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Spurs 106, Pacers 92 - Dec 21, '15
The Indiana Pacers visited the Spurs in San Antonio on Tuesday, and though it took until the fourth quarter for the Spurs to pull away, the good guys wrapped up a solid 106-92 victory to maintain their perfect record at home this season. The marquee matchup appeared to be the two young guns at small forward for each team, until Kawhi Leonard did this to Paul George's game. George went 1-14 from the field, getting vexed at every opportunity by the mysticism of Leonard's otherworldly defense and finished with almost as many turnovers (6) as points (7). In what was an otherwise standard Spurs victory in December, the story of Kawhi's climb into the elite tier of NBA players remains this season's most fascinating ongoing storyline in San Antonio.
The speed of this game was right where the Spurs wanted it to be. The Pacers are in the top 10 in the NBA in Pace, and came into this matchup averaging nearly 99.5 possessions per game, but the Spurs kept them in check and slowed it down to a just-above-Spurs-average Pace of 96.3. And yet, San Antonio still put up 18 fast break points to only four for Indiana. These Spurs are what I like to refer to as an opportunistic fast break team - gone are the days of Tony Parker and Manu Ginobili repeatedly running opposing guards into the ground with one-man fast breaks, but this team will still pick and choose their spots to run on the opposition. With Kawhi Leonard seemingly getting his signature poke-steal-dunk at least once a game, and the picture-perfect outlet passes that the Spurs big men can execute on long rebounds, this team maintains its aura of efficiency even in the open floor. And boy, were there a lot of long rebounds...
The Pacers shot only 42.2%, with an absolutely horrendous and Lakers-level 46% Effective Field Goal Percentage, which gave the Spurs ample opportunity to snag those long rebounds and get out on the fast break. But long rebounds also give the offensive team a better chance to corral those misses as the ball often will carom past the defensive box out, and the Pacers were able to do just that, to the tune of 13 offensive rebounds and 18 second chance points. The Spurs lead the league in limiting opposing teams' second chance points, so this was likely just an unfortunate blip on the radar of a long season.
Boris Diaw had his croissant-covered fingerprints all over the game and punished the Pacers at will in the paint, taking whatever small-ball four Indiana tried to put on him down low and abusing him mercilessly. His 41.0 Net Rating in 25 minutes played is astounding, and the Pacers had no answer to his question of Qui peut me défendre? (That is French for "Who can defend me?" in case you were wondering.) It is a joy to watch this man play the game of basketball when he is fully engaged and looking to push the envelope. He so often is criticized for being too passive and unselfish, but it was refreshing to watch him be assertive and resolute against the smaller lineups of the Pacers, and bodes well for the future when the Spurs may face more of these types of lineups (*cough* Golden State *cough*). Boris helped the Spurs to a 62-38 advantage in points in the paint, and oh by the way, did these types of things too.
Tony Parker reminded the world that he can still pull the rabbit out of the hat, scoring nine of his 15 points in the decisive fourth quarter, and turned the Pacers perimeter (and interior) defense into unwilling spectators with plays like this:
This was a relatively clean game turnover-wise, as the Spurs executed their philosophy of not turning the ball over, coughing it up only nine times. Meanwhile the Pacers only had 14 themselves. The Spurs complimented their low turnover total by producing 27 assists, and I find it interesting that after having added LaMarcus Aldridge in the offseason (a more than capable isolation player) and watching Kawhi Leonard's one-on-one game improve by leaps and bounds, the Spurs are actually averaging more assists per game this year than last (25.3 to 24.4), and have a higher Assist Ratio this year as well (19.4% to 18.6%). Being able to mix up the looks on the offensive end of the floor makes this team that much more dangerous.
This victory was a perfectly average Spurs game, clocking in with a score of 100.1 on the Spurs Index. Unfortunately, George Hill's return was marred by a rogue furbee that refused to leave his head, causing all in attendance and those watching on TV to wonder whether blondes really do have more fun. In any event, the Spurs travel to Minnesota to take on the Timberwolves on Wednesday.
Four Factors (def.)
