San Antonio Spurs Stats | Steals fuel Fast Break Transition

Monday, October 4th, 2010...4:48 am

Whose Defense Creates the Most Offense

There’s a common saying in football that the best defense is a good offense. In basketball, it might be more appropriate to say that a good defense can create good offense. Great ball pressure or playing the passing lanes can often lead to turnovers that can, in turn, lead to fast breaks and easy buckets.

The Spurs have long been known as one of the best defensive teams (of all time), but their style of physical defensive play doesn’t necessarily lend itself to steals and easy offensive possessions. In recent years, the trend has gotten worse. The following is a list of the NBA teams in 2009/10 sorted by the number of steals “converted.” (I defined converted as scoring a close basket or free throw within 6 or fewer seconds of the steal.)

Fast Break Points by Team

Team	Steals	Pts/Stl	Unastd Close	Close Ast	FT	Pts	FB Pts/Stl
GSW	761	1.22	72	61	64	330	0.43
PHI	667	1.08	58	65	55	301	0.45
SAC	564	1.20	50	65	31	261	0.46
OKC	654	1.14	55	51	46	258	0.39
MEM	645	1.11	58	48	40	252	0.39
ATL	592	1.23	54	48	41	245	0.41
UTA	675	1.17	56	45	34	236	0.35
CHA	632	1.18	43	47	56	236	0.37
DET	596	1.15	44	49	37	223	0.37
DEN	683	1.08	41	53	28	216	0.32
NJN	573	1.06	48	38	43	215	0.38
CLE	564	1.16	40	36	57	209	0.37
LAL	612	1.09	33	45	43	199	0.33
NOH	625	1.20	28	46	49	197	0.32
BOS	701	1.06	43	39	32	196	0.28
MIA	605	1.07	41	36	35	189	0.31
HOU	583	1.14	29	42	38	180	0.31
LAC	532	1.02	37	40	24	178	0.33
MIN	597	1.09	39	28	39	173	0.29
MIL	580	1.06	37	25	48	172	0.30
DAL	624	1.12	31	41	25	169	0.27
POR	523	1.15	31	39	29	169	0.32
CHI	531	1.02	22	43	32	162	0.31
IND	585	1.07	25	33	43	159	0.27
TOR	469	1.16	32	32	29	157	0.33
SAS	516	1.11	25	31	34	146	0.28
NYK	586	1.03	35	25	20	140	0.24
PHX	479	1.14	19	25	34	122	0.25
WAS	493	1.04	19	20	36	114	0.23
ORL	512	1.06	18	23	24	106	0.21

“Pts/Stl” include all points and possessions in plays following steals. All other statistics must be converted within six seconds of a steal without a stoppage in play. I assumed one point per possession after a stoppage of play. For a closer look at the underlying details of these statistics, check out my post on basketball-analysis.com.

The Spurs are right near the bottom of this list, but perhaps surprising to some, they have company in the offensive juggernaut known as the Phoenix Suns. The Suns have never been known for their defense, and nor have they collected a significant number of steals since their pre-Nash days.

However, for the steals they did have, their perceived fastbreaking tendencies should lead to a high conversion rate. I know Nash recently said something to the effect that the Suns of 2009/10 were not really a fast break team, but I am nonetheless surprised by this result. Other typical fast break teams such as Golden State, Philadelphia, Oklahoma City, Memphis and Atlanta all appeared near the top of this list.

Many harp on the perils of gambling in an effort to create steals. If a player over-commits and fails, he often leaves his team at a disadvantage. However, statistical models estimate that players with more steals tend to be more valuable than the action would reasonably dictate. Most statistical formulas place the value of a steal equal to barely over one point created, but regression models place this value at well over this amount (82games, abpr forum, basketball-reference, Off SPM and Def SPM).

This indicates that defensively, the lost value from taking these gambles is often made up in the havoc they cause. Additionally, from an offensive standpoint, steals can have significant value. Based on my data from the play-by-play from basketballvalue.com, plays in which the player who steals the ball finishes the possession himself result in about 1.5 points per possession.

Despite the fact that the Spurs have been so great defensively, they have rarely excelled in the steals department. One can’t really argue against the success of the Spurs defensive historically, but more steals could help on the offensive end, and perhaps even create a spark defensively.

Another factor to look at is who can finish with efficiency after steals. This shows both ability to finish in transition and how frequently steals were made on the perimeter. Following is a list of the top players sorted by fast break points created.

