OFFENSE
|
DEFENSE
|
TOTAL
|
||||||
Team
|
SUM
|
RANK
|
SUM
|
RANK
|
SUM
|
RANK
|
||
Minnesota
|
36
|
2
|
53
|
10
|
89
|
1
|
||
Oklahoma
City
|
48
|
8
|
43
|
5
|
91
|
2
|
||
L.A.
Clippers
|
34
|
1
|
59
|
17
|
93
|
3
|
||
Portland
|
36
|
2
|
57
|
14
|
93
|
3
|
||
Houston
|
37
|
4
|
58
|
16
|
95
|
5
|
||
San
Antonio
|
64
|
15
|
35
|
2
|
99
|
6
|
||
Memphis
|
58
|
13
|
44
|
8
|
102
|
7
|
||
Toronto
|
47
|
6
|
56
|
13
|
103
|
8
|
||
Charlotte
|
68
|
18
|
38
|
4
|
106
|
9
|
||
Chicago
|
76
|
24
|
33
|
1
|
109
|
10
|
||
Golden
State
|
69
|
20
|
43
|
5
|
112
|
11
|
||
Indiana
|
79
|
26
|
36
|
3
|
115
|
12
|
||
Phoenix
|
47
|
6
|
68
|
18
|
115
|
12
|
||
Washington
|
73
|
22
|
43
|
5
|
116
|
14
|
||
Cleveland
|
66
|
17
|
53
|
10
|
119
|
15
|
||
Sacramento
|
49
|
9
|
72
|
19
|
121
|
16
|
||
Miami
|
65
|
16
|
57
|
14
|
122
|
17
|
||
Dallas
|
51
|
10
|
78
|
24
|
129
|
18
|
||
Denver
|
57
|
12
|
73
|
21
|
130
|
19
|
||
Atlanta
|
80
|
27
|
52
|
9
|
132
|
20
|
||
New
Orleans
|
45
|
5
|
90
|
28
|
135
|
21
|
||
Detroit
|
56
|
11
|
81
|
25
|
137
|
22
|
||
New
York
|
61
|
14
|
77
|
23
|
138
|
23
|
||
Orlando
|
84
|
29
|
55
|
12
|
139
|
24
|
||
Brooklyn
|
68
|
18
|
72
|
19
|
140
|
25
|
||
Boston
|
81
|
28
|
75
|
22
|
156
|
26
|
||
L.A.
Lakers
|
78
|
25
|
85
|
26
|
163
|
27
|
||
Utah
|
73
|
22
|
91
|
29
|
164
|
28
|
||
Milwaukee
|
71
|
21
|
95
|
30
|
166
|
29
|
||
Philadelphia
|
103
|
30
|
88
|
27
|
191
|
30
|
||
Similar to my NFL Performance Ratings these break each team
down using the metrics & statistics I have tested and found to be of the
highest correlation to team success. One
aspect to keep in mind is the ratings above are best when lower compared to NFL
ratings that are best when higher. We
can use these ratings numerous ways, identifying teams that may be over or
under valued, or also for total players identifying which matchups could
produce more or less points. Last key
item of note is these ratings weight each stat equally, where below in my
projected wins & power ratings they are properly weighted to their impact
based on statistical testing. Using an
equal weight for each statistic can add a lot of value to your handicapping
efforts when properly applied.
