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The numbers from Spurs vs. Thunder don't tell the whole story

The Spurs turn in one of the Spursy-est performances of the year in a dismantling of the already mostly-dismantled Thunder.

Soobum Im-USA TODAY Sports

Spurs 130, Thunder 91 - Mar 25, '15











Russell Westbrook is a beast.  He is one of the most unstoppable players in the league, on a team which has become increasingly reliant on his offensive brilliance to produce wins.  The combination of his talent and the vacuum left by KD in the Thunder lineup has led to Westbrook going on a offensive tear which compares to some of Kobe's multi-game streaks, and his near-triple-double averages over the last two months have been nothing less than a throwback to the heyday of Oscar Robertson.  So when he turns in a relatively pedestrian line of 16-7-4, the Durant-less and Ibaka-less Thunder are in trouble.

There's a deluge of variations around an old sarcastic quip that the best way to win in sports is to outscore the other guy.  While all rules and adages have their exceptions, that one has been one of the more reliable pieces of advice to follow.  Needless to say, on a night where the Spurs collectively held the wall against Russell's one-man attack, the burden of outscoring the other guy was noticeably lightened.  That relatively lower bar, however, did not stop the Spurs from attacking on the offensive end like it was June 2014.

Four Factors (def.)






Spurs Thunder
Shooting (eFG%) 55% 43%
Ball Handling (TO%) 11% 10%
Off Rebounding (OR%) 29% 19%
Shooting FTs (FT Rate) 22% 16%






Perhaps the most maddening aspect of this Spurs season so far has been the flashes of brilliance surrounded by incredible inconsistency and mediocre play.  Against Dallas, we saw a classic case of the 3rd quarter Spurs when they begin to overthink the offense, when they pass up an makable shot for the sake of making one more pass, and the rim diameter suddenly shrinks by 50%.

Part of this is a necessary byproduct of Popovich's offensive schemes; he's been caught more than once cajoling his team to overpass rather than make a mistake in the other direction.  When that attitude is combined with an attack mentality, and the seemingly heretical idea that the team should score rather than the player, we begin to see the reemergence of the Spur's legendary Beautiful Game.

So what was the difference against OKC?  Did they underpass?  Did they go one-one-one more than they did against Dallas? Or did they just shoot better?  Did they suddenly and inexplicably start making the same shots they've been missing all year? Is it really just a matter of hoping that improbable hot streaks happen at the right time for your team?  What exactly is the point of "team" play if it's all just chance and statistics?

Team ball is a hard concept to capture in numbers, so we often rely on bulk numbers like total assists, total passes, passes-per-possession, etc.

Team Stats (Definitions at bottom of post)






Spurs Thunder
Pace (No. of Possessions) 96.8
Points Per Possession (PPP) 1.34 0.94
Points Per Shot (PPS) 1.48 1.01
2-PT FG% 56.7% 41.7%
3-PT FG% 61.9% 33.3%
FT% 78.9% 92.9%
True Shooting % 67.5% 47.3%
Offensive Rating 134.9 93.7
Defensive Rating 93.7 134.9
Net Rating 41.3 -41.3
Spurs Thunder
Passes / poss. 3.3 2.8
% of FGA uncontested 46.6% 42.2%
Points in the paint 56 40
Second chance points 13 6
Fast break points 11 11
Spurs Thunder
Assists 28 16
Steals 7 8
Turnovers 11 10
Ball Control Index (BCI)
(Assists + Steals) / TO
3.18 2.40
Spurs Thunder
Expected Offensive Rebounds 9.5 12.0
Offensive Rebounds 11 9
Difference 1.5 -3.0






While advanced analytics are improving, they can often understate the very point they're intended to make.  Take, for example, the % of uncontested shots taken by the two teams.  The Spurs' passing allowed them to take 46.6% percent of their shots open, while the Thunder had open looks on 42.2%.  That's a differential of 4.4%, which, while nice, is hardly overwhelming.  A team will often win a game despite being outshot by 4-5%, but that's not the case here; the Spurs FG% wasn't 4.4% better than the Thunder, it was 15% better from 2, and 28% better from 3.  That combined for an overall TS% advantage of 20.2%.  You might see a team occasionally overcome a deficit of 5-10% in that category, but 20%+ translates to early blowouts.

But again, this begs the question: are they simply shooting better?  Are mistakes in the offense and in the play calling being masked by a statistical outlier of made baskets?


Spurs Shot Chart

Thunder Shot Chart

Ultimately, the entire point of a pass is to move the ball in such a manner that the defense can't react quickly enough to prevent a high-percentage shot.  You could cross Usain Bolt with a cheetah, and that hybrid speed demon still wouldn't be fast enough to chase a ball being whipped around the court by trained professional athletes.  This logic tells us that the uncontested shot should be the gold standard of basketball offense, particularly for a team that runs offense the way San Antonio does.

But somehow, the number just doesn't bear that out.

Perhaps it's an artifact of the collection of data, but I suspect that it's also a matter of which player is taking the open shot, and where from.  While we were all delighted to see Duncan unleash one of his semi-annual three point attempts, having him take that shot, even while "uncontested" in normal play, is probably not the path to the Spurs' most efficient offense. Quite frankly, I wouldn't be surprised if Parker's "contested" floaters are higher percentage than some of Danny Green's "uncontested" drives.  It's a matter of recognizing the offensive strengths of every individual player, and running the offense to get a player, *any* player, a shot that he can make with high reliability.  For Danny Green, that's anywhere outside the arc with 5 feet of space.  For Parker, that's 10-18 feet with a split second to square up.  Kawhi's swiss-army-knife offensive game allows the Spurs to run enough iso to force a double team, which is the classic formula for getting a man open.