Fast Break Points by player

Player	Team	Stls	`Pts/Stl	FB Unastd Close	FB Close Ast	FB FT	FB Pts Created	FB Pts/Stl	FB Astd Close	FB Pts
Rajon Rondo	BOS	189	1.21	27	22	5	103	0.54	9	77
CJ Watson	GSW	103	1.32	20	17	19	93	0.9	6	71
Andre Iguodala	PHI	141	1.17	19	16	16	86	0.61	22	98
Tyreke Evans	SAC	109	1.27	20	17	12	86	0.79	15	82
Monta Ellis	GSW	143	1.3	18	17	15	85	0.59	12	75
LeBron James	CLE	125	1.3	18	9	28	82	0.66	16	96
Rudy Gay	MEM	118	1.15	23	9	8	72	0.61	13	80
Josh Smith	ATL	130	1.23	23	9	7	71	0.55	15	83
Russell Westbrook	OKC	108	1.21	14	17	8	70	0.65	7	50
Dwyane Wade	MIA	142	1.14	20	6	13	65	0.46	19	91
Baron Davis	LAC	126	1.06	14	15	5	63	0.5	5	43
Kevin Durant	OKC	112	1.21	14	9	17	63	0.56	13	71
Andre Miller	POR	93	1.27	11	14	13	63	0.68	1	37
Gerald Wallace	CHR	117	1.21	14	7	19	61	0.52	12	71
Courtney Lee	NJN	93	1.2	17	7	12	60	0.65	7	60
Rodney Stuckey	DET	101	1.15	14	12	5	57	0.56	10	53
Jason Terry	DAL	94	1.1	13	9	12	56	0.6	6	50
Louis Williams	PHI	80	1.18	10	14	8	56	0.7	7	42
Beno Udrih	SAC	89	1.37	10	15	5	55	0.62	4	33
Mike Conley	MEM	109	1.31	11	13	6	54	0.5	5	38
Trevor Ariza	HOU	126	1.33	15	8	8	54	0.43	13	64
Kobe Bryant	LAL	113	1.19	10	11	11	53	0.47	6	43
Brandon Jennings	MIL	105	1.09	13	7	13	53	0.5	6	51
Stephen Curry	GSW	152	0.98	12	11	4	50	0.33	7	42
OJ Mayo	MEM	98	1.08	16	5	8	50	0.51	16	72
Jrue Holiday	PHI	79	1.14	7	15	5	49	0.62	4	27
Jonny Flynn	MIN	82	1.12	7	8	18	48	0.59	2	36
Stephen Jackson	CHR	132	1.14	7	14	5	47	0.36	13	45
Raymond Felton	CHR	123	1.15	7	13	6	46	0.37	5	30
Devin Harris	NJN	79	1.05	9	11	5	45	0.57	4	31
Manu Ginobili	SAS	103	1.25	5	13	9	45	0.44	1	21
Darren Collison	NOR	78	1.21	7	10	10	44	0.56	11	46
Deron Williams	UTA	96	1.28	6	12	7	43	0.45	6	31
Danny Granger	IND	94	1.06	5	8	16	42	0.45	8	42
Chauncey Billups	DEN	82	1.02	5	14	4	42	0.51	0	14
Ronnie Brewer	UTA	91	1.21	14	5	3	41	0.45	5	41
Andrei Kirilenko	UTA	83	1.22	11	5	8	40	0.48	5	40
Marcus Thornton	NOR	58	1.4	9	6	10	40	0.69	15	58
Mario Chalmers	MIA	91	1.05	8	10	3	39	0.43	1	21
James Harden	OKC	80	1.23	8	5	13	39	0.49	6	41
Joe Johnson	ATL	82	1.24	8	10	2	38	0.46	6	30
Thaddeus Young	PHI	81	1	11	5	6	38	0.47	12	52
John Salmons	CHI	99	1.08	7	5	14	38	0.38	9	46
Will Bynum	DET	55	1.33	7	10	2	36	0.65	2	20
Maurice Williams	CLE	70	1.09	6	10	4	36	0.51	1	18
Carmelo Anthony	DEN	88	1.23	9	5	8	36	0.41	14	54
Jason Kidd	DAL	145	1.06	4	12	4	36	0.25	2	16
Corey Brewer	MIN	117	1.07	14	2	4	36	0.31	11	54
Ron Artest	LAL	106	1.08	7	6	10	36	0.34	7	38
Eric Gordon	LAC	69	1.17	7	7	7	35	0.51	6	33
Marvin Williams	ATL	66	1.17	9	2	12	34	0.52	8	46
Nene Hilario	DEN	115	1.16	8	7	3	33	0.29	3	25
George Hill	SAS	69	1.13	8	4	9	33	0.48	9	43
Kyle Lowry	HOU	60	1.12	3	10	7	33	0.55	3	19
