The Spurs' offense got good looks and put away Trail Blazers

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The Spurs gave up 19 second chance and 16 fast break points, but got loads of good looks from two and hit the threes they took as they topped the Blazers in Aldridge's return to Portland

By BrettJones@comradebernout Nov 12, 2015, 10:41am CST

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Spurs 113, Trail Blazers 101 - Nov 11, '15

The Spurs played a pretty good all-around game in this one, benefitting from really solid play from a lot of different guys, with 8 players notching .40 AdjGS/minute or higher. No really out-of-this-world performances, just sustainable team basketball.

They didn't perform terribly well on fast breaks and second chance points, as the Blazers scored 16 in transition and somehow parlayed just 10 offensive rebounds into a ridiculous 19 points. The Spurs, on the other hand, scored just 6 on their 8 offensive boards. Odd.

The Spurs didn't take a lot (or enough) threes in this one with just 15 attempts, which is a bit concerning, but they nailed 46.7% of the ones they took. So the Spurs were a bit fortunate in that regard.

Two point field goal percentage continues to be outstanding as the Spurs are hitting over 54% from inside the arc this season. They lead the league in simple FG%, but since so few of those looks are threes, their effective FG% is third in the league behind Golden State and OKC. We've said it many times before, but it's going to be really crucial for the Spurs to find ways to get more looks from deep if they want to keep pace with top Western conference squads.

Manu Ginobili continues to be dynamite in a bottle, contributing 14 points, 5 boards and 4 assists in 22 minutes of play. I don't think anyone expected Manu to start the season so well. I hope he can keep it up over the course of a long season.

Diaw, Ginobili and Mills continue to lead a marvelously effective second unit. The change in offensive style when they check in is outright jarring.

The Spurs' starters lack of offensive rhythm has mostly been attributed to incorporating Aldridge, but I wonder if it's not something more simple. Last year, the Spurs first unit struggled with their spacing when both Duncan and Splitter shared the floor. Aldridge replacing Sparkles has only compounded that problem, as the Spurs not only have two bigs clogging the paint, but another isolation-heavy player to accommodate.

Yet it seems that when Duncan heads to the bench and Aldridge moves to center with Leonard and the second unit, the Spurs offense comes to life. Which makes me wonder how much of the starter's offensive woes are primarily due to their neo-Twin Towers lineup. The Duncan-Aldridge pairing is the Spurs 5th least effective two-man lineup, with a -1.6 Net Rating in 155 minutes of play.

Of course, that figure mirrors the Spurs starting unit at large, and it's hard to tease out how much of the disfunction is simply those two sharing the court. It'll be interesting to see if Duncan and Aldridge share the floor as much as the season goes on, or if Pop opts to play one of the two alongside Diaw or West in smaller lineups.

All in all, it was a solid win as the Spurs overcame some big Portland advantages in second chance and transition points by executing well offensively and harassing the Blazers into poor, contested looks all night long. Let's keep the wins coming.

Four Factors (def.)

	Spurs	Trail Blazers
Shooting (eFG%)	57%	49%
Ball Handling (TO%)	12%	9%
Off Rebounding (OR%)	24%	23%
Shooting FTs (FT Rate)	22%	26%

Team Stats (Definitions at bottom of post)

	Spurs	Trail Blazers
Pace (No. of Possessions)	95.0
Points Per Possession (PPP)	1.19	1.06
Points Per Shot (PPS)	1.38	1.15
2-PT FG%	58.2%	45.5%
3-PT FG%	46.7%	40.9%
FT%	77.8%	60.9%
True Shooting %	62.8%	51.5%

	Spurs	Trail Blazers
Offensive Rating	121.6	104.0
Defensive Rating	104.0	121.6
Net Rating	17.6	-17.6

	Spurs	Trail Blazers
Passes / poss.	3.7	2.6
% of FGA uncontested	45.1%	31.8%
Points in the paint	46	36
Second chance points	6	19
Fast break points	7	16

	Spurs	Trail Blazers
Assists	27	26
Steals	4	6
Turnovers	11	9
Ball Control Index (BCI) (Assists + Steals) / TO	2.82	3.56

	Spurs	Trail Blazers
Expected Offensive Rebounds	8.5	11.0
Offensive Rebounds	8	10
Difference	-0.5	-1.0

Spurs Shot Chart

Trail Blazers Shot Chart

Players (Definitions at bottom of post, columns sortable)

