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Examining 2018 fantasy football wide receiver efficiency stats

Examining 2018 fantasy football wide receiver efficiency stats

Fantasy football statistical analysis

Examining 2018 fantasy football wide receiver efficiency stats

By July 16, 2019 4:04 pm

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Numbers can lie. They often do in fantasy football. Context is everything, and raw, season-long stats can be the worst. Yet, every year, fantasy football prognosticators and gamers rely heavily on using these very data points to create arguments for or against a player.

In today’s exercise, I won’t suggest much of anything based on the data but rather let it speak for itself. Ranking placements using last year’s numbers are not an endorsement or case against a player in 2019 drafts.

In the first table, we’ll look at metrics from 2018 wide receivers based on the following data:

Reception rate: The percentage of overall targets caught. This does not exclude uncatchable passes.

Yards per reception: What does a player do with the ball in his hands, regardless of where he caught it. Subtracting average air yards per target (AAYPT) may be a more accurate to illustrate a player’s ability after the catch, but it also is nearly as dependent on extenuating factors as the old-fashioned YPC.

TD efficiency: How many receptions a player averages before scoring a touchdown.

Fumble rate: How many touches a player averages before fumbling the ball. Only total fumbles were factored since losing the fumble is mostly chance.

Non-PPR fantasy points per touch: How many standard fantasy points are generated per rush, receive, pass and two-point conversation touches.

PPR fantasy points per touch: How many point-per-reception fantasy points are generated per rush, receive, pass and two-point conversation touches.

The threshold for inclusion is a minimum of 50 targets.

(Reinhold Matay, USA TODAY Sports)