Carlos Delfino	MIL	80	1.16	5	4	14	32	0.4	4	32
Omri Casspi	SAC	54	1.3	4	10	3	31	0.57	9	29
Derek Fisher	LAL	90	1.04	4	7	8	30	0.33	1	18
Ty Lawson	DEN	48	1.27	7	6	4	30	0.63	5	28
Jamal Crawford	ATL	61	1.38	3	7	10	30	0.49	6	28
Delonte West	CLE	55	1.02	5	4	12	30	0.55	0	22
Toney Douglas	NYK	42	1.19	12	2	2	30	0.71	5	36
JR Smith	DEN	99	1.12	6	6	6	30	0.3	8	34
Chris Paul	NOR	96	1.18	6	6	6	30	0.31	1	20
Sergio Rodriguez	NYK	50	1.18	6	8	0	28	0.56	3	18
Quentin Richardson	MIA	70	1.2	4	7	6	28	0.4	3	20
Jarrett Jack	TOR	60	1.17	4	9	2	28	0.47	3	16
Earl Watson	IND	104	1.02	1	8	10	28	0.27	1	14
Eric Maynor	OKC	40	1.38	5	8	2	28	0.7	2	16
Aaron Brooks	HOU	69	1	4	8	3	27	0.39	6	23
Damien Wilkins	MIN	66	1.11	6	5	5	27	0.41	1	19
Jared Dudley	PHO	81	1.23	2	7	9	27	0.33	1	15
CJ Miles	UTA	58	1.24	9	2	4	26	0.45	4	30
Kirk Hinrich	CHI	85	0.91	1	9	6	26	0.31	4	16
Luol Deng	CHI	66	1.17	3	9	2	26	0.39	4	16
Tony Allen	BOS	59	1	9	0	8	26	0.44	8	42
Chris Douglas-Roberts	NJN	55	0.98	7	2	7	25	0.45	10	41
Jason Richardson	PHO	66	1.14	6	4	5	25	0.38	8	33
Thabo Sefolosha	OKC	97	1.06	6	5	3	25	0.26	8	31
Ronnie Price	UTA	40	1.2	2	9	3	25	0.63	3	13
Jonas Jerebko	DET	79	1.19	4	3	11	25	0.32	9	37
Derrick Rose	CHI	57	1.19	2	5	10	24	0.42	10	34
DJ Augustin	CHR	45	1.24	4	4	8	24	0.53	3	22
Mike Bibby	ATL	67	1.07	2	8	4	24	0.36	3	14
Rudy Fernandez	POR	62	1.16	2	9	2	24	0.39	1	8
Steve Blake	POR	58	1.17	4	7	2	24	0.41	0	10
Wesley Matthews	UTA	64	1.05	5	4	6	24	0.38	7	30
Jordan Farmar	LAL	52	1.19	6	3	6	24	0.46	5	28
Elton Brand	PHI	82	1.04	5	3	7	23	0.28	4	25
Sonny Weems	TOR	39	1.28	6	3	5	23	0.59	7	31
Devin Brown	NOR	33	1.21	4	2	11	23	0.7	2	23
Brandon Roy	POR	61	1.13	4	6	3	23	0.38	5	21
Keyon Dooling	NJN	34	1.41	7	3	2	22	0.65	0	16
Kevin Martin	HOU	46	1	6	1	8	22	0.48	9	38
Jeff Green	OKC	104	1.08	7	4	0	22	0.21	3	20
Shawn Marion	DAL	69	1.25	6	4	2	22	0.32	12	38
Caron Butler	WAS	116	1.21	3	5	6	22	0.19	1	14
Sam Young	MEM	34	1.18	5	2	7	21	0.62	0	17
Ramon Sessions	MIN	55	0.89	7	2	3	21	0.38	4	25
Tyrus Thomas	CHI	63	1	6	2	5	21	0.33	2	21
DeMar DeRozan	TOR	43	1.16	5	3	4	20	0.47	6	26
Ronald Murray	CHR	46	1.15	3	5	4	20	0.43	5	20
Lamar Odom	LAL	75	1.01	1	8	2	20	0.27	5	14
Corey Maggette	GSW	52	1.13	4	3	6	20	0.38	14	42
Nate Robinson	NYK	49	1.16	4	4	3	19	0.39	1	13
Andray Blatche	WAS	85	0.86	2	5	5	19	0.22	2	13
Goran Dragic	PHO	48	1.17	3	2	9	19	0.4	5	25
Matt Barnes	ORL	59	1	3	5	3	19	0.32	10	29
Gilbert Arenas	WAS	41	1.05	1	2	12	18	0.44	2	18
Dorell Wright	MIA	52	1.17	4	3	4	18	0.35	3	18
T.J. Ford	IND	44	1	6	2	2	18	0.41	0	14
Ben Wallace	DET	86	1.1	5	4	0	18	0.21	1	12
A.J. Price	IND	35	1.23	3	3	6	18	0.51	0	12
Paul Pierce	BOS	84	0.94	2	5	3	17	0.2	3	13