When all the players know their own spots, their own strengths, the strengths of their teammates, and the chinks in the armor of the opposing defense, we get treated to a game such as last night.  It's easy to say that they simply shot better, but that's not the whole story: they took the shots they were supposed to take.  In the failed comeback attempt against Dallas, Kawhi had an open look from 10 feet which he has been burying all year long, but he elected instead to dish to Tiago, who, while open, was too deep under the basket, and fumbled the unexpected pass.  Against OKC, there was no such hesitancy or overthinking from Kawhi or any other Spur; once they had their shot, they took it.

Players (Definitions at bottom of post, columns sortable)







Tony Parker 28 26.2 0.95 21 Pts (10-14 FG, 1-1 3PT ) 6 Reb (0 Off), 6 Ast, 3 Stl, 22% 79% 143.8 94.3 49.6
Kawhi Leonard 23 17.3 0.75 14 Pts (5-9 FG, 1-2 3PT, 3-4 FT) 5 Reb (1 Off), 5 Ast, 1 Blk, 1 Stl, 1 PF 20% 72% 146.5 88.6 57.8
Boris Diaw 25 15.1 0.61 19 Pts (9-15 FG, 1-1 3PT ) 6 Reb (3 Off), 1 Ast, 1 TO, 2 PF 28% 59% 140.9 101.6 39.2
Tim Duncan 27 13.5 0.50 16 Pts (5-9 FG, 1-1 3PT, 5-6 FT) 6 Reb (0 Off), 1 Ast, 1 Blk, 2 TO 22% 59% 138.6 95.4 43.2
Patty Mills 19 11.7 0.61 11 Pts (4-6 FG, 3-4 3PT ) 1 Reb (0 Off), 3 Ast, 15% 76% 125.9 88.9 37.0
Jeff Ayres 11 11.1 1.02 10 Pts (5-6 FG, 0-1 FT) 8 Reb (2 Off), 1 Ast, 1 TO 33% 68% 144.0 85.5 58.5
Danny Green 23 10.5 0.45 10 Pts (4-7 FG, 2-3 3PT ) 2 Reb (2 Off), 3 Ast, 1 Blk, 2 Stl, 2 TO, 3 PF 16% 52% 133.3 92.4 40.9
Tiago Splitter 16 6.3 0.39 9 Pts (3-6 FG, 3-4 FT) 4 Reb (1 Off), 1 Ast, 1 Blk, 2 TO, 2 PF 25% 50% 118.8 87.8 30.9
Manu Ginobili 15 5.5 0.37 7 Pts (1-3 FG, 1-3 3PT, 4-4 FT) 2 Reb (0 Off), 1 Stl, 1 TO, 2 PF 17% 58% 109.2 111.4 -2.2
Marco Belinelli 18 5.0 0.27 6 Pts (2-4 FG, 2-3 3PT ) 4 Reb (1 Off), 2 Ast, 2 TO, 1 PF 15% 41% 134.6 99.0 35.7
Matt Bonner 16 3.9 0.25 5 Pts (2-3 FG, 1-1 3PT ) 1 Reb (0 Off), 1 PF 10% 69% 121.1 97.5 23.6
Cory Joseph 10 2.2 0.22 2 Pts (1-4 FG, ) 1 Reb (0 Off), 3 Ast, 21% 48% 143.3 76.5 66.9
Reggie Williams 10 1.7 0.18 0 Pts (0-2 FG, 0-2 3PT ) 4 Reb (1 Off), 2 Ast, 10% 34% 143.3 76.5 66.9

Show Thunder Players






Aside from the ever-baffling anomaly that is Manu Ginobili, the Spur's players turned in uniformly spectacular offensive differentials.  This kind of offensive efficiency can't be achieved by simply taking uncontested shots; even the best passing game can only garner open looks at a clip in the 40%s.  This sort of stat line can only be done by getting players the shots they can make even while contested.  That's something that varies for each player, which is why the Spurs offensive schemes, while so highly regarded around the league, have been so difficult to duplicate, even for the Spurs themselves.  At current count, the two Popovich protégés Kerr and Bud are the only ones producing at a rate high enough to rival the originals.

Spurs Index: 99.4 (def.)






Factor Value Score
Passing (AST%) 54.9% 26.5
Shooting (eFG%) 55.1% 20.5
Defensive Rebounding (DReb%) 81.3% 21.3
Defense (DefRtg) 93.7 21.4
Opponent % of FGA Uncontested 42.2% 9.7
Total 99.4






Thunder Spurs Index: 79.8 Show Breakdown











Again, while I am occasionally skeptical of some advanced statistics, this particular cobbled-together indicator tells us almost perfectly what the eye-test was blaring at klaxon levels all last night: this is what the Spurs look like when they're The Spurs.  This is what it looks like when the needle isn't being forced to redline or left sputtering and stalling; this is what it looks like when it's purring along at the exact RPM optimally calculated to produce wins.

So long as they keep making shots, of course.








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 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.






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