PPR points per touch ranking

Rk
Player
Tm
Rec%
%Rk
YPR
YPR Rk
Rec/TD
Rec/TD rk
Tch/Fmb
Rk
PP/T
PP/T rk
PPR/T
1
 David Moore
SEA
49.1%
78
17.1
4
5.20
4
13.50
50
2.34
1
3.74
2
 Mike Williams
LAC
65.2%
40
15.4
11
4.30
2
N/A
0
2.21
2
3.53
3
 Kenny Stills
MIA
57.8%
61
15.0
20
6.17
7
38.00
30
2.16
4
3.45
4
 John Ross
CIN
36.2%
83
10.0
79
3.00
1
N/A
0
2.00
13
3.40
5
 Mike Evans
TAM
62.3%
47
17.7
3
10.75
31
43.00
24
2.08
6
3.39
6
 Josh Gordon
2TM
57.7%
62
18.0
2
10.25
26
N/A
0
2.18
3
3.38
7
 Marvin Jones
DET
56.5%
63
14.5
23
7.00
12
N/A
0
2.03
9
3.31
8
 A.J. Green
CIN
59.7%
57
15.1
17
7.67
14
23.00
40
1.98
15
3.27
9
 Josh Reynolds
LAR
54.7%
69
13.9
29
5.80
6
N/A
0
1.97
16
3.23
10
 DeSean Jackson
TAM
55.4%
67
18.9
1
10.25
25
N/A
0
2.12
5
3.22
11
 Tyrell Williams
LAC
63.1%
46
15.9
10
8.20
17
21.50
41
2.02
10
3.20
12
 John Brown
BAL
43.3%
81
17.0
5
8.40
19
N/A
0
2.04
7
3.20
13
 Courtland Sutton
DEN
50.0%
77
16.8
8
10.50
28
N/A
0
2.00
12
3.17
14
 T.Y. Hilton
IND
63.3%
44
16.7
9
12.67
41
N/A
0
1.99
14
3.14
15
 Tyler Lockett
SEA
81.4%
2
16.9
7
5.70
5
35.00
34
2.04
8
3.13
16
 Chris Godwin
TAM
62.1%
49
14.3
25
8.43
20
14.75
49
1.88
18
3.10
17
 Antonio Brown
PIT
61.9%
51
12.5
50
6.93
11
N/A
0
1.83
22
3.08
18
 Cooper Kupp
LAR
72.7%
9
14.2
27
6.67
10
N/A
0
1.90
17
3.07
19
 Tyreek Hill
KAN
63.5%
43
17.0
6
7.25
13
N/A
0
2.01
11
3.06
20
 Rashard Higgins
CLE
73.6%
7
14.7
22
9.75
23
19.50
42
1.84
21
3.06
21
 Robby Anderson
NYJ
53.2%
75
15.0
19
8.33
18
26.00
37
1.83
23
3.05
22
 Chris Hogan
NWE
63.6%
42
15.2
14
11.67
37
N/A
0
1.87
19
3.03
23
 Anthony Miller
CHI
61.1%
55
12.8
44
4.71
3
40.00
27
1.85
20
3.01
24
 Calvin Ridley
ATL
69.6%
22
12.8
43
6.40
8
35.00
35
1.79
27
2.97
25
 Davante Adams
GNB
65.7%
36
12.5
48
8.54
21
N/A
0
1.75
28
2.94
26
 Curtis Samuel
CAR
60.0%
56
12.7
46
7.80
15
47.00
21
1.81
24
2.93
27
 Chris Conley
KAN
61.5%
54
10.4
72
6.40
9
16.00
47
1.59
46
2.92
28
 Kenny Golladay
DET
58.8%
58
15.2
16
14.00
47
71.00
8
1.80
26
2.92
29
 Antonio Callaway
CLE
54.4%
70
13.6
35
8.60
22
45.00
22
1.75
29
2.90
30
 Michael Gallup
DAL
48.5%
80
15.4
12
16.50
60
N/A
0
1.81
25
2.87
31
 DeAndre Hopkins
HOU
70.6%
17
13.7
33
10.45
27
58.50
15
1.71
32
2.87
32
 Julio Jones
ATL
66.5%
30
14.8
21
14.13
48
57.50
17
1.73
31
2.85
33
 Alshon Jeffery
PHI
70.7%
16
13.0
40
10.83
32
65.00
12
1.69
36
2.85
34
 Doug Baldwin
SEA
68.5%
24
12.4
51
10.00
24
N/A
0
1.67
39
2.84
35
 Amari Cooper
2TM
70.1%
21
13.4
37
10.71
30
38.50
29
1.68
38
2.82
36
 Zay Jones
BUF
54.9%
68
11.6
59
8.00
16
58.00
16
1.65
41
2.80
37
 Tyler Boyd
CIN
70.4%
18
13.5
36
10.86
33
N/A
0
1.69
37
2.80
38
 Devin Funchess
CAR
55.7%
66
12.5
49
11.00
34
N/A
0
1.65
42
2.79
39
 Marquez Valdes-Scantling
GNB
52.1%
76
15.3
13
19.00
64
N/A
0
1.74
30
2.78
40
 Odell Beckham
NYG
62.1%
50
13.7
34
12.83
42
42.00
25
1.70
33
2.77
41
 Kelvin Benjamin
2TM
37.3%
82
15.2
15
25.00
71
N/A
0
1.69
35
2.76
42
 Allen Robinson
CHI
58.5%