Carlos Arroyo	MIA	36	0.94	1	4	6	16	0.44	1	10
Tayshaun Prince	DET	34	1.41	2	3	6	16	0.47	8	26
Jameer Nelson	ORL	48	0.96	3	5	0	16	0.33	2	10
Danilo Gallinari	NYK	75	0.95	4	2	4	16	0.21	0	12
Ray Allen	BOS	64	0.91	3	4	2	16	0.25	8	24
Vince Carter	ORL	53	1.17	3	2	6	16	0.3	1	14
Dahntay Jones	IND	40	1.3	2	5	2	16	0.4	8	22
Hedo Turkoglu	TOR	55	1.18	4	4	0	16	0.29	2	12
Grant Hill	PHO	60	1.2	2	4	4	16	0.27	4	16
Jose Calderon	TOR	47	1.02	2	5	2	16	0.34	4	14
Anthony Carter	DEN	39	1.23	2	6	0	16	0.41	2	8
Anthony Parker	CLE	63	1.19	0	6	4	16	0.25	0	4
Terrence Williams	NJN	43	1.05	5	1	3	15	0.35	6	25
Willie Green	PHI	32	0.91	2	3	5	15	0.47	3	15
Charlie Villanueva	DET	48	1.1	4	2	3	15	0.31	5	21
Shannon Brown	LAL	57	1	4	2	3	15	0.26	8	27
Marcus Camby	LAC	95	1.02	1	4	5	15	0.16	1	9
Larry Hughes	NYK	52	1.31	5	1	2	14	0.27	2	16
Rafer Alston	NJN	50	1.04	0	6	2	14	0.28	0	2
Shane Battier	HOU	53	1.09	1	5	2	14	0.26	0	4
David Lee	NYK	85	1.11	2	5	0	14	0.16	5	14
Richard Hamilton	DET	30	1.33	1	4	4	14	0.47	1	8
Luis Scola	HOU	63	0.89	1	5	2	14	0.22	6	16
DeJuan Blair	SAS	50	1.02	4	2	2	14	0.28	1	12
Zaza Pachulia	ATL	37	1.22	3	2	3	13	0.35	2	13
Jeff Teague	ATL	34	1.18	3	3	1	13	0.38	2	11
Marco Belinelli	TOR	42	1.19	2	2	5	13	0.31	1	11
Al Harrington	NYK	62	1.19	4	0	5	13	0.21	2	17
Zach Randolph	MEM	80	1.08	0	3	7	13	0.16	8	23
Luke Ridnour	MIL	54	1.09	2	3	3	13	0.24	1	9
David West	NOR	76	1.17	0	6	1	13	0.17	1	3
Donte Greene	SAC	41	1.39	1	4	3	13	0.32	9	23
Paul Millsap	UTA	64	1.28	3	2	3	13	0.2	3	15
Martell Webster	POR	45	1.04	3	1	5	13	0.29	9	29
Ryan Gomes	MIN	62	1.26	2	4	1	13	0.21	1	7
Ben Gordon	DET	49	1.1	1	4	2	12	0.24	6	16
Mickael Pietrus	ORL	53	1.06	3	1	4	12	0.23	4	18
Jason Williams	ORL	53	1.06	4	2	0	12	0.23	1	10
JJ Hickson	CLE	36	1.33	5	1	0	12	0.33	9	28
Amare Stoudemire	PHO	52	1.25	2	4	0	12	0.23	2	8
Maurice Evans	ATL	34	1.35	3	3	0	12	0.35	2	10
Jamaal Tinsley	MEM	33	1.09	1	4	2	12	0.36	0	4
Randy Foye	WAS	33	1.24	2	2	4	12	0.36	0	8
Amir Johnson	TOR	44	0.91	4	0	3	11	0.25	2	15
Chris Duhon	NYK	59	1.15	1	4	1	11	0.19	0	3
Anthony Morrow	GSW	65	1.25	2	3	1	11	0.17	3	11
Marcus Williams	MEM	32	1	1	4	1	11	0.34	1	5
Roger Mason	SAS	30	1.13	2	3	0	10	0.33	1	6
Anthony Tolliver	GSW	32	1.34	1	2	4	10	0.31	5	16
Andres Nocioni	SAC	32	1.19	1	3	2	10	0.31	2	8
Dirk Nowitzki	DAL	70	1.14	0	5	0	10	0.14	5	10
Craig Smith	LAC	33	0.91	3	1	2	10	0.3	4	16
James Posey	NOR	42	0.95	0	5	0	10	0.24	0	0
Ime Udoka	SAC	34	1.18	1	4	0	10	0.29	2	6
Ersan Ilyasova	MIL	53	0.85	2	2	2	10	0.19	2	10
Mike Dunleavy	IND	38	1.32	3	1	2	10	0.26	2	12
Antoine Wright	TOR	30	1.27	3	0	4	10	0.33	3	16
Al Thornton	LAC	45	1	3	0	3	9	0.2	9	27
Peja Stojakovic	NOR	48	1.31	0	4	1	9	0.19	5	11
Brook Lopez	NJN	55	1	0	3	3	9	0.16	3	9