For this final version let’s add a matrix that shows where
each team ranked in the above non-weighted performance ratings throughout
different points of the season:
ASB
|
|||||||||||||
19-Dec
|
26-Dec
|
2-Jan
|
9-Jan
|
15-Jan
|
23-Jan
|
27-Jan
|
2-Feb
|
9-Feb
|
13-Feb
|
5-Mar
|
20-Mar
|
FINAL
|
|
Atlanta
|
12
|
12
|
9
|
16
|
15
|
10
|
14
|
15
|
17
|
17
|
17
|
21
|
20
|
Boston
|
25
|
26
|
26
|
27
|
28
|
27
|
27
|
27
|
27
|
26
|
26
|
26
|
26
|
Brooklyn
|
23
|
24
|
24
|
21
|
24
|
22
|
22
|
22
|
22
|
22
|
23
|
23
|
25
|
Charlotte
|
7
|
5
|
9
|
9
|
10
|
9
|
10
|
10
|
11
|
12
|
10
|
11
|
9
|
Chicago
|
16
|
15
|
11
|
13
|
10
|
12
|
13
|
11
|
10
|
8
|
9
|
11
|
10
|
Cleveland
|
26
|
22
|
22
|
20
|
21
|
19
|
18
|
20
|
21
|
21
|
15
|
13
|
15
|
Dallas
|
21
|
20
|
20
|
24
|
22
|
23
|
23
|
20
|
20
|
18
|
22
|
20
|
18
|
Denver
|
10
|
12
|
17
|
10
|
9
|
13
|
11
|
14
|
14
|
15
|
19
|
18
|
19
|
Detroit
|
13
|
10
|
16
|
22
|
19
|
16
|
20
|
18
|
15
|
13
|
16
|
16
|
22
|
Golden State
|
18
|
19
|
12
|
13
|
12
|
13
|
15
|
12
|
12
|
10
|
10
|
8
|
11
|
Houston
|
9
|
9
|
8
|
7
|
8
|
7
|
7
|
6
|
4
|
6
|
3
|
5
|
5
|
Indiana
|
1
|
1
|
2
|
2
|
2
|
3
|
5
|
7
|
7
|
7
|
6
|
8
|
12
|
LA Clippers
|
8
|
7
|
4
|
5
|
6
|
6
|
5
|
5
|
5
|
5
|
3
|
2
|
3
|
LA Lakers
|
27
|
27
|
28
|
26
|
26
|
26
|
26
|
26
|
26
|
26
|
28
|
27
|
27
|
Memphis
|
19
|
18
|
13
|
11
|
12
|
10
|
9
|
9
|
9
|
10
|
12
|
8
|
7
|
Miami
|
16
|
11
|
14
|
13
|
18
|
19
|
17
|
19
|
22
|
22
|
19
|
19
|
17
|
Milwaukee
|
29
|
29
|
29
|
30
|
30
|
30
|
30
|
30
|
30
|
29
|
29
|
29
|
29
|
Minnesota
|
2
|
1
|
1
|
1
|
1
|
1
|
1
|
1
|
1
|
1
|
1
|
1
|
1
|
New Orleans
|
11
|
17
|
15
|
19
|
19
|
21
|
18
|
17
|
17
|
16
|
21
|
22
|
21
|
New York
|
22
|
24
|
25
|
24
|
23
|
25
|
24
|
24
|
24
|
24
|
25
|
24
|
23
|
Okla City
|
4
|
3
|
7
|
5
|
3
|
4
|
4
|
2
|
3
|
4
|
2
|
3
|
2
|
Orlando
|
25
|
23
|
23
|
23
|
25
|
24
|
25
|
25
|
25
|
25
|
24
|
24
|
24
|
Philadelphia
|
28
|
27
|
27
|
28
|
27
|
28
|
29
|
29
|
29
|
30
|
30
|
30
|
30
|
Phoenix
|
20
|
20
|
18
|
18
|
16
|
13
|
12
|
13
|
13
|
14
|
13
|
13
|
12
|
Portland
|
7
|
6
|
5
|
4
|
3
|
4
|
3
|
4
|
2
|
2
|
5
|
3
|
3
|
Sacramento
|
14
|
12
|
18
|
11
|
12
|
17
|
21
|
23
|
19
|
20
|
18
|
13
|
16
|
San Antonio
|
7
|
3
|
6
|
8
|
7
|
8
|
8
|
8
|
8
|
9
|
8
|
6
|
6
|
Toronto
|
4
|
8
|
3
|
3
|
3
|
2
|
2
|
2
|
5
|
2
|
6
|
6
|
8
|
Utah
|
30
|
30
|
30
|
29
|
29
|
29
|
28
|
28
|
28
|
28
|
27
|
28
|
28
|
Washington
|
17
|
15
|
21
|
16
|
17
|
18
|
16
|
16
|
15
|
18
|
13
|
16
|
14
|
Next up let’s take a closer look at the above matrices, and
provide some color behind a few teams that “stand out” for seemingly rating
higher or lower than their final record.