Spurs

Player	Min	AdjGS	GS/Min	Line	Usage%	Floor%	OffRtg	DefRtg	NetRtg
Kawhi Leonard	35	19.1	0.55	20 Pts (7-14 FG, 1-5 3PT, 5-5 FT) 7 Reb (0 Off), 3 Ast, 1 Stl, 1 TO, 3 PF	24%	61%	119.0	116.8	2.2
LaMarcus Aldridge	35	15.7	0.45	23 Pts (9-18 FG, 0-1 3PT, 5-6 FT) 6 Reb (2 Off), 2 Ast, 1 Blk, 4 TO, 3 PF	33%	49%	123.2	116.8	6.5
Tim Duncan	21	14.5	0.68	12 Pts (5-7 FG, 2-3 FT) 6 Reb (0 Off), 2 Ast, 2 Blk, 1 Stl, 1 TO, 3 PF	22%	68%	105.5	122.0	-16.5
Manu Ginobili	22	14.3	0.64	14 Pts (6-12 FG, 1-2 3PT, 1-1 FT) 5 Reb (4 Off), 3 Ast, 3 PF	25%	59%	132.9	96.2	36.7
Tony Parker	30	12.7	0.43	11 Pts (5-8 FG, 1-2 FT) 1 Reb (0 Off), 5 Ast, 1 Stl, 3 PF	15%	71%	115.4	114.7	0.7
Danny Green	31	11.7	0.38	11 Pts (4-6 FG, 3-4 3PT, 0-1 FT) 4 Reb (0 Off), 2 Ast, 2 PF	10%	67%	111.3	111.0	0.3
Rasual Butler	15	8.0	0.53	5 Pts (2-3 FG, 1-1 3PT ) 3 Reb (0 Off), 3 Ast, 1 Stl, 1 TO	12%	61%	138.5	78.3	60.2
Boris Diaw	18	7.5	0.42	6 Pts (3-6 FG, 0-1 3PT ) 5 Reb (2 Off), 4 Ast, 1 TO, 2 PF	18%	54%	131.1	90.1	41.0
Patty Mills	18	7.3	0.40	7 Pts (3-3 FG, 1-1 3PT ) 1 Reb (0 Off), 1 Ast, 1 TO	10%	73%	131.9	86.6	45.3
David West	13	1.8	0.14	4 Pts (2-5 FG, ) 3 Reb (0 Off), 2 Ast, 1 Blk, 2 TO, 2 PF	27%	35%	113.6	77.6	36.0
Matt Bonner	1	0.4	0.39	0 Pts 1 Reb (0 Off),	0%	0%	200.0	0.0	200.0
Kyle Anderson	1	0.0	0.00	0 Pts ,	0%	0%	200.0	0.0	200.0
Ray McCallum	1	0.0	0.00	0 Pts ,	0%	0%	200.0	0.0	200.0

Show Trail Blazers Players

Player	Min	AdjGS	GS/Min	Line	Usage%	Floor%	OffRtg	DefRtg	NetRtg
Damian Lillard	37	19.8	0.54	22 Pts (7-19 FG, 5-8 3PT, 3-7 FT) 6 Reb (1 Off), 9 Ast, 1 Stl, 3 TO, 3 PF	32%	43%	113.1	122.0	-8.8
Ed Davis	18	19.7	1.11	11 Pts (5-5 FG, 1-2 FT) 6 Reb (3 Off), 3 Ast, 1 Blk, 2 Stl, 1 TO, 2 PF	18%	81%	78.0	130.4	-52.3
Mason Plumlee	30	17.1	0.56	9 Pts (3-7 FG, 3-6 FT) 9 Reb (4 Off), 4 Ast, 1 Blk, 2 Stl, 2 PF	14%	57%	119.2	116.4	2.8
Al-Farouq Aminu	33	10.6	0.32	11 Pts (4-11 FG, 2-6 3PT, 1-2 FT) 3 Reb (0 Off), 4 Ast, 1 Blk, 2 PF	16%	46%	122.6	115.5	7.1
Meyers Leonard	24	10.3	0.43	7 Pts (3-4 FG, 1-1 3PT ) 5 Reb (0 Off), 2 Ast, 1 PF	8%	79%	112.3	108.3	4.0
CJ McCollum	36	9.9	0.27	21 Pts (9-21 FG, 1-4 3PT, 2-2 FT) 1 Reb (1 Off), 2 Ast, 4 TO, 1 PF	31%	39%	112.6	105.6	7.0
Gerald Henderson	18	9.9	0.56	12 Pts (6-10 FG, ) 2 Reb (0 Off), 1 PF	25%	59%	107.3	138.4	-31.0
Allen Crabbe	20	3.1	0.16	6 Pts (1-6 FG, 0-2 3PT, 4-4 FT) 1 Reb (0 Off), 1 Ast, 1 Stl, 1 TO, 2 PF	20%	41%	80.7	146.1	-65.4
Noah Vonleh	7	1.6	0.21	2 Pts (1-2 FG, ) 2 Reb (0 Off), 1 PF	11%	49%	53.3	116.3	-62.9
Pat Connaughton	1	0.0	0.00	0 Pts (0-1 FG, ) 1 Reb (1 Off),	33%	0%	0.0	200.0	-200.0
Tim Frazier	1	0.0	0.00	0 Pts ,	0%	0%	0.0	200.0	-200.0
Maurice Harkless	16	-0.9	-0.06	0 Pts (0-2 FG, 0-1 3PT ) , 1 Ast,	6%	19%	72.4	140.6	-68.1