Eddie House	BOS	40	0.98	0	2	5	9	0.23	2	9
Mike Miller	WAS	39	0.79	2	1	3	9	0.23	2	11
Rasual Butler	LAC	36	1.03	1	3	1	9	0.25	5	13
Jamario Moon	CLE	34	1.18	4	0	1	9	0.26	2	13
Chase Budinger	HOU	34	1.5	2	2	1	9	0.26	7	19
Steve Nash	PHO	42	1.05	1	3	0	8	0.19	1	4
Michael Beasley	MIA	80	0.89	4	0	0	8	0.1	7	22
Keith Bogans	SAS	45	0.93	1	3	0	8	0.18	0	2
Devean George	GSW	41	1.46	1	0	6	8	0.2	0	8
Pau Gasol	LAL	37	0.97	0	3	2	8	0.22	9	20
Chris Andersen	DEN	42	1.05	0	3	2	8	0.19	1	4
Arron Afflalo	DEN	46	1.04	2	2	0	8	0.17	7	18
Jason Maxiell	DET	36	0.97	3	0	2	8	0.22	4	16
Marc Gasol	MEM	69	1.04	1	3	0	8	0.12	0	2
Luc Mbah a Moute	MIL	60	0.97	2	1	2	8	0.13	2	10
Taj Gibson	CHI	50	1.22	1	3	0	8	0.16	0	2
Kris Humphries	NJN	36	1.11	2	1	2	8	0.22	2	10
Jose Juan Barea	DAL	35	1.09	1	2	2	8	0.23	5	14
Charlie Bell	MIL	39	0.92	0	3	1	7	0.18	0	1
Darius Songaila	NOR	62	1.06	0	3	0	6	0.1	2	4
Rashard Lewis	ORL	78	1.18	0	2	2	6	0.08	0	2
Chris Kaman	LAC	37	0.97	1	2	0	6	0.16	4	10
Chuck Hayes	HOU	73	1.08	0	3	0	6	0.08	0	0
Troy Murphy	IND	72	0.92	1	2	0	6	0.08	4	10
Carlos Boozer	UTA	84	1.06	1	2	0	6	0.07	4	10
Anderson Varejao	CLE	71	1.04	1	1	2	6	0.08	3	10
Richard Jefferson	SAS	45	1	0	0	6	6	0.13	10	26
Carl Landry	HOU	55	1.16	1	0	4	6	0.11	3	12
Jared Jeffries	NYK	62	0.98	1	2	0	6	0.1	0	2
Tim Duncan	SAS	45	1	0	3	0	6	0.13	2	4
Kenyon Martin	DEN	72	0.92	1	1	1	5	0.07	6	15
Kevin Love	MIN	43	1.02	1	1	1	5	0.12	1	5
Dwight Howard	ORL	75	1.12	1	1	1	5	0.07	0	3
Drew Gooden	DAL	41	1	1	1	1	5	0.12	3	9
Wilson Chandler	NYK	46	0.85	1	0	3	5	0.11	6	17
Udonis Haslem	MIA	30	1.13	0	2	1	5	0.17	1	3
Rasheed Wallace	BOS	80	1	0	1	2	4	0.05	2	6
Kevin Garnett	BOS	68	1.04	1	1	0	4	0.06	2	6
Al Jefferson	MIN	63	1.29	0	2	0	4	0.06	1	2
Spencer Hawes	SAC	32	0.75	0	2	0	4	0.13	5	10
Al Horford	ATL	59	1.2	0	2	0	4	0.07	4	8
Samuel Dalembert	PHI	42	1.02	1	1	0	4	0.1	1	4
Chris Bosh	TOR	43	1.14	0	1	2	4	0.09	1	4
Boris Diaw	CHR	60	1.15	0	1	2	4	0.07	0	2
Antawn Jamison	WAS	71	1.01	0	1	1	3	0.04	4	9
Jason Thompson	SAC	41	1	0	1	1	3	0.07	5	11
Nick Collison	OKC	37	0.95	0	1	1	3	0.08	1	3
Emeka Okafor	NOR	54	1.2	0	0	2	2	0.04	4	10
Channing Frye	PHO	64	0.95	1	0	0	2	0.03	1	4
Antonio McDyess	SAS	43	1.21	1	0	0	2	0.05	1	4
Nenad Krstic	OKC	32	1.06	0	1	0	2	0.06	2	4
Yi Jianlian	NJN	37	0.95	0	0	2	2	0.05	3	8
LaMarcus Aldridge	POR	67	1	0	0	2	2	0.03	11	24
Joakim Noah	CHI	32	0.75	0	1	0	2	0.06	4	8
Brad Miller	CHI	44	0.91	0	1	0	2	0.05	2	4
Andrew Bynum	LAL	35	1.11	0	0	1	1	0.03	2	5
Matt Bonner	SAS	30	0.83	0	0	1	1	0.03	0	1
Josh Boone	NJN	30	0.8	0	0	0	0	0	1	2
Brandon Rush	IND	56	0.96	0	0	0	0	0	1	2
Mehmet Okur	UTA	38	0.84	0	0	0	0	0	2	4
Roy Hibbert	IND	30	0.97	0	0	0	0	0	1	2
Andrew Bogut	MIL	39	0.79	0	0	0	0	0	0	0