Minnesota:
the Timberwolves have been ranked #1 for 12 of the 13 editions we published
including each of the last 12 since Christmas.
Why did a mere 40-42 team rate so highly? The answer is very simple – Minnesota was
very solid in all categories that comprise this analysis besides the biggest
one on each side of the ball: Effective FG%.
The Wolves were ranked 21st offensively & 27th
defensively in that area, which is the most heavily weighted statistic when
using linear regression as I do below.
Portland &
Houston: these teams are matching up in the opening round of the
Western Conference playoffs, and were ranked tied for 3rd & 5th
respectively in these ratings – very solid obviously. Both teams had Top 4 offenses and mid ranked
defenses – look for a lot of points, with turnovers (especially for Houston
both sides of the floor) & offensive rebounding being key drivers to the
winner of this series.
Western
Conference: of the 15 teams in the conference 7 rated #1 thru #7 here,
and just 2 rated amongst the bottom 9 teams – shows how strong that conference
is.
Toronto, Charlotte
& Chicago: here is a trio of teams we made a lot of cash backing
this season, and they check in at #8, #9 & #10 overall – the top 3 teams in
the Eastern Conference. Although they
are the top 3 teams in the conference using the equally weighted method they
slip in the linear weighted model because of average to poor EFG%, especially
offensively. These teams, especially the
latter two, are best known for their work on the defensive end – which is where
they will no question need to excel in order to advance in the playoffs.
Brooklyn:
the Nets check in at #25, easily the lowest rated team in the playoffs this
season – even the lowly Hawks are ranked #20!
What does it all mean? Brooklyn
is very much a middle of the road team AT BEST when using full regular season
statistics as even their EFG% numbers are middle of the pack – and they frankly
do not excel in any one area besides possibly defensive pressure/forcing
turnovers (which was assisted by the Livingston addition to the starting lineup
in early calendar year 2014) and getting to the FT line offensively – both
areas they leveraged to pick up a win in Toronto in Game One.
Next let’s dive into the Power Ratings which use the
Performance Rankings as a base:
HOME
|
ROAD
|
|
Power Rating
|
Power Rating
|
|
L.A. Clippers
|
117.0
|
113.0
|
San Antonio
|
116.2
|
112.7
|
Miami
|
116.0
|
112.5
|
Golden State
|
115.5
|
112.5
|
Oklahoma City
|
116.2
|
112.2
|
Dallas
|
114.7
|
111.7
|
Toronto
|
114.3
|
111.3
|
Phoenix
|
114.2
|
111.2
|
Washington
|
113.3
|
110.8
|
Houston
|
114.5
|
110.5
|
Memphis
|
113.1
|
110.1
|
Indiana
|
113.7
|
109.7
|
Minnesota
|
112.2
|
109.7
|
New York
|
111.6
|
109.6
|
Portland
|
112.7
|
109.2
|
Charlotte
|
111.9
|
108.9
|
Chicago
|
111.8
|
108.8
|
Brooklyn
|
110.9
|
107.9
|
New Orleans
|
110.3
|
107.8
|
Detroit
|
109.5
|
107.5
|
Atlanta
|
109.6
|
107.1
|
Denver
|
109.4
|
106.9
|
Cleveland
|
108.8
|
106.8
|
Sacramento
|
108.6
|
106.6
|
Boston
|
108.5
|
106.5
|
Orlando
|
106.5
|
104.5
|
L.A. Lakers
|
105.6
|
103.6
|
Utah
|
105.4
|
103.4
|
Milwaukee
|
105.2
|
103.2
|
Philadelphia
|
102.0
|
100.0
|
These are actually Power Ratings that can be used when
handicapping nightly matchups.