Spurs Index: 101.8 (def.)

Factor	Value	Score
Passing (AST%)	58.7%	28.4
Shooting (eFG%)	56.7%	21.1
Defensive Rebounding (DReb%)	77.3%	20.2
Defense (DefRtg)	104.0	19.3
Opponent % of FGA Uncontested	31.8%	12.8
Total		101.8

Trail Blazers Spurs Index: 95.1 Show Breakdown

Confused? Show Advanced Stats Glossary

eFG%: Effective Field Goal percentage. (via) Effective Field Goal Percentage; the formula is (FG + 0.5 * 3P) / FGA. This statistic adjusts for the fact that a 3-point field goal is worth one more point than a 2-point field goal. For example, suppose Player A goes 4 for 10 with 2 threes, while Player B goes 5 for 10 with 0 threes. Each player would have 10 points from field goals, and thus would have the same effective field goal percentage (50%).

AdjGS: a take-off of the Game Score metric (definition here) accepted by a lot of basketball stat nerds. It takes points, assists, rebounds (offensive & defensive), steals, blocks, turnovers and fouls into account to determine an individual's "score" for a given game. The "adjustment" in Adjusted Game Score is simply matching the total game scores to the total points scored in the game, thereby redistributing the game's points scored to those who had the biggest impact on the game itself, instead of just how many balls a player put through a basket.

Usage%: This "estimates the % of team possessions a player consumes while on the floor" (via). The usage of those possessions is determined via a formula using field goal and free throw attempts, offensive rebounds, assists and turnovers. The higher the number, the more prevalent a player is (good or bad) in a team's offensive outcome.

Floor%: Via Basketball-Reference.com: Floor % answers the question, "when Player X uses a possession, what is the probability that his team scores at least 1 point?". The higher the Floor%, the more frequently the team probably scores when the given player is involved.

Offensive Rating (offRtg): Points per 100 possessions.

Defensive Rating (defRtg): Points allowed per 100 possessions.

Spurs Index: The Spurs Index © is a just-for-fun formula that attempts to quantify just how "Spursy" a particular game is, based off averages for the 2013-2014 regular season. A perfectly average game would have a Spurs Index of 100. The formula consists of four factors which the Spurs are known for and lead or nearly lead the league in: Shooting (effective Field Goal %), Passing (Assist percentage), Defensive Rebounding Rate, and Defensive Rating. These metrics are weighted as follows:

Factor	Weight	Average
Passing (AST%)	30%	62.1%
Shooting (eFG%)	20%	53.7%
Defensive Rebounding (DReb%)	20%	76.4%
Defense (DefRtg)	20%	100.1
Opponent % of FGA Uncontested	10%	40.8%

The values for each metric are determined based on how a particular game's performance compares to the Spurs 2013-2014 regular season average for that metric. For instance, the average effective Field Goal percentage for 2013-2014 was 53.7%. So if the Spurs shot 60% in a given game, the score for eFG% would be calculated by: (0.6 / 0.537) * 20, which would yield a "score" for that factor of 22.3.

Special thanks to:

Bill Connelly over at our sister blog Rock M Nation, for the idea for Study Hall (and many of the stats and definitions)
Nick Bottomley, whose nba stats API project made it possible to automate the statistical breakdowns for every game