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Spurs 103, Magic 91 - Apr 1, '15
The Spurs are making it a habit to win handily for the past few games and they had their easiest one yet against the Magic on Wednesday. The difference between a team gearing up for a playoff run and one looking forward to the offseason was evident. At no point was the outcome of the game in question, as the Magic simply didn't have the depth and cohesiveness to really bother the Spurs once they created some separation, courtesy of the second unit.
The Magic fired Jacque Vaughn mid-season because the team was not showing improvement but they are simply more than a coaching change away from figuring things out, as it was clear by their inability to get three-point shots and free throws. The Spurs actually posted a lower effective field goal percentage but because they took more outside shots and got to the line they had a significant difference in points per possession. The Magic got the edge on points in the paint but if they are not drawing fouls, they absolutely need to diversify their attack to include more three-pointers, something that might not be possible with the current roster.
The difficulty recognizing what shots make for an efficient offense also seems to affect how Orlando plays on defense. The Spurs not only got to the line 23 times and made the most of their opportunities there but also took 29 three-pointers, more than they average in the season. Some of those were completely open as well. Watching teams trying to figure out basic things offers a good reminder of how lucky we are to be Spurs fans.
Four Factors (def.)
Spurs
Magic
Shooting (eFG%)
42%
45%
Ball Handling (TO%)
11%
13%
Off Rebounding (OR%)
23%
27%
Shooting FTs (FT Rate)
27%
10%
Team Stats (Definitions at bottom of post)
Spurs
Magic
Pace (No. of Possessions)
95.5
Points Per Possession (PPP)
1.08
0.95
Points Per Shot (PPS)
1.20
0.98
2-PT FG%
38.6%
44.7%
3-PT FG%
44.8%
29.4%
FT%
87.0%
88.9%
True Shooting %
53.6%
46.9%
Spurs
Magic
Offensive Rating
107.2
95.8
Defensive Rating
95.8
107.2
Net Rating
11.3
-11.3
Spurs
Magic
Passes / poss.
3.6
2.8
% of FGA uncontested
54.7%
38.7%
Points in the paint
32
50
Second chance points
16
8
Fast break points
8
12
Spurs
Magic
Assists
20
24
Steals
8
7
Turnovers
10
12
Ball Control Index (BCI)
(Assists + Steals) / TO
2.80
2.58
Spurs
Magic
Expected Offensive Rebounds
11.8
13.0
Offensive Rebounds
11
14
Difference
-0.8
1.0
Spurs Shot Chart
Magic Shot Chart
The Spurs went 6-for-8 from the corners and it's obvious how much better they are when they make those. There seems to be correlation between efficiency from the corner and wins. Last season, the Spurs shot 26.2 percent on losses from the corner and 45.2 percent on wins. This season those numbers are 37.9 percent and 44.3 percent. So when you see those corner threes falling it probably means the Spurs are playing well.
Players (Definitions at bottom of post, columns sortable)
Spurs
Aron Baynes
24
16.4
0.69
18 Pts (5-10 FG, 8-8 FT) 5 Reb (2 Off), 1 Blk, 2 TO, 1 PF
28%
61%
113.8
82.4
31.4
Manu Ginobili
18
16.1
0.91
13 Pts (4-7 FG, 3-5 3PT, 2-2 FT) 3 Reb (0 Off), 3 Ast, 2 Stl, 1 TO, 1 PF
22%
63%
128.7
59.7
69.0
Boris Diaw
24
15.0
0.63
11 Pts (4-9 FG, 2-5 3PT, 1-1 FT) 4 Reb (1 Off), 4 Ast, 1 Blk, 2 Stl, 1 TO
19%
52%
129.8
60.2
69.7
Kawhi Leonard
21
13.9
0.67
10 Pts (3-7 FG, 2-2 3PT, 2-2 FT) 7 Reb (1 Off), 1 Ast, 2 Stl,
18%
56%
104.4
111.9
-7.5
Tiago Splitter
21
8.8
0.42
8 Pts (3-8 FG, 2-2 FT) 7 Reb (4 Off), 2 Ast, 1 TO, 1 PF
22%
47%
112.0
99.2
12.8
Marco Belinelli
30
8.6
0.28
12 Pts (4-12 FG, 3-7 3PT, 1-2 FT) 4 Reb (0 Off), 3 Ast, 1 Stl, 2 TO
21%
36%
103.4
90.4
13.0
Tony Parker
22
6.4
0.29
7 Pts (2-7 FG, 1-1 3PT, 2-2 FT) , 4 Ast, 1 PF
17%
53%
111.2
104.0
7.2
Cory Joseph
26
6.4
0.25
8 Pts (4-8 FG, 0-1 3PT ) 7 Reb (0 Off), 2 Ast, 1 TO, 3 PF
15%
49%
104.0
89.3
14.7
Patty Mills
12
4.4
0.36
3 Pts (1-4 FG, 1-4 3PT ) 3 Reb (1 Off), 1 Ast, 1 Stl,
14%
33%
88.8
136.2
-47.4
Tim Duncan
12
3.7
0.31
6 Pts (2-5 FG, 2-4 FT) 3 Reb (0 Off), 1 Blk, 1 TO
29%
39%
98.2
108.9
-10.7
Matt Bonner
9
2.1
0.22
2 Pts (1-2 FG, 0-1 3PT ) 1 Reb (1 Off),
10%
50%
65.2
171.8
-106.6
Danny Green
15
0.6
0.04
3 Pts (1-3 FG, 1-3 3PT ) 2 Reb (0 Off), 1 TO, 1 PF
12%
23%
105.8
100.4
5.4
Jeff Ayres
6
0.6
0.11
2 Pts (1-4 FG, ) 3 Reb (1 Off), 1 PF
31%
25%
36.4
156.3
-119.9
Show Magic Players
Aron Baynes had a career-high 18 points along with five rebounds to round up a very productive 24 minutes. It's hard to overstate how much he's evolved this year. He's not fouling as much, his defense is better and even his 15 footer has become reliable.
As good as Baynes was, Manu Ginobili was better on a per minute basis. Manu did a little bit of everything and had his shot going, which always makes things easier for him on the offensive side. Hopefully, his touch from outside won't abandon him again.
Spurs Index: 94.0 (def.)
Factor
Value
Score
Passing (AST%)
57.1%
27.6
Shooting (eFG%)
42.4%
15.8
Defensive Rebounding (DReb%)
73.1%
19.1
Defense (DefRtg)
95.8
20.9
Opponent % of FGA Uncontested
38.7%
10.5
Total
94.0
Magic Spurs Index: 92.9 Show Breakdown
The Spurs had fewer assists than their opponent and shot poorly from inside the arc but won thanks to their ability to get to the line. That statement obviously doesn't describe most Spurs wins, which makes the low score on the Spurs Index unsurprising.
--- Definitions 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:
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.
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