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Utah Valley

Also known as: Utah Valley Wolverines
Program History

2013 Team Stats (1 games)

96.0
PPG
70.0
Opp
+26.0
Margin
58.6%
FG%
43.8%
3P%
77.8%
FT%
32.0
RPG
20.0
APG
14.0
TO
-
Est. poss./game
62.0
Adj PPG
70.2
Adj Opp PPG
#286
Scoring Rank

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 โ†’ 760 (#291) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ†’ 839 (#288) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +102 elo More โ†’ 923 (#276) HCA +102 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +3.1 More โ†’ -9.0 (#290) HCA +3.1
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +3.2 More โ†’ -9.2 (#297) HCA +3.2
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ†’ 0.321 (#253) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -15.2 More โ†’ 0.148 (#303) AdjNet -15.2
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -15.3 More โ†’ 0.146 (#303) AdjNet -15.3
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 62.0 | AdjD 70.2 More โ†’ 0.322 (#286) AdjO 62.0 | AdjD 70.2
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 63.4 | AdjD 68.3 More โ†’ 0.392 (#274) AdjO 63.4 | AdjD 68.3
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 โ†’ 0.262 (#294) 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 โ†’ 0.274 (#295) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 139 | GP 28 More โ†’ 810 (#295) RD 139 | GP 28

2013 Schedule & Results

Date Vs/At Opponent Result Score
2012-11-09 @ IUPUI Jaguars L 54 - 67
2012-11-12 @ North Carolina A&T Aggies W 64 - 55
2012-11-14 @ Washington State Cougars L 49 - 72
2012-11-17 vs Arizona Christian Firestorm W 96 - 70
2012-11-20 @ Eastern Washington Eagles W 86 - 83
2012-11-21 @ Santa Clara Broncos L 67 - 75
2012-11-23 vs South Carolina Upstate Spartans L 50 - 75
2012-11-27 @ North Carolina Central Eagles L 52 - 70
2012-12-01 vs Pepperdine Waves W 67 - 63
2012-12-05 @ Weber State Wildcats L 56 - 89
2012-12-08 @ Troy Trojans W 86 - 82
2012-12-15 vs Utah State Aggies L 63 - 69
2012-12-19 vs Troy Trojans W 67 - 64
2012-12-22 vs North Carolina Central Eagles L 67 - 73
2012-12-28 @ Austin Peay Governors W 84 - 77
2012-12-29 @ Chattanooga Mocs L 69 - 76
2013-01-05 vs NJIT Highlanders L 52 - 57
2013-01-09 @ Kansas City Roos W 78 - 66
2013-01-12 vs Houston Christian Huskies W 83 - 62
2013-01-19 @ UT Rio Grande Valley Vaqueros L 60 - 62
2013-01-26 @ Chicago State Cougars L 54 - 62
2013-01-28 vs Peru State College Bobcats W 84 - 49
2013-02-02 @ Cal State Bakersfield Roadrunners L 62 - 75
2013-02-09 vs UT Rio Grande Valley Vaqueros W 66 - 49
2013-02-11 vs Northern New Mexico Eagles W 86 - 63
2013-02-16 @ NJIT Highlanders L 55 - 63
2013-02-18 vs Pacific Union Pioneers W 73 - 43
2013-02-23 @ Houston Christian Huskies L 63 - 73
2013-02-26 @ North Dakota State Bison L 56 - 63
2013-03-02 vs Chicago State Cougars W 76 - 69
2013-03-09 vs Cal State Bakersfield Roadrunners L 58 - 73
2013-03-14 @ Houston Christian Huskies L 74 - 76

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 GP PM/G PM/40 FG% 3P% FT% RAPM TS% eFG%
Ben Aird Ben Aird C 30 33.6 15.1 9.0 0.9 0.8 1.9 1.2 0.6 26.0 -82 20 -4.1 -4.8 55.6 0.0 75.0 -2.27 1146.3 55.6
Holton Hunsaker Holton Hunsaker G 32 33.4 13.2 2.2 3.1 1.4 0.0 2.3 0.6 16.8 -60 20 -3.0 -3.6 35.0 25.0 75.0 0.01 895.0 42.5
Alfonzo Hubbard Alfonzo Hubbard F 19 28.9 11.6 4.7 1.8 0.8 0.3 1.6 0.8 16.8 -64 12 -5.3 -7.3 53.3 40.0 92.9 -3.48 519.8 60.0
Nick Thompson Nick Thompson F 32 32.1 9.9 7.9 4.2 1.0 0.1 3.3 0.6 19.1 -58 20 -2.9 -3.6 60.0 50.0 70.0 0.61 647.5 65.0
Jason Johnson Jason Johnson G 31 28.7 9.7 2.7 2.0 0.9 0.1 1.5 0.4 13.6 -19 19 -1.0 -1.4 63.6 60.0 0 2.69 1372.7 77.3
Antoine Hosley Antoine Hosley G 28 18.0 6.1 1.2 0.8 0.6 0.0 1.3 0.2 7.3 -83 16 -5.2 -12.4 33.3 50.0 0 -5.02 1433.3 41.7
Zach Jones Zach Jones F 30 13.8 3.8 2.4 0.5 0.4 0.5 0.4 0.1 7.0 -85 19 -4.5 -14.3 50.0 0 0 -5.34 2825.0 50.0
Keawe Enos Keawe Enos G 30 13.1 2.8 0.7 0.9 0.3 0.0 0.7 0.2 3.9 -40 18 -2.2 -8.5 60.0 50.0 100.0 -1.47 714.3 80.0
Taylor Brown Taylor Brown G 32 17.0 2.1 1.5 1.0 0.6 0.2 0.5 0.2 4.5 -59 20 -3.0 -7.6 62.5 40.0 60.0 -4.77 328.4 75.0
Will Sinclair Will Sinclair C 27 5.6 0.3 1.1 0.1 0.0 0.3 0.3 0.0 1.7 0 15 0.0 0.0 0 0 0 0.83 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