๐Ÿปโฌ‡๏ธ๐Ÿ€

Oklahoma

Also known as: Oklahoma Sooners, Oklahoma
Program History

2014 Team Stats (16 games)

79.3
PPG
-
Opp
-
Margin
43.2%
FG%
37.3%
3P%
76.8%
FT%
36.3
RPG
14.4
APG
10.6
TO
-
Est. poss./game
83.2
Adj PPG
70.2
Adj Opp PPG
#30
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†’ 1179 (#51) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More โ†’ 1251 (#34) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +92 elo More โ†’ 1047 (#103) HCA +92 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.8 More โ†’ +14.0 (#27) HCA +2.8
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.9 More โ†’ +13.1 (#27) HCA +2.9
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More โ†’ 0.704 (#55) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +19.6 More โ†’ 0.906 (#31) AdjNet +19.6
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +19.8 More โ†’ 0.907 (#31) AdjNet +19.8
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 83.2 | AdjD 70.2 More โ†’ 0.764 (#30) AdjO 83.2 | AdjD 70.2
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 77.9 | AdjD 70.3 More โ†’ 0.668 (#40) AdjO 77.9 | AdjD 70.3
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†’ 0.788 (#36) 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†’ 0.771 (#37) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 114 | GP 33 More โ†’ 1237 (#40) RD 114 | GP 33

2014 Schedule & Results

Date Vs/At Opponent Result Score
2013-11-08 @ Alabama Crimson Tide W 82 - 73
2013-11-11 vs North Texas Mean Green W 95 - 82
2013-11-13 vs Idaho Vandals W 85 - 65
2013-11-22 @ Seton Hall Pirates W 86 - 85
2013-11-23 @ Michigan State Spartans L 76 - 87
2013-11-29 vs Little Rock Trojans W 101 - 81
2013-12-02 vs Mercer Bears W 96 - 82
2013-12-05 vs Texas A&M-Corpus Christi Islanders W 78 - 56
2013-12-08 @ George Mason Patriots W 81 - 66
2013-12-14 vs Tulsa Golden Hurricane W 101 - 91
2013-12-17 vs UT Arlington Mavericks W 91 - 89
2013-12-21 @ Texas A&M Aggies W 64 - 52
2013-12-30 vs Louisiana Tech Bulldogs L 98 - 102
2014-01-04 @ Texas Longhorns W 88 - 85
2014-01-08 vs Kansas Jayhawks L 83 - 90
2014-01-11 vs Iowa State Cyclones W 87 - 82
2014-01-14 @ Kansas State Wildcats L 66 - 72
2014-01-18 @ Baylor Bears W 66 - 64
2014-01-22 vs TCU Horned Frogs W 77 - 69
2014-01-25 @ Texas Tech Red Raiders W 74 - 65
2014-01-27 vs Oklahoma State Cowboys W 88 - 76
2014-02-01 @ Iowa State Cyclones L 75 - 81
2014-02-05 @ West Virginia Mountaineers L 86 - 91
2014-02-08 vs Baylor Bears W 88 - 72
2014-02-12 vs Texas Tech Red Raiders L 60 - 68
2014-02-15 @ Oklahoma State Cowboys W 77 - 74
2014-02-22 vs Kansas State Wildcats W 86 - 73
2014-02-24 @ Kansas Jayhawks L 75 - 83
2014-03-01 vs Texas Longhorns W 77 - 65
2014-03-05 vs West Virginia Mountaineers W 72 - 62
2014-03-08 @ TCU Horned Frogs W 97 - 67
2014-03-13 vs Baylor Bears L 73 - 78
2014-03-20 vs North Dakota State Bison L 75 - 80

2014 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%
Buddy Hield Buddy Hield G 27 32.2 16.3 4.4 1.9 1.4 0.1 1.9 8.5 13.8 205 28 7.3 10.0 45.0 40.4 76.5 2.76 90.4 57.0
Cameron Clark Cameron Clark G 27 27.2 15.9 5.1 1.1 1.0 0.4 1.3 8.1 14.1 135 28 4.8 7.7 45.5 34.0 80.0 -0.61 88.6 49.1
Isaiah Cousins Isaiah Cousins G 27 29.6 11.7 4.0 2.1 1.1 0.4 1.1 5.5 12.8 175 28 6.2 9.4 45.9 43.6 80.4 2.53 92.7 54.1
Ryan Spangler Ryan Spangler F 27 29.4 9.6 9.2 1.3 0.6 1.0 1.0 3.5 17.2 229 28 8.2 12.3 50.0 50.0 73.1 4.33 104.5 50.5
Jordan Woodard Jordan Woodard G 27 27.5 9.6 2.1 4.5 1.1 0.1 2.0 4.5 11.0 135 28 4.8 7.7 36.4 37.5 79.7 0.75 83.1 42.6
Tyler Neal Tyler Neal F 27 15.4 5.7 2.8 0.6 0.3 0.3 0.9 2.9 5.9 87 28 3.1 9.5 41.6 40.9 85.2 2.09 87.2 53.2
Je'lon Hornbeak Je'lon Hornbeak G 26 18.3 5.3 1.9 2.6 0.8 0.1 1.3 2.3 7.0 111 24 4.6 11.1 39.3 22.6 70.6 1.69 90.2 45.1
Frank Booker Frank Booker G 26 12.8 4.6 1.3 0.5 0.3 0.2 0.7 2.2 4.1 26 27 1.0 3.1 32.1 34.6 66.7 -1.83 93.9 48.2
D.J. Bennett D.J. Bennett F 27 9.0 2.7 2.0 0.1 0.2 0.9 0.5 1.0 4.4 -9 27 -0.3 -1.7 51.9 0 76.9 -1.15 110.0 51.9
Trey Slate Trey Slate G 5 2.0 0.8 0.2 0.0 0.0 0.0 0.4 0.4 0.2 -12 6 -2.0 -52.7 50.0 0.0 0 -2.34 100.0 50.0
C.J. Cole C.J. Cole F 7 3.4 0.6 1.0 0.0 0.1 0.0 0.1 0.3 1.3 -9 8 -1.1 -16.6 0.0 0.0 0 -2.48 100.0 0.0
James Fraschilla James Fraschilla G 4 1.8 0.5 0.5 0.2 0.2 0.0 0.8 0.0 0.8 -8 5 -1.6 -50.7 0 0 50.0 -1.64 113.6 0
Austin Mankin Austin Mankin F 7 2.7 0.4 0.3 0.4 0.0 0.0 0.0 0.1 1.0 -4 9 -0.4 -9.7 0.0 0 0 -1.35 150.0 0.0
Daniel Harper Daniel Harper G 4 1.5 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.2 -11 5 -2.2 -74.4 0 0 0 -2.27 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