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Stats breakdown: Ball-movement, Kawhi Leonard enough to beat the Magic

The Spurs moved the ball well to find open three-point shooters and received a huge boost from their young star in the win over the Magic.

Soobum Im-USA TODAY Sports

Spurs 110, Magic 103 - Feb 4, '15

No matter the opponent, no matter how well a specific player performs, the Spurs have a hard time stringing together enough good possessions to take control of the score against teams that put up a fight lately. Not even great nights from Duncan, Ginobili and Leonard were enough to prevent this one from staying close throughout. Of course there are occasions in which everything clicks -- the victory over the Blazers in Jan. 16 comes to mind -- but recently games like Wednesday's against the Magic seem to be the norm. And that's fine! There's still time to get better. For now, I'm sure the team will gladly take the wins, however they may come.

Four Factors (def.)

Spurs Magic
Shooting (eFG%) 55% 56%
Ball Handling (TO%) 12% 13%
Off Rebounding (OR%) 15% 13%
Shooting FTs (FT Rate) 17% 17%

The Spurs would typically thrive on a low turnover, low offensive rebounding game because of their defense but they couldn't contain Orlando's main scorers on Wednesday. Fortunately, the Magic are a bad enough team that it didn't matter.

Team Stats (Definitions at bottom of post)

Spurs Magic
Pace (No. of Possessions) 96.7
Points Per Possession (PPP) 1.14 1.07
Points Per Shot (PPS) 1.31 1.23
2-PT FG% 57.7% 50.8%
3-PT FG% 43.8% 47.6%
FT% 57.1% 64.3%
True Shooting % 61.0% 57.1%
Offensive Rating 115.6 104.9
Defensive Rating 104.9 115.6
Net Rating 10.7 -10.7
Spurs Magic
Passes / poss. 3.8 2.8
% of FGA uncontested 48.8% 39.3%
Points in the paint 40 46
Second chance points 9 7
Fast break points 7 16
Spurs Magic
Assists 32 27
Steals 7 6
Turnovers 11 12
Ball Control Index (BCI)
(Assists + Steals) / TO
3.55 2.75
Spurs Magic
Expected Offensive Rebounds 10.0 10.0
Offensive Rebounds 6 5
Difference -4.0 -5.0

Let's talk about the glorious JV, the recently fired coach of the Magic, Jacque Vaughn. With the players the Magic has, a 96.6 pace is way too slow. After playing at one of the league's slowest paces in December, Vaughn tried to get his guys to speed up. It didn't produce results but at least gave the Magic an identity to build on. Then they reverted back to old habits and now Vaughn is gone. He never really had a chance with the roster his GM assembled but the JV couldn't actually put his imprint on the team and now Pop's coaching tree has a branch that has fallen unceremoniously.

With that out of the way, please feast your eyes on those free throw percentages. Neither team got to the line enough for it to matter (a combined 28 free throws) but Elfrid Payton (2-6), Manu Ginobili (0-2) and Tim Duncan (4-8) better work on those freebies.

The Spurs not only averaged more passes per possession but also controlled the BCI index thanks to their 32 assists, the sixth time in the season in which they log over 30 assists. Interesting fact: The Spurs have lost two of those games, the first against the Grizzlies in triple overtime and the other against the Thunder. Last season they won all 16 games in which they averaged over 30 assists.

Spurs Shot Chart

Magic Shot Chart

The Spurs made a killing from the corners and inside while the Magic couldn't buy a bucket from the left baseline.

Players (Definitions at bottom of post, columns sortable)


Kawhi Leonard 38 23.9 0.64 18 Pts (7-9 FG, 4-4 FT) 5 Reb (0 Off), 5 Ast, 1 Blk, 4 Stl, 3 TO 17% 68% 104.9 107.2 -2.3
Tim Duncan 34 23.1 0.69 26 Pts (11-17 FG, 4-8 FT) 10 Reb (1 Off), 1 Ast, 1 Blk, 1 Stl, 1 TO, 3 PF 30% 59% 101.0 120.7 -19.6
Manu Ginobili 29 16.8 0.58 13 Pts (5-9 FG, 3-5 3PT, 0-2 FT) 6 Reb (0 Off), 10 Ast, 1 TO, 2 PF 18% 60% 140.4 87.5 52.9
Marco Belinelli 17 9.5 0.55 11 Pts (4-6 FG, 3-4 3PT ) 1 Reb (0 Off), 1 Ast, 1 TO 20% 55% 137.3 88.2 49.1
Patty Mills 18 7.9 0.43 9 Pts (3-8 FG, 3-8 3PT ) 1 Reb (0 Off), 3 Ast, 1 Stl, 1 TO 25% 39% 141.1 82.6 58.4
Tony Parker 30 7.4 0.25 15 Pts (6-15 FG, 3-5 3PT ) , 3 Ast, 2 TO, 1 PF 26% 37% 101.9 116.7 -14.8
Boris Diaw 19 6.4 0.33 4 Pts (2-3 FG, 0-1 3PT ) 2 Reb (1 Off), 3 Ast, 1 Blk, 2 PF 7% 75% 95.9 128.3 -32.5
Danny Green 26 5.4 0.21 6 Pts (2-9 FG, 2-9 3PT ) 5 Reb (1 Off), 3 Ast, 1 Blk, 1 Stl, 1 TO, 1 PF 19% 27% 102.7 111.6 -8.9
Aron Baynes 14 5.0 0.34 4 Pts (2-3 FG, ) 9 Reb (3 Off), 1 TO, 3 PF 14% 44% 154.6 63.2 91.3
Cory Joseph 16 4.5 0.29 4 Pts (2-5 FG, ) 2 Reb (0 Off), 3 Ast, 15% 51% 123.1 106.9 16.2

Show Magic Players

Kawhi has become a fixture at the top of the Adjusted Game Score list. Big Fun was actually more productive per minute and extremely consistent, scoring six, seven, seven and six in each quarter. Still, Leonard deserves player of the game because 18 points in 9 shots, five rebounds, four assists and four steals is just a ridiculous line. Manu Ginobili had a really great game as well, logging 10 assists to just one turnover. Marco Belinelli also had a solid night in his return.

For the Magic, Tobias Harris and Nikola Vucevic broke away from the pack thanks to monster nights against Boris Diaw and Tim Duncan. Vucevic is not a good defender but few centers are as consistently productive. Harris will become a restricted free agent and will get seriously paid. In the right team his lack of an ideal position won't matter but if he's inked by the wrong franchise, he could be one of those signings that are later regretted. I'm not sure where the Magic fall on that spectrum.

Spurs Index: 107.9 (def.)

Factor Value Score
Passing (AST%) 72.7% 35.1
Shooting (eFG%) 54.8% 20.4
Defensive Rebounding (DReb%) 87.5% 22.9
Defense (DefRtg) 104.9 19.1
Opponent % of FGA Uncontested 39.3% 10.4
Total 107.9

Magic Spurs Index: 97.8 Show Breakdown

Few offensive rebounds allowed? Check. A lot of assists? Check. That's enough to make this game do well on the Spurs Index but the defense needs to improve.



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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