59
13.7
32
13.75
45
56.00
18
1.63
43
2.76
43
 Donte Moncrief
JAX
53.9%
74
13.9
28
16.00
55
48.00
20
1.63
44
2.75
44
 Kendrick Bourne
SFO
63.6%
41
11.6
60
10.50
29
42.00
26
1.59
47
2.73
45
 Brandin Cooks
LAR
68.4%
26
15.1
18
16.00
53
90.00
3
1.70
34
2.70
46
 Christian Kirk
ARI
63.2%
45
13.7
30
14.33
50
N/A
0
1.65
40
2.68
47
 Demaryius Thomas
2TM
66.3%
31
11.5
63
11.80
38
N/A
0
1.53
53
2.66
48
 JuJu Smith-Schuster
PIT
66.9%
29
12.9
42
15.86
52
112.00
2
1.55
52
2.64
49
 Larry Fitzgerald
ARI
61.6%
53
10.6
70
11.50
36
N/A
0
1.52
54
2.62
50
 Emmanuel Sanders
DEN
72.4%
11
12.2
53
17.75
61
76.00
6
1.57
50
2.61
51
 Sterling Shepard
NYG
61.7%
52
13.2
38
16.50
58
69.00
10
1.58
49
2.61
52
 Adam Thielen
MIN
73.9%
5
12.2
54
12.56
40
118.00
1
1.52
55
2.59
53
 Corey Davis
TEN
58.0%
60
13.7
31
16.25
57
71.00
9
1.59
48
2.59
54
 Sammy Watkins
KAN
72.7%
10
13.0
39
13.33
44
45.00
23
1.56
51
2.56
55
 Michael Thomas
NOR
85.0%
1
11.2
64
13.89
46
62.50
14
1.43
61
2.54
56
 Robert Woods
LAR
66.2%
32
14.2
26
14.33
49
N/A
0
1.61
45
2.53
57
 Josh Doctson
WAS
56.4%
64
12.1
55
22.00
69
N/A
0
1.41
62
2.48
58
 Jarvis Landry
CLE
54.4%
71
12.1
56
20.25
66
86.00
4
1.49
56
2.47
59
 Michael Crabtree
BAL
54.0%
73
11.2
65
18.00
62
N/A
0
1.39
65
2.46
60
 Julian Edelman
NWE
68.5%
23
11.5
62
12.33
39
85.00
5
1.46
57
2.45
61
 Keenan Allen
LAC
71.3%
15
12.3
52
16.17
56
35.33
33
1.44
60
2.44
62
 Nelson Agholor
PHI
66.0%
35
11.5
61
16.00
54
68.00
11
1.40
63
2.43
63
 Adam Humphries
TAM
72.4%
12
10.7
68
15.20
51
39.00
28
1.36
67
2.42
64
 Mohamed Sanu
ATL
70.2%
20
12.7
45
16.50
59
37.50
31
1.45
59
2.41
65
 Jordy Nelson
OAK
71.6%
14
11.7
58
21.00
67
64.00
13
1.38
66
2.41
66
 Keelan Cole
JAX
54.3%
72
12.9
41
38.00
79
19.00
44
1.31
71
2.40
67
 Taywan Taylor
TEN
66.1%
33
12.6
47
37.00
77
37.00
32
1.34
69
2.39
68
 Dede Westbrook
JAX
65.3%
38
10.9
67
13.20
43
25.33
39
1.39
64
2.39
69
 Stefon Diggs
MIN
68.5%
25
10.0
78
11.33
35
N/A
0
1.34
68
2.36
70
 D.J. Moore
CAR
67.1%
28
14.3
24
27.50
73
17.00
46
1.46
58
2.35
71
 Golden Tate
2TM
65.5%
37
10.7
69
18.50
63
26.00
38
1.31
70
2.32
72
 Randall Cobb
GNB
62.3%
48
10.1
76
19.00
65
19.00
45
1.20
75
2.30
73
 Cole Beasley
DAL
74.7%
3
10.3
74
21.67
68
N/A
0
1.23
73
2.28
74
 Quincy Enunwa
NYJ
55.9%
65
11.8
57
38.00
80
19.50
43
1.23
74
2.25
75
 Seth Roberts
OAK
70.3%
19
11.0
66
22.50
70
N/A
0
1.24
72
2.23
76
 Jermaine Kearse
NYJ
48.7%
79
10.0
77
37.00
78
N/A
0
1.13
77
2.16
77
 Jarius Wright
CAR
72.9%
8
10.4
73
43.00
81
15.00
48
1.17
76
2.14
78
 Willie Snead
BAL
65.3%
39
10.5
71
62.00
83
N/A
0
1.13
78
2.13
79
 Ryan Grant
IND
67.3%
27
9.5
81
35.00
75
N/A
0
1.08
82
2.13
80
 Danny Amendola
MIA
74.7%
4
9.8
80
59.00
82
30.50
36
1.10
80
2.09
81
 Chester Rogers
IND
73.6%
6
9.2
82
26.50
72
54.00
19
1.10
79
2.09
82
 Laquon Treadwell
MIN
66.0%
34
8.6
83
35.00
76
N/A
0
1.00
83
2.03
83
 Taylor Gabriel
CHI
72.0%
13
10.3
75
33.50
74
76.00
7
1.09
81
2.01

