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Utah Valley

Also known as: Utah Valley Wolverines
Program History

2014 Team Stats (16 games)

65.6
PPG
66.7
Opp
-1.1
Margin
42.6%
FG%
35.5%
3P%
74.4%
FT%
32.8
RPG
13.9
APG
10.9
TO
-
Est. poss./game
62.2
Adj PPG
65.5
Adj Opp PPG
#216
Scoring Rank

Model Outputs

2013-2014
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†’ 1030 (#149) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ†’ 1030 (#147) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +92 elo More โ†’ 1034 (#122) HCA +92 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.8 More โ†’ -3.5 (#215) HCA +2.8
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More โ†’ -3.1 (#218) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ†’ 0.467 (#194) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet -5.3 More โ†’ 0.353 (#216) AdjNet -5.3
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet -5.4 More โ†’ 0.348 (#218) AdjNet -5.4
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 62.2 | AdjD 65.5 More โ†’ 0.427 (#216) AdjO 62.2 | AdjD 65.5
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 63.7 | AdjD 65.1 More โ†’ 0.466 (#207) AdjO 63.7 | AdjD 65.1
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†’ 0.462 (#185) 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†’ 0.470 (#183) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 119 | GP 30 More โ†’ 1053 (#132) RD 119 | GP 30

2014 Schedule & Results

Date Vs/At Opponent Result Score
2013-11-08 vs IU Indianapolis Jaguars W 74 - 66
2013-11-11 vs North Carolina A&T Aggies W 78 - 71
2013-11-12 @ Oklahoma State Cowboys L 40 - 93
2013-11-19 @ Oregon Ducks L 54 - 69
2013-11-23 @ Pepperdine Waves L 53 - 58
2013-11-30 @ Tennessee Tech Golden Eagles L 71 - 74
2013-12-02 @ South Dakota Coyotes L 67 - 71
2013-12-07 vs Saint Katherine SAINT KATHERINE W 89 - 37
2013-12-11 vs Weber State Wildcats W 62 - 59
2013-12-14 @ Utah State Aggies L 60 - 71
2013-12-20 vs Haskell Jayhawks W 103 - 64
2013-12-23 vs North Dakota State Bison L 70 - 74
2013-12-28 vs Tennessee Tech Golden Eagles W 75 - 66
2014-01-04 @ Cal State Bakersfield Roadrunners W 82 - 74
2014-01-11 vs Grand Canyon Lopes W 65 - 58
2014-01-16 @ Idaho Vandals W 71 - 66
2014-01-19 @ Seattle U Redhawks W 52 - 51
2014-01-23 vs Kansas City Roos W 66 - 48
2014-01-25 vs Chicago State Cougars W 62 - 55
2014-01-30 @ UT Rio Grande Valley Vaqueros W 67 - 53
2014-02-01 @ New Mexico State Aggies L 49 - 72
2014-02-06 @ Grand Canyon Lopes W 79 - 68
2014-02-13 vs Seattle U Redhawks L 57 - 71
2014-02-15 vs Idaho Vandals W 89 - 88
2014-02-20 @ Chicago State Cougars W 79 - 70
2014-02-22 @ Kansas City Roos L 56 - 74
2014-02-27 vs New Mexico State Aggies W 66 - 61
2014-03-01 vs UT Rio Grande Valley Vaqueros W 45 - 42
2014-03-07 vs Cal State Bakersfield Roadrunners W 64 - 55
2014-03-13 vs UT Rio Grande Valley Vaqueros W 83 - 63
2014-03-14 vs Idaho Vandals L 69 - 74
2014-03-19 @ California Golden Bears L 64 - 77

2014 Roster

Minutes by Position

Each player's share of the team's minutes per game (season minutes over the roster's), placed by position, so every column is one game's minutes. 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%
Holton Hunsaker Holton Hunsaker G 29 33.4 13.6 2.4 4.0 0.9 0.0 2.7 6.5 11.7 -38 28 -1.4 -1.7 33.3 37.5 89.8 -1.72 86.5 43.7
Ben Aird Ben Aird C 29 29.5 11.6 8.2 1.6 0.8 1.2 1.4 5.4 16.7 -16 28 -0.6 -0.8 42.3 31.6 62.9 0.94 91.9 44.2
Mitch Bruneel Mitch Bruneel F 29 32.0 10.5 5.4 1.0 0.8 0.1 0.9 4.5 12.4 -58 28 -2.1 -2.6 58.8 42.1 78.6 -2.37 102.0 64.9
Zach Nelson Zach Nelson F 29 30.6 9.7 6.2 3.5 0.8 1.0 2.4 4.3 14.4 -20 28 -0.7 -1.0 44.4 16.1 57.4 0.07 97.5 46.4
Hayes Garrity Hayes Garrity G 29 21.7 8.7 2.8 1.5 0.4 0.0 1.3 4.4 7.8 -38 28 -1.4 -2.6 36.4 31.4 70.8 -1.63 90.3 42.6
Keawe Enos Keawe Enos G 29 29.7 7.9 2.6 1.8 0.7 0.0 1.2 3.5 8.3 -29 28 -1.0 -1.5 43.6 44.0 88.0 -0.59 102.7 59.9
Cory Cardwell Cory Cardwell G 1 4.0 3.0 0.0 0.0 1.0 0.0 0.0 0.0 4.0 - - - - 0 0 0 - 0 0
Brenden Evans Brenden Evans F 29 10.2 2.5 2.4 0.1 0.3 0.2 0.6 0.8 4.2 -38 28 -1.4 -6.1 59.1 0.0 64.7 -2.3 123.8 59.1
Chad Ross Chad Ross F 29 8.2 1.1 1.5 0.1 0.2 0.1 0.4 0.7 2.1 -25 28 -0.9 -5.0 31.6 0.0 50.0 -2.52 76.2 31.6
Taylor Brown Taylor Brown G 22 5.8 0.6 0.3 0.3 0.1 0.0 0.1 0.4 0.8 24 19 1.3 9.2 50.0 42.9 0 1.1 87.5 68.8
Eli Robison Eli Robison G 11 2.9 0.6 0.5 0.1 0.0 0.1 0.4 0.2 0.7 -7 9 -0.8 -16.2 0.0 0.0 0 -2.03 175.0 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