Texas Tech

Season: 2027 preview 2026 2025 2024 2023 2022 2021 2020 2019 2018 2017

Also known as: Texas Tech Red Raiders, Texas Tech

Program History

Coach: Tubby Smith

2015 Team Stats (12 games)

57.8

PPG

74.0

Opp

-16.2

Margin

39.6%

FG%

33.7%

3P%

59.2%

FT%

30.4

RPG

11.0

APG

15.6

Est. poss./game

61.9

Adj PPG

60.2

Adj Opp PPG

#140

Scoring Rank

Model Outputs

2014-2015

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 →	1013 (#164)	-
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More →	986 (#186)	-
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +90 elo More →	902 (#300)	HCA +90 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.9 More →	+2.4 (#136)	HCA +2.9
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.8 More →	-0.3 (#177)	HCA +2.8
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More →	0.347 (#249)	-
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +4.0 More →	0.613 (#134)	AdjNet +4.0
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +4.1 More →	0.616 (#132)	AdjNet +4.1
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 61.9 \| AdjD 60.2 More →	0.539 (#140)	AdjO 61.9 \| AdjD 60.2
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 60.2 \| AdjD 63.6 More →	0.425 (#256)	AdjO 60.2 \| AdjD 63.6
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 →	0.504 (#166)	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 →	0.481 (#178)	Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 138 \| GP 32 More →	1027 (#150)	RD 138 \| GP 32

2015 Schedule & Results

Date	Vs/At	Opponent	Result	Score
2014-11-14	vs	Loyola Maryland Greyhounds	W	71 - 59
2014-11-18	@	LSU Tigers	L	64 - 69
2014-11-22	vs	Missouri State Bears	W	80 - 68
2014-11-25	vs	Northwestern State Demons	W	75 - 64
2014-11-30	vs	Air Force Falcons	W	63 - 62
2014-12-03	vs	Auburn Tigers	W	46 - 44
2014-12-10	vs	Fresno State Bulldogs	W	73 - 56
2014-12-14	vs	Prairie View A&M Panthers	W	79 - 51
2014-12-17	vs	South Carolina State Bulldogs	W	101 - 39
2014-12-19	vs	Arkansas-Pine Bluff Golden Lions	W	72 - 51
2014-12-22	vs	Loyola Chicago Ramblers	L	44 - 62
2014-12-23	vs	Houston Cougars	L	69 - 82
2014-12-29	vs	North Texas Mean Green	W	60 - 45
2015-01-03	vs	Texas Longhorns	L	61 - 70
2015-01-05	vs	West Virginia Mountaineers	L	67 - 78
2015-01-10	@	Kansas Jayhawks	L	54 - 86
2015-01-14	@	Kansas State Wildcats	L	51 - 58
2015-01-17	vs	TCU Horned Frogs	L	42 - 62
2015-01-21	@	Oklahoma State Cowboys	L	43 - 63
2015-01-24	vs	Iowa State Cyclones	W	78 - 73
2015-01-28	@	Oklahoma Sooners	L	36 - 81
2015-01-31	@	West Virginia Mountaineers	L	58 - 77
2015-02-04	vs	Kansas State Wildcats	W	64 - 47
2015-02-07	@	Iowa State Cyclones	L	38 - 75
2015-02-10	vs	Kansas Jayhawks	L	51 - 73
2015-02-14	@	Texas Longhorns	L	41 - 56
2015-02-17	vs	Baylor Bears	L	49 - 54
2015-02-21	vs	Oklahoma Sooners	L	75 - 79
2015-02-25	@	TCU Horned Frogs	L	54 - 71
2015-02-28	vs	Oklahoma State Cowboys	W	63 - 62
2015-03-06	@	Baylor Bears	L	74 - 77
2015-03-11	@	Texas Longhorns	L	53 - 65

2015 Roster

Show Alumni If everyone stayed four years

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%
Devaugntah Williams	G	28	24.7	11.1	3.0	1.4	0.8	0.1	1.9	5.2	9.2	-108	25	-4.3	-7.4	37.7	39.5	73.5	0.3	93.1	47.9
Robert Turner	G	28	24.4	8.1	2.9	1.9	0.9	0.1	1.5	4.2	8.0	-127	25	-5.1	-8.7	33.1	27.1	73.3	-1.32	86.1	38.6
Toddrick Gotcher	G	28	24.5	7.5	2.7	1.5	0.6	0.4	1.0	4.0	7.8	-102	25	-4.1	-7.3	36.0	33.3	69.8	1.06	81.2	45.5
Norense Odiase	C	27	21.9	7.1	4.9	0.7	0.3	0.6	1.7	3.7	8.1	-99	25	-4.0	-7.9	44.0	0	48.4	-0.44	74.5	44.0
Zach Smith	F	27	28.5	6.5	4.9	1.3	0.6	1.6	1.2	3.3	10.5	-111	24	-4.6	-6.9	47.7	33.3	57.8	2.39	81.2	50.6
Keenan Evans	G	28	18.5	5.9	2.1	1.5	0.8	0.4	1.5	3.5	5.6	-124	25	-5.0	-12.3	36.7	31.6	66.7	-2.29	66.3	42.9
Justin Gray	G	13	16.8	5.1	2.3	0.3	0.6	0.5	0.9	1.6	6.2	22	11	2.0	4.6	38.1	0.0	84.6	1.2	123.5	38.1
Randy Onwuasor	G	26	18.6	3.9	2.7	1.3	1.0	0.2	1.7	2.4	5.0	-97	23	-4.2	-9.9	29.0	18.2	55.6	-2.58	69.0	32.3
Isaiah Manderson	F	28	14.1	3.9	2.6	0.2	0.3	0.2	1.2	2.7	3.3	-69	24	-2.9	-9.8	52.6	0.0	44.0	-0.22	63.2	52.6
Justin Jamison	F	7	7.9	3.1	1.9	0.3	0.1	0.1	0.4	1.0	4.1	-29	7	-4.1	-23.3	57.1	66.7	66.7	-3.02	132.2	71.4
Aaron Ross	F	19	9.9	2.7	1.9	0.3	0.1	0.2	1.1	2.4	1.7	-57	18	-3.2	-14.4	21.7	0.0	86.4	-0.75	46.7	21.7
Stan Mays	G	6	4.3	2.3	0.3	0.2	0.0	0.0	1.0	0.8	1.0	-4	5	-0.8	-6.6	40.0	40.0	75.0	-1.1	82.2	60.0
Alex Foster	F	19	5.9	0.8	0.5	0.1	0.0	0.3	0.6	0.4	0.7	-29	17	-1.7	-13.2	50.0	0	25.0	-2.34	76.8	50.0
Clark Lammert	F	25	7.8	0.7	1.5	0.4	0.2	0.1	0.3	0.4	2.2	-60	22	-2.7	-13.8	36.4	0	28.6	-1.97	63.9	36.4
Luke Adams	G	11	3.2	0.5	0.4	0.1	0.1	0.0	0.4	0.5	0.2	-1	8	-0.1	-1.4	0.0	0.0	80.0	-0.52	34.7	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