Rajon Rondo led the league in steals and also led the league in converting steals to buckets. CJ Watson (0.90) and Tyreke Evans (0.79) stood out for their exceptional conversion rates of fast break points per steal. (League average was 0.33). At this point in his career, though Jason Kidd is still able to force turnovers, he seems to have trouble scoring quickly off them. His conversion rate is only 0.25.

Lebron James was perhaps the best finisher, leading the NBA with 28 free throws made within 6 seconds of his own steal. Andre Iguodala was the top beneficiary of setups from another player’s steal, scoring 22 close baskets in that fashion. Monta Ellis, Rudy Gay, Josh Smith, Russell Westbrook and Dwyane Wade were among the other noteworthy finishers. Points per steal was watered down by non-transition possessions, but some familiar players still managed to make an appearance near the top of this list. Watson, Ellis and Lebron were joined by Beno Udrih, Trevor Ariza and Mike Conley among the leaders in team points per individual steal.

Here is a list of the Spurs with their transition possessions and points per possession, as defined by Synergy .

Fast Break Points for Spurs

Player	Stls	Pts/Stl	FB Ucl	FB ClAst	FB FT	FB Pts Created	FB Pts/Stl	FB AstdClose	FB Pts	Syn Trans Poss	Syn Trans PPP
Manu Ginobili	103	1.25	5	13	9	45	0.44	1	23	130	1.27
George Hill	69	1.13	8	4	9	33	0.48	9	43	169	1.3
Tony Parker	29	1.41	3	2	3	13	0.45	2	15	193	1.17
Tim Duncan	45	1	0	3	0	6	0.13	2	10	49	1.04
Keith Bogans	45	0.93	1	3	0	8	0.18	0	2	58	1.17
Roger Mason	30	1.13	2	3	0	10	0.33	1	8	62	1.16
DeJuan Blair	50	1.02	4	2	2	14	0.28	1	18	21	1
Richard Jefferson	45	1	0	0	6	6	0.13	10	26	140	1.28
Michael Finley	10	1	0	1	0	2	0.2	0	0	6	0
Antonio McDyess	43	1.21	1	0	0	2	0.05	1	6	18	1.06
Matt Bonner	30	0.83	0	0	1	1	0.03	0	1	28	1.21
Garrett Temple	13	1.08	2	0	5	9	0.69	1	11	17	1.06
Malik Hairston	4	1	0	0	0	0	0	3	6	12	1.58
Ian Mahinmi	3	0.67	0	0	0	0	0	0	0	3	0.67

This list includes players who played most of their 2009/10 minutes with the Spurs. For this reason, the totals might differ slightly from the Spurs actual totals. Synergy transition possessions can be off steals, blocks, defensive rebounds or made shots and do not include assists.

