🐻⬇️🏀

Wagner Seahawks

Also known as: Wagner Seahawks
Program History

2013 Team Stats (2 games)

47.5
PPG
67.1
Opp
+1.8
Margin
31.3%
FG%
26.9%
3P%
59.1%
FT%
38.0
RPG
7.5
APG
24.0
TO
83.2
Pace

Model Outputs

2012-2013
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 → 963 (#599) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1110 (#306) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +147 elo More → 1077 (#74) HCA +147 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +3.0 More → +18.2 (#267) HCA +3.0
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.3 More → +7.0 (#192) HCA +3.3
Efficiency Efficiency Tempo-adjusted efficiency version of Pythagorean ratings. NetEff -19.5 More → 0.045 (#258) NetEff -19.5
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 68.1 | AdjD 66.5 More → 0.537 (#169) AdjO 68.1 | AdjD 66.5
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 → 0.664 (#181) 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 → 0.647 (#173) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 146 | GP 31 More → 1078 (#142) RD 146 | GP 31

2013 Schedule & Results

2013 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%
J. Williams J. Williams F 27 30.4 15.6 6.4 1.0 1.1 0.4 2.5 1.1 20.9 68 2.4 3.2 48.4 33.3 82.4 0.73 548.3 50.0
L. Rivers L. Rivers G 20 29.2 13.0 2.6 1.6 0.8 0.1 2.0 0.2 15.9 63 3.1 5.2 20.0 33.3 0 0.34 2600.0 30.0
K. Ortiz K. Ortiz G 31 33.9 11.8 4.3 5.4 2.0 0.1 3.9 0.8 19.0 40 1.3 1.7 36.0 0.0 50.0 0.15 606.0 36.0
M. Burton M. Burton G 25 23.9 8.6 1.9 2.2 1.2 0.2 1.1 1.0 12.0 84 3.4 5.2 32.0 36.4 60.0 0.74 397.1 40.0
M. Moody M. Moody F 30 16.8 6.9 5.3 0.4 1.0 1.3 1.0 0.3 13.6 5 0.2 0.4 50.0 0 57.1 0.01 934.1 50.0
E. Fanning E. Fanning G 22 16.7 6.4 2.9 0.4 0.5 0.1 1.5 0.3 8.5 22 1.0 2.2 28.6 25.0 57.1 0.08 699.4 35.7
O. Parker O. Parker F 31 20.9 5.5 4.3 0.5 0.8 0.7 0.8 0.4 10.7 79 2.5 4.9 33.3 0 69.2 0.62 485.3 33.3
D. Anderson D. Anderson G 31 15.5 4.2 2.5 0.5 0.6 0.5 1.7 0.5 6.1 63 1.9 3.5 11.8 10.0 0.0 0.0 366.3 14.7
J. Thompson J. Thompson F 30 24.1 3.7 2.9 1.3 0.9 0.5 1.4 0.1 7.8 125 4.3 8.4 0.0 0.0 0 1.04 1375.0 0.0
N. Folahan N. Folahan C 29 14.6 3.0 3.3 0.0 0.0 1.5 0.8 0.2 6.9 23 0.8 2.2 33.3 0 50.0 -0.02 625.0 33.3
H. Naurais H. Naurais F 14 4.8 0.9 1.0 0.2 0.3 0.2 0.4 0.1 2.1 13 0.9 4.0 0.0 0 0 -0.1 300.0 0.0
L. Burnett L. Burnett G 18 4.6 0.7 0.6 0.2 0.1 0.0 0.2 0.1 1.3 14 0.8 3.5 0.0 0 0 0.1 600.0 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