0 60 5.5 15.1 0.0 0 0 0.58 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