Manu Ginobili seemed to be the best thief and fast break distributor for the Spurs. Tony Parker creates few steals, but had reasonable success in the transition despite his injury woes. George Hill was possibly the Spurs’ best overall finisher on the break.

Perhaps the most important information from this table is that, despite being a significant factor in the Spurs’ fast break, Richard Jefferson saw his transition possessions decrease for the second consecutive year. Jefferson’s transition possessions, as defined by Synergy, decreased from 285 in 2007/08 to 208 in 2008/09 and to 126 in last year’s regular season. Perhaps the Spurs could bring in someone to better spark the break and increase his value.

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Filed under NBA Stats, Richard Jefferson, San Antonio Spurs, Spurs Stats

13 Comments

Basketball-Analysis.com» Whose Defense Creates the Most Offense
October 4th, 2010 at 5:58 am

[...] Monday, I will release a post detailing the NBA leaders for fastbreak points resulting from steals. I detail lists by player and by team and take a closer look at the Spurs. I will quickly discuss [...]
The Beat Counselor
October 4th, 2010 at 7:11 am

Can’t disagree with the conclusion that RJ wasn’t fully utilized in transition last year.

On the other hand, I believe that the traditional Spurs attitude towards steals is that it is a gambling style of defense that causes the on-ball defender to often be out of place defensively which results in the defense having to rotate to compensate.

I do however appreciate the defensive prowess of a player like Rondo who not only can get steals by reaching in but also by recovering from his overgambling, not giving up on the play and being able to break up the play from behind the ball handler (which is especially effective against PGs that are good 3pt shooters).

Perhaps it would be smart to investigate such a strategy when guarding PGs just because the hand-check rule has made defending todays quicker PGs so difficult. This maybe more of an option now that we have another big anchoring the paint. That being said the defender would have to be tenacious after a failed first attempt. I could see hill being more effective at this than TP because he seems to have longer arms.

As for the other type of steal, reading the passing lanes and intercepting the pass (ala Trevor Ariza), this may be where RJ can create more fastbreak opportunities for himself.
Again, having Splitter allows us to gamble more defensively on the perimeter.
Greyberger
October 4th, 2010 at 11:04 am

I was surprised to see how highly steals are valued in regression analysis. In the cited examples a steal is worth more than the change of possession AND the extra likelyhoood of scoring on the ensuing offensive possession. In other words a steal appears more valuable than we can easily explain.

Sometimes regression analysis puts us in the position of explaining a result that seems counter-intuitive. For example according to some models built on regressions, offensive rebounds are more correlated with wins and more valuable than defensive boards. How can this be, when the value of an defensive rebound is denying your opponent the value of an offensive one? The numbers sometimes come into conflict with what you know to be true about basketball.

You can either conclude that what we assume about possession and efficiency and basketball in theory is wrong (few people do this) or you can conclude your measurement is capturing more than intended. Maybe individual offensive rebounding numbers illustrate team strength in rebounding or some other area in a way we don’t fully understand. Steals almost certainly ‘capture’ strong defense in regressions in a way that would make their value seem inflated in other contexts.

This isn’t really a problem as long as you’re convinced what is being captured is the individual’s skill. Back to the Rondo example - it’s not just about what Rajon Rondo can do with his unique skillset. His steals come in a defense that is constantly applying pressure, doesn’t allow a good fg% or many good looks, and has great defenders in the paint for when Rondo gambles and gets beat. It’s not just Rondo those steals are describing but the Celtics as well.

Another snag that contributes to how difficult it is to properly estimate the value of player steals is the missing input problem. Since stats for the most important part of defense (shooting defense) aren’t available at an individual level, the defensive stats that we DO have end up with exaggerated value. The heavy weight of a ‘fg% allowed’ input (or proxy like Drtg does) would put steals and blocks in their proper context.

Then there’s the puzzle of the Spurs, who historically aren’t just bad at steals, they’re apathetic! Under Popovich the Spurs don’t seem to care at all about forcing TOs, fouls or getting offensive rebounds and focus instead on keeping team TO down and denying offensive boards and free throws to the opponent. In 2009 for example, the Spurs were best-in-league at opponent free throw rate, opponent ORB%, and team TO… and worst-in-league or second worst in the flipside of those factors. This trend is so prominent that you have to figure it’s coming from the top. How can we assess a player’s ability at something if the coach is explicitly telling him to not even attempt it?
nba fan 83
October 4th, 2010 at 12:50 pm

With the Nba becoming an increasingly offensive league, we can’t assume playing sound defense will result in a favorable outcome (no score) more than 50% of the time. Teams nowadays score in excess of 50% all the time, which means more drastic measures are needed to break up plays and risks have to be taken. It might be time for the spurs to revisit their conservative approach to defense.
Jaceman
October 4th, 2010 at 2:22 pm