Zero surprise here. Low-volume players generate the most points per touch. Mike Evans at No. 5 is the only player in the top 13 with more than 46 catches.

Non-PPR points per touch ranking

Comparing the ranking in non-PPR, the list shakes out almost the same … the biggest variation in the top 20 spots is John Ross falling from fourth in PPR to 13th in standard scoring. Tyreek Hill climbed eight places in PPR. Brandin Cooks went from No. 45 in PPR to 34th in non-, and Chris Conley’s 19-point fall in to 46th in standard scoring was the largest change in either direction.

(Geoff Burke, USA TODAY Sports)

Weighted grading for overall efficiency

Rk
Player
Tm
Rk
Player
Tm
1
Ryan Grant
IND
43
Tyreek Hill
KAN
2
Alshon Jeffery
PHI
44
Doug Baldwin
SEA
3
D.J. Moore
CAR
45
Jermaine Kearse
NYJ
4
Chris Godwin
TAM
46
Seth Roberts
OAK
5
Josh Gordon
2TM
47
Amari Cooper
2TM
6
Julian Edelman
NWE
48
Tyrell Williams
LAC
7
Allen Robinson
CHI
49
Keenan Allen
LAC
8
Marvin Jones
DET
50
Kenny Golladay
DET
9
Demaryius Thomas
2TM
51
Mike Evans
TAM
10
Kendrick Bourne
SFO
52
JuJu Smith-Schuster
PIT
11
Josh Doctson
WAS
53
DeAndre Hopkins
HOU
12
Nelson Agholor
PHI
54
Michael Thomas
NOR
13
Adam Thielen
MIN
55
Jordy Nelson
OAK
14
Golden Tate
2TM
56
Larry Fitzgerald
ARI
15
Kelvin Benjamin
2TM
57
David Moore
SEA
16
Robby Anderson
NYJ
58
Adam Humphries
TAM
17
Randall Cobb
GNB
59
Taywan Taylor
TEN
18
Sterling Shepard
NYG
60
Chris Conley
KAN
19
Mike Williams
LAC
61
Curtis Samuel
CAR
20
Josh Reynolds
LAR
62
Marquez Valdes-Scantling
GNB
21
A.J. Green
CIN
63
Cooper Kupp
LAR
22
Laquon Treadwell
MIN
64
Antonio Brown
PIT
23
Quincy Enunwa
NYJ
65
Christian Kirk
ARI
24
Rashard Higgins
CLE
66
Jarvis Landry
CLE
25
Chester Rogers
IND
67
Tyler Boyd
CIN
26
Dede Westbrook
JAX
68
Odell Beckham
NYG
27
DeSean Jackson
TAM
69
Donte Moncrief
JAX
28
Devin Funchess
CAR
70
Sammy Watkins
KAN
29
Calvin Ridley
ATL
71
Tyler Lockett
SEA
30
Zay Jones
BUF
72
Robert Woods
LAR
31
Corey Davis
TEN
73
Keelan Cole
JAX
32
Courtland Sutton
DEN
74
Taylor Gabriel
CHI
33
Mohamed Sanu
ATL
75
Chris Hogan
NWE
34
Julio Jones
ATL
76
John Ross
CIN
35
Michael Gallup
DAL
77
Emmanuel Sanders
DEN
36
Jarius Wright
CAR
78
Kenny Stills
MIA
37
Antonio Callaway
CLE
79
Michael Crabtree
BAL
38
Willie Snead
BAL
80
Davante Adams
GNB
39
Danny Amendola
MIA
81
Cole Beasley
DAL
40
Brandin Cooks
LAR
82
Stefon Diggs
MIN
41
John Brown
BAL
83
T.Y. Hilton
IND
42
Anthony Miller
CHI

In this model, players were graded on their ranking relative to their peers in the six chosen categories. The weighting is always going to be subjective in a situation like this one, so after some tinkering, this is how it bore out:

TD efficiency: 50 percent of the grade
Reception percentage: 15%
YPR: 15%
Fumble rate: 5%
Non-PPR/touch: 7.5%
PPR/touch: 7.5%

It’s not perfect, but touchdown efficiency always should have the most weight in a situation of this nature. Reception percentage arguably could be higher at the expense of yards per reception (have to catch the ball to do something with it), but this balances well and doesn’t favor a PPR hog with a high rate or a low-catch, big-play type. After all, balanced rankings is the aim … it does more good for more people that way.

The composite score produced the table above. Ryan Grant atop the list can be considered the outlier, but familiar names otherwise adorn the top 10.