Keep in mind however that when the playoffs commence ratings
become more hyper-sensitive to variance in performance, and are adjusted
slightly from what you see above. But
these can still be used as a solid estimate – let’s take a look at projected
lines for Game One of each series versus the actual line posted in Vegas:
[#1] PACERS -6.5
[#8] hawks Vegas line: -8 Variance: 1.5 points
[#2] HEAT -7
[#7] bobcats Vegas line: -9.5 Variance: 2.5 points
[#3] RAPTORS -6.5 [#6] nets Vegas
line: -3.5 Variance: (3.0)
points
[#4] BULLS -1 [#5] wizards Vegas line: -4.5 Variance: 3.5 points
[#1] SPURS -4.5 [#8] mavericks Vegas line: -9.5 Variance:
5.0 points
[#2] THUNDER -6 [#7] grizzlies Vegas line: -8 Variance: 2.0 points
[#3] CLIPPERS -4.5 [#6] warriors Vegas line: -7.5 Variance: 3.0 points
[#4] ROCKETS -5.5 [#5] blazers Vegas line: -5 Variance: (0.5) points
What initially really jumps off the page is the fact 6 of the 8 lines (and another is just 0.5 points below & may still move on Sunday to positive territory) are HIGHER on the favorite in Vegas compared to my ratings - which makes perfect sense since Vegas routinely adjusts odds on favorites up based on the public typically backing the favorites. For Saturday’s games my ratings suggested plays on Hawks, Raptors, Grizzlies & Warriors – 3 of 4 underdogs; the pair of 3pt variances split while the two smaller variance plays also split. However, remember, line value is only one small piece of the handicapping puzzle – and unlike the regular season there are small adjustments made to these ratings in the playoffs designed to further accentuate the performance fluctuation by team.
Lastly let’s take a look at wins by team in three critical
buckets: ATS Win %, Final Wins, Regression Wins. Also we will examine the variance between
actual & regression wins:
ATS WIN %
|
FINAL ACTUAL WINS
|
REGRESS WINS
|
ACTUAL - REGRESS WINS
|
||||||||
Wins
|
RANK
|
Wins
|
RANK
|
Wins
|
RANK
|
Wins
|
RANK
|
||||
L.A. Clippers
|
0.568
|
4
|
57.0
|
3
|
59.4
|
1
|
(2.4)
|
21
|
|||
San Antonio
|
0.549
|
5
|
62.0
|
1
|
56.8
|
2
|
5.2
|
9
|
|||
Miami
|
0.463
|
24
|
54.0
|
5
|
56.4
|
3
|
(2.4)
|
20
|
|||
Golden State
|
0.519
|
10
|
51.0
|
8
|
55.0
|
4
|
(4.0)
|
15
|
|||
Oklahoma City
|
0.538
|
6
|
59.0
|
2
|
54.3
|
5
|
4.7
|
11
|
|||
Dallas
|
0.537
|
7
|
49.0
|
10
|
51.4
|
6
|
(2.4)
|
22
|
|||
Toronto
|
0.582
|
3
|
48.0
|
11
|
49.6
|
7
|
(1.6)
|
25
|
|||
Phoenix
|
0.642
|
1
|
48.0
|
11
|
49.0
|
8
|
(1.0)
|
27
|
|||
Washington
|
0.531
|
9
|
44.0
|
14
|
48.7
|
9
|
(4.7)
|
12
|
|||
Houston
|
0.500
|
13
|
54.0
|
5
|
48.4
|
10
|
5.6
|
6
|
|||
Memphis
|
0.456
|
25
|
50.0
|
9
|
48.2
|
11
|
1.8
|
24
|
|||
Indiana
|
0.469
|
20
|
56.0
|
4
|
47.1
|
12
|
8.9
|
2
|
|||
Minnesota
|
0.476
|
18
|
40.0
|
17
|
45.4
|
13
|
(5.4)
|
7
|
|||
New York
|
0.463
|
23
|
37.0
|
19
|
43.9
|
14
|
(6.9)
|
4
|
|||
Portland
|
0.537
|
7
|
54.0
|
5
|
43.5
|
15
|
10.5
|
1
|
|||
Charlotte
|
0.595
|
2
|
43.0
|
16
|
42.4
|
16
|
0.6
|
28
|
|||
Chicago
|
0.506
|
12
|
48.0
|
11
|
42.3
|
17
|
5.7
|
5
|
|||
Brooklyn
|
0.512
|
11
|
44.0
|
14
|
40.4
|
18
|
3.6
|
17
|
|||
New Orleans
|
0.487
|
17
|
34.0
|
21
|
37.7
|
19
|
(3.7)
|
16
|
|||