Spurs actually like breaking a lot more than people think, but I think with Timmy’s age it’s harder for the bigs to keep up. While steals are a big part of it, I think the philosophy is generally the same in previous years of shot alteration and quick outlets from the defensive board, which I believe is where Tony Parker had a lot of success. It is still a gamble, when to help and when to leak, but hopefully with the interior defense there, we have more of those opportunities.
Jaceman
October 4th, 2010 at 2:25 pm

Spurs defense has been all about floor spacing and shot alteration, forcing wings to the baseline where a big alters (or blocks) the shot and gets the board. This leads to quick outlets as the wings can then leak out in transition. While this isn’t as statistically flashy as the steal, it’s equally as effective, and won’t often show up in the box scores.
Scott Sereday
October 4th, 2010 at 4:10 pm

Good observations Greyberger,

A couple notes: Steals are almost certainly capturing some tendencies that the other data in the models miss. Since such little information is readily available defensively, a player who averages an extra steal per 100 possessions seems to also simply have better defensive abilities since they are usually more athletic than average. There could also be random oddities that screw the results.
As for rebounds: a rebound is a rebound and is worth a possession…from a team’s standpoint, anyway. The one missing piece of information is that gathering a rebound that a teammate would have otherwise grabbed adds no value. That is why the accepted value of an individual defensive rebound is around .3 (since the opposing team has a 30% offensive rebounding rate) and offensive rebounding value is accepted at 70%.

Jaceman,
From what I can tell, Parker’s rather high number of transition possessions seem to be from quick strikes from outlet passes, when the defense is largely back but not set. This is defined as a fast break, but probably not as easy of a shot as other transition plays (although certainly much easier to create).
And clearly the Spurs have done tons of things right defensively. I’m sure spicing things up with a few more defensive gambles might make things even better, but clearly they should be careful not to mess up what has been a very good thing.
rj
October 4th, 2010 at 8:48 pm

so…..no one has said much about james anderson in camp. how about gist, gee, or jerrils? it would be great if one of these spurs blog could highlight the performers of training camp. been hearing good things about blair and the HEB commercials
anonymous
October 5th, 2010 at 5:24 am

The staff writer for Bleach Report is at this minute. name calling and insulting many Spurs fans on his Blog. Google this,(Bleacher Report-Spurs have a rough road) and help those other Spurs fans out. Instead of us taking on other Spurs fan Bloggers here, go over there and take care of that staff writing Laker fan.
Evolution through blood, sweat, and teadrops | 48 Minutes of Hell
October 5th, 2010 at 9:15 am

[...] the rim). Like Richard Jefferson in his prime, to keep his offensive efficiency up Hill relies on fast break points, a decent percentage from 3-pointers, and free throws. A shot designed to avoid contact takes away [...]
dae
October 5th, 2010 at 9:31 am

Anyone else notice how as a whole, the top “points per steal” teams aren’t what you call title contenders?

I’m not sure what the point of this article is. On the one hand, they’re saying it’s worth gambling on steals but as we can see by the list provided, most of the steal converting teams are pretty crappy.
rob
October 5th, 2010 at 11:46 am

One of the problems that encompasses gambling on steals from a Spurs defensive perspective is the fact that the defense relys on generous spacing and rotational help.

If player x gambles on a steal…it breaks down the system of rotating to cover. There’s not many times an individual player on this team is defending man on man unless they happen to be the on ball defender. It’s more like a motion/man defense where everybody else except the on ball defender is jockying for rotational position in anticipation that if the on ball defender does his job directing the opponent to a certain spot…they’re able to cover the seams on the court.
Greyberger
October 5th, 2010 at 7:41 pm

Yeah Pop is certainly no-nonsense about players whose ‘initiative’ hurts the team defense. He’s publicly said the most important thing for his teams is to force bad shots and not foul… as opposed to forcing turnovers or rebounding every miss, I guess.

Re: Scott, you’re right and right about the mistake being the difference from team level to individual level. Offense and defensive rebounding might be equally important to a team, but 10 offensive boards in a game is obviously a greater contribution than just 10 defensive rebounds. If you were to remove that player and those 10 d. rebounds from the reckoning, any (sane) model would assume your teammates to pick up most of the slack.

Reason number 92 why Kobe’s game 7 looks so bad on paper.

Monday, October 4th, 2010...4:48 am

Whose Defense Creates the Most Offense

Fast Break Points by Team

Fast Break Points by player

Fast Break Points for Spurs

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