(Kim Klement, USA TODAY Sports)

Composite scoring without weighting

This table generically shows where each player falls in an aggregate scoring of their categorical finish without weighting applied. In other words, a first-place ranking is just as valuable in touchdowns as reception percentage, which ultimately is a reflection of which players are more evenly efficient.

Composite Rk
 Player
Tm
Rec%
YPR%
TD%
Fum%
PP/T%
PPR/T%
Non-PPR Rk
PPR Rk
1
 Tyler Lockett
SEA
2
7
5
8
15
34
1
2
2
 Mike Williams
LAC
40
11
2
2
2
0
2
1
3
 Cooper Kupp
LAR
9
27
10
17
18
0
3
3
4
 David Moore
SEA
78
4
4
1
1
50
4
24
5
 Tyreek Hill
KAN
43
6
13
11
19
0
5
4
6
 Josh Gordon
2TM
62
2
26
3
6
0
10
5
7
 Rashard Higgins
CLE
7
22
23
21
20
42
7
12
8
 Tyrell Williams
LAC
46
10
17
10
11
41
8
15
9
 DeSean Jackson
TAM
67
1
25
5
10
0
11
6
10
 Marvin Jones
DET
63
23
12
9
7
0
13
7
11
 Kenny Stills
MIA
61
20
7
4
3
30
9
14
12
 Mike Evans
TAM
47
3
31
6
5
24
6
9
13
 T.Y. Hilton
IND
44
9
41
14
14
0
14
8
14
 A.J. Green
CIN
57
17
14
15
8
40
12
26
15
 John Brown
BAL
81
5
19
7
12
0
15
10
16
 Josh Reynolds
LAR
69
29
6
16
9
0
18
13
17
 Chris Godwin
TAM
49
25
20
18
16
49
17
33
18
 Chris Hogan
NWE
42
14
37
19
22
0
19
11
19
 Courtland Sutton
DEN
77
8
28
12
13
0
20
18
20
 Calvin Ridley
ATL
22
43
8
27
24
35
16
22
21
 Antonio Brown
PIT
51
50
11
22
17
0
23
20
22
 Davante Adams
GNB
36
48
21
28
25
0
26
19
23
 Tyler Boyd
CIN
18
36
33
37
37
0
27
17
24
 Anthony Miller
CHI
55
44
3
20
23
27
22
28
25
 Robby Anderson
NYJ
75
19
18
23
21
37
24
37
26
 Doug Baldwin
SEA
24
51
24
39
34
0
31
25
27
 DeAndre Hopkins
HOU
17
33
27
32
31
15
21
16
28
 John Ross
CIN
83
79
1
13
4
0
34
38
29
 Amari Cooper
2TM
21
37
30
38
35
29
28
30
30
 Alshon Jeffery
PHI
16
40
32
36
33
12
25
23
31
 Julio Jones
ATL
30
21
48
31
32
17
29
27
32
 Curtis Samuel
CAR
56
46
15
24
26
21
30
34
33
 Michael Gallup
DAL
80
12
60
25
30
0
39
39
34
 Robert Woods
LAR
32
26
49
45
56
0
40
29
35
 Christian Kirk
ARI
45
30
50
40
46
0
42
35
36
 Chris Conley
KAN
54
72
9
46
27
47
41
65
37
 Antonio Callaway
CLE
70
35
22
29
29
22
35
41
38
 Kenny Golladay
DET
58
16
47
26
28
8
32
31
39
 Marquez Valdes-Scantling
GNB
76
13
64
30
39
0
46
43
40
 Brandin Cooks
LAR
26
18
53
34
45
3
33
21
41
 Odell Beckham
NYG
50
34
42
33
40
25
37
44
42
 Sammy Watkins
KAN
10
39
44
51
54
23
36
36
43
 Devin Funchess
CAR
66
49
34
42
38
0
50
48
44
 Demaryius Thomas
2TM
31
63
38
53
47
0
51
45
45
 Kelvin Benjamin
2TM
82
15
71
35
41
0
53
52
46
 Kendrick Bourne
SFO
41
60
29
47
44
26
45
51
47
 Allen Robinson
CHI
59
32
45
43
42
18
44
49
48
 Zay Jones
BUF
68
59
16
41
36
16
43
50
49
 Adam Thielen
MIN
5
54
40
55
52
1
38
32
50
 D.J. Moore
CAR
28
24
73
58
70
46
59
66
51
 Larry Fitzgerald
ARI
53
70
36
54
49
0
61
56
52
 Keenan Allen
LAC
15
52
56
60
61
33
55
58
53
 Michael Thomas
NOR
1
64
46
61
55
14
49
46
54
 Mohamed Sanu
ATL
20
45
59
59
64
31
56
57
55
 Emmanuel Sanders
DEN
11
53
61
50
50
6
48
42
56
 JuJu Smith-Schuster
PIT
29
42
52
52
48
2
47
40
57
 Stefon Diggs
MIN
25
78
35
68
69
0
63
54
58
 Donte Moncrief
JAX
74
28
55
44
43
20
54
61
59
 Adam Humphries
TAM
12
68
51
67
63
28
60
63
60
 Julian Edelman
NWE
23
62
39
57
60
5
52
47
61
 Sterling Shepard
NYG
52
38
58
49
51
10
57
55
62
 Cole Beasley
DAL
3
74
68
73
73
0
66
60
63
 Corey Davis
TEN
60
31
57
48
53
9
58
53
64
 Dede Westbrook
JAX
38
67
43
64
68
39
65
69
65
 Seth Roberts
OAK
19
66
70
72
75
0
68
64
66
 Josh Doctson
WAS
64
55
69
62
57
0
69
67
67
 Jordy Nelson
OAK
14
58
67
66
65
13
62
59
68
 Taywan Taylor
TEN
33
47
77
69
67
32
67
71
69
 Nelson Agholor
PHI
35
61
54
63
62
11
64
62
70
 Jarius Wright
CAR
8
73
81
76
77
48
72
79
71
 Golden Tate
2TM
37
69
63
70
71
38
71
77
72
 Michael Crabtree
BAL
73
65
62
65
59
0
74
73
73
 Keelan Cole
JAX
72
41
79
71
66
44
77
80
74
 Danny Amendola
MIA
4
80
82
80
80
36
76
78
75
 Randall Cobb
GNB
48
76
65
75
72
45
78
81
76
 Ryan Grant
IND
27
81
75
82
79
0
79
74
77
 Willie Snead
BAL
39
71
83
78
78
0
80
75
78
 Chester Rogers
IND
6
82
72
79
81
19
73
72
79
 Jarvis Landry
CLE
71
56
66
56
58
4
70
70
80
 Laquon Treadwell
MIN
34
83
76
83
82
0
82
76
81
 Quincy Enunwa
NYJ
65
57
80
74
74
43
81
83
82
 Taylor Gabriel
CHI
13
75
74
81
83
7
75
68
83
 Jermaine Kearse
NYJ
79
77
78
77
76
0
83
82