Detroit
|
0.432
|
29
|
29.0
|
23
|
37.6
|
20
|
(8.6)
|
3
|
|||
Atlanta
|
0.469
|
20
|
38.0
|
18
|
36.2
|
21
|
1.8
|
23
|
|||
Denver
|
0.476
|
18
|
36.0
|
20
|
35.4
|
22
|
0.6
|
29
|
|||
Cleveland
|
0.488
|
15
|
33.0
|
22
|
34.3
|
23
|
(1.3)
|
26
|
|||
Sacramento
|
0.468
|
22
|
28.0
|
24
|
30.7
|
24
|
(2.7)
|
19
|
|||
Boston
|
0.488
|
16
|
25.0
|
26
|
28.1
|
25
|
(3.1)
|
18
|
|||
Orlando
|
0.430
|
30
|
23.0
|
28
|
27.5
|
26
|
(4.5)
|
14
|
|||
L.A. Lakers
|
0.500
|
13
|
27.0
|
25
|
21.8
|
27
|
5.2
|
10
|
|||
Utah
|
0.434
|
28
|
25.0
|
26
|
20.4
|
28
|
4.6
|
13
|
|||
Milwaukee
|
0.444
|
26
|
15.0
|
30
|
20.3
|
29
|
(5.3)
|
8
|
|||
Philadelphia
|
0.439
|
27
|
19.0
|
29
|
19.5
|
30
|
(0.5)
|
30
|
|||
The first column ATS Win % is not only impacted by actual
team performance but also certainly by other factors that are tough to measure
but we know they exist such as expectations & public teams. Team expectations at the beginning of the
season certainly plays a critical role in ATS performance because perceived
“good” teams people will continually wait on if they start slow (New York),
while perceived “bad” teams people will continually wait and/or bet on to
flounder after a hot start which sometimes doesn’t occur (Phoenix). We also see teams such as Miami who checks in
at #24 in ATS performance largely driven by the fact they are more actively
managing the regular season grind compared to most other teams, with a clear
eye on winning another championship.
Understanding these largely unmeasurable variables is absolutely
critical to having success betting on the NBA because the season is such a long
grind, and emotional levels, lineups, injuries, motivation and other human
behaviors are key in the NBA compared to say the NFL where every team plays
once per week and is typically motivated equally.
Perhaps the most critical piece of this final NBA analysis
entry of the season is the far right column.
As a reminder let’s define regression wins: this figure represents how
many games a team is projected to win based on their performance in specific
statistical categories I have defined (with help from many other books &
intelligent NBA executives) as having the greatest impact on winning games,
properly weighted using linear regression.
The statistics & weights will remain for my eyes only as that is
proprietary, but we can discuss the results in some detail that will provide
insight into my process to the astute reader.
One item of note is the rank column for the actual minus regression wins
metric uses absolute values of the variances to better represent which teams
were furthest or closest to actual wins.
Based on this metric let’s take a closer look at the playoff teams from
each conference, and possibly identify teams that are over or under valued
based on their true statistical performance this season. In total of the 16 playoff teams 10 posted a
record better than their true performance suggested (5 in each conference) –
but who has the biggest variances?
CHECK BACK TOMORROW FOR A DETAILED ANALYSIS OF EACH PLAYOFF SERIES.
Email me directly: boss@thesportsboss.com
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