Spurs | Pacers | |
Shooting (eFG%) | 55% | 46% |
Ball Handling (TO%) | 10% | 14% |
Off Rebounding (OR%) | 17% | 26% |
Shooting FTs (FT Rate) | 10% | 17% |
Team Stats (Definitions at bottom of post)
Spurs | Pacers | |
Pace (No. of Possessions) | 96.3 | |
Points Per Possession (PPP) | 1.10 | 0.96 |
Points Per Shot (PPS) | 1.19 | 1.02 |
2-PT FG% | 58.0% | 43.7% |
3-PT FG% | 30.0% | 36.8% |
FT% | 88.9% | 60.0% |
True Shooting % | 57.0% | 47.6% |
Spurs |
Pacers | |
Offensive Rating | 111.6 | 94.3 |
Defensive Rating | 94.3 | 111.6 |
Net Rating | 17.4 | -17.4 |
Spurs | Pacers | |
Passes / poss. | 3.3 | 2.9 |
% of FGA uncontested | 40.4% | 38.9% |
Points in the paint | 62 | 38 |
Second chance points | 6 | 18 |
Fast break points | 18 | 4 |
Spurs | Pacers | |
Assists | 27 | 21 |
Steals | 8 | 5 |
Turnovers | 9 | 14 |
Ball Control Index (BCI) (Assists + Steals) / TO |
3.89 | 1.86 |
Spurs | Pacers | |
Expected Offensive Rebounds | 10.5 | 12.8 |
Offensive Rebounds | 7 | 13 |
Difference | -3.5 | 0.2 |
Spurs Shot Chart
Pacers 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 | 25.2 | 0.72 | 24 Pts (10-19 FG, 1-6 3PT, 3-3 FT) 6 Reb (1 Off), 5 Ast, 3 Stl, 2 PF | 27% | 61% | 105.0 | 85.8 | 19.2 |
Tony Parker | 28 | 13.0 | 0.47 | 15 Pts (7-12 FG, 1-1 3PT ) 1 Reb (0 Off), 4 Ast, 2 PF | 21% | 63% | 95.7 | 87.1 | 8.7 |
LaMarcus Aldridge | 27 | 12.7 | 0.47 | 10 Pts (4-11 FG, 2-2 FT) 9 Reb (3 Off), 1 Ast, 1 Blk, 3 Stl, 2 PF | 21% | 44% | 97.7 | 84.8 | 12.9 |
Boris Diaw | 25 | 11.1 | 0.44 | 14 Pts (7-9 FG, 0-1 3PT ) 8 Reb (2 Off), 1 Ast, 4 TO, 1 PF | 23% | 51% | 129.2 | 88.1 | 41.0 |
Tim Duncan | 23 | 10.2 | 0.45 | 7 Pts (3-6 FG, 1-1 FT) 5 Reb (1 Off), 3 Ast, 2 Blk, 2 Stl, 1 TO, 3 PF | 16% | 54% | 104.0 | 95.0 | 9.0 |
Patty Mills | 20 | 8.9 | 0.44 | 10 Pts (4-8 FG, 1-4 3PT, 1-2 FT) , 4 Ast, 1 PF | 20% | 59% | 132.9 | 104.1 | 28.8 |
David West | 17 | 7.7 | 0.46 | 7 Pts (3-5 FG, 1-1 FT) 5 Reb (0 Off), 1 Ast, 2 Blk, 1 TO, 1 PF | 18% | 56% | 130.3 | 117.5 | 12.9 |
Manu Ginobili | 20 | 7.6 | 0.37 | 7 Pts (3-6 FG, 1-2 3PT ) , 4 Ast, | 15% | 61% | 123.2 | 88.3 | 35.0 |
Jonathon Simmons | 11 | 5.9 | 0.53 | 7 Pts (3-4 FG, 1-1 3PT ) 3 Reb (0 Off), 2 Ast, 2 TO, 1 PF | 27% | 53% | 125.9 | 118.1 | 7.8 |
Boban Marjanovic | 2 | 3.3 | 1.71 | 2 Pts (1-1 FG, ) 2 Reb (0 Off), 1 Blk, | 25% | 100% | 50.0 | 100.0 | -50.0 |
Danny Green | 26 | 0.8 | 0.03 | 3 Pts (1-7 FG, 1-5 3PT ) 5 Reb (0 Off), 2 Ast, 1 Blk, 1 TO, 1 PF | 14% | 20% | 107.4 | 99.4 | 8.0 |
Kyle Anderson | 4 | 0.3 | 0.08 | 0 Pts 1 Reb (0 Off), | 0% | 0% | 100.0 | 111.1 | -11.1 |
Rasual Butler | 2 | -0.8 | -0.40 | 0 Pts (0-1 FG, ) , | 25% | 0% | 50.0 | 100.0 | -50.0 |
Show Pacers Players
Spurs Index: 100.1 (def.)
Factor | Value | Score |
Passing (AST%) | 58.7% | 28.4 |
Shooting (eFG%) | 55.1% | 20.5 |
Defensive Rebounding (DReb%) | 74.5% | 19.5 |
Defense (DefRtg) | 94.3 | 21.2 |
Opponent % of FGA Uncontested | 38.9% | 10.5 |
Total | 100.1 |
Pacers Spurs Index: 93.7 Show Breakdown
Confused? Hide 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% |
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