The two farthest right columns show a composite ranking for just PPR and just non-PPR scoring systems. As seen in the earlier tables, there just isn’t a great deal of variation. Efficient is efficient, regardless of the scoring system. Low-volume players are generally deep-ball receivers, which naturally generates more efficiency once the ball is caught. Efficiency per opportunity typically sides with PPR favorites.

Takeaways for 2019

Efficiency should be only part of the puzzle, much like other obscure calculations advice-givers tend to toss out there. Highly efficient players, such as Seattle Seahawks wide receiver David Moore, aren’t necessarily consistent players, and it’s extremely important for this to be recognized.

When do you play a guy like Moore? Efficiency tends to be most helpful in situations where gamers are trying to get lucky in a tough situation — bye weeks, huge GPP contests in DFS where lineup variation is extremely important, etc., but doesn’t help as much as it seems like it should in conventional situations.

Does it make as much of an impact if a lineup fixture is dominant and efficient? Not in a relative sense compared to a part-time player when you’re trying to get the most bang for your buck. About the only real gain from a stud player being efficient is being able to overcome a poor showing by the offense.

A final side note of interest: The average age of the top 25 players in composite efficiency is 26 years old — right in the prime of a career. The average age of the bottom 25?  Yep, 26. Guess the average age of all 83 receivers … You got it.

Join next time for an examination of how consistent the most efficient wide receivers were in 2018 to see if there’s any crossover.

, , Fantasy football statistical analysis

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