The Running Back Value Index: Part One

Eric Hardter

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Since January, DLF’s own Ryan McDowell has been coordinating monthly mock drafts and subsequently analyzing the results.  The resulting ADP data has been an invaluable asset, essentially serving as a mainline to the pulse of the dynasty community.  Startup drafters are provided with a rough estimate of where to target certain players, and trade partners now have a better sense of relative values.

Over the course of these successive drafts, the running back position has seen its share of ups and downs.  Roster cuts and free agent signings have affected the fates of multiple players and the NFL Draft looms large as yet another harbinger of upheaval.  Metaphorical stocks rise and fall and values fluctuate like the changing of the tides.

When it comes to such a transiently natured position, though, what is the true definition of the word value?  Yes, the ADP data reflects how we currently view this crop of ball carriers, but that type of beauty is merely in the eyes of the drafting beholders.  Will the returns upon investment be commensurate with the price?

I’ve taken it upon myself to answer that exact question.  After refining the methodology and scrutinizing the data, I’ve created the Running Back Value Index.  This Index serves as a predictor for which particular NFL running backs (note: no 2013 rookies are included in this study) could potentially offer the most dynasty value, based on select criteria.  In part one, I’ll cover the science behind the process as well as release the Index itself.  In part two (tomorrow), I’ll compare the results to the ADP data, highlighting players whose values differ dramatically.

The study utilized four main criteria, which are listed below:

1.) Age

Compared to other positions, running backs begin to decline at a relatively young age.  With an average 2012 rookie age of 22.9, a running back’s shelf life is quite pronounced indeed.  “Dynasty Doctor” Scott Peak adds the following:

Medical literature supports evidence that athletic ability declines with age. One article reviewed athletic ability as a function of age, and noted a performance peak at age 26 for track and field and age 21 for swimmers (1). There are data to suggest athletes have a reduction in the size of fast muscle fibers, replaced by slower muscle fibers, and this plays a role in the decline of explosive force production with age (2).  In this article, 60-meter sprint times, vertical jump and isometric force all declined with advancing age (2). Muscle mass also declines with age, likely due in part to a reduction in growth hormone production as time passes. Master swimmers have been shown to have a decrease in performance with age due to a drop in metabolic power and increase in energy expenditure (3).  Running speed has been shown to decline with age, especially for endurance events, and metabolic power in running uniformly declines with age (4), as well as a decline in jump power (5). Ample evidence suggests a physiological and neuromuscular basis for decline in athletic performance over time.

2.) Workload

Similar to the above, ball carriers tend to regress statistically as their cumulative usage increases.  As such, this study takes into account total touches, including rushes and receptions in both the regular season and the playoffs.

3.)  Percentage of Fantasy Points from Touchdowns

Call it the “fluke factor,” if you will.  As scoring touchdowns can be unpredictable (just ask LeSean McCoy), it’s important to know how well each running back performs if/when they’re held out of the end zone.  The touchdowns in question are of both the rushing and receiving variety.

4.) Average Fantasy Finish

In order to predict the future, sometimes we must delve back into the past.  The totality of each running back’s fantasy career was accounted for (note: standard PPR scoring was used), affording the averaged data.

Each of these four categories was scored on a scale from 1 – 10, with ten being the best possible.  This scoring system is detailed in the table below:

Age

Score

Touches

Score

% From TD’s

Score

Average PPR Finish

Score

22

10

0 – 250

10

0 – 10.0

10

1.0 – 6.0

10

23

9

251 – 500

9

10.1 – 13.0

9

6.1 – 12.0

9

24

8

501 – 750

8

13.1 – 16.0

8

12.1 – 18.0

8

25

7

751 – 1000

7

16.1 – 19.0

7

18.1 – 24.0

7

26

6

1001 – 1250

6

19.1 – 22.0

6

24.1 – 30.0

6

27

5

1251 – 1500

5

22.1 – 25.0

5

30.1 – 36.0

5

28

4

1501 – 1750

4

25.1 – 28.0

4

36.1 – 42.0

4

29

3

1751 – 2000

3

28.1 – 31.0

3

42.1 – 48.0

3

30

2

2001 – 2250

2

31.1 – 34.0

2

48.1 – 54.0

2

> 30

1

> 2250

1

> 34.0

1

> 54.1

1

In order to account for each player’s fantasy longevity, a fifth parameter was also utilized.  For example, over the course of his six-year career, Adrian Peterson sports an average fantasy finish as the PPR RB6.2.  This average is lower than that of Doug Martin, who finished as the PPR RB2 in 2012, his only year in the NFL.

In order to account for discrepancies in consistency, as well as prevent against one-year wonders (ex. Steve Slaton), each player’s average PPR finish (the fourth criterion above) was “multiplied” proportionate to the amount of years considered.  This is summarized in the following table:

Years Considered

Multiplier

1

0.33

2 – 4

0.67

> 5

1.00

Again, the main principle in effect is that dependability should be rewarded.  Players with only one year considered have the lowest multiplier (0.33) to safeguard against statistical aberrations.  Running backs with two-to-four years of production have proven to be “trend-worthy,” and benefit from a larger multiplier (0.67).  Ball carriers with five or more years of fantasy prowess are rewarded with an equivalent multiplier of 1.0, so that their scores directly mirror that of their average PPR finish.  The amount of seasons considered is noted in the “years” column, with subsequent scores adjacent.

Therefore, between the five categories of ten points apiece, a maximum total of 50 points can be attained.  The larger the total, the better dynasty “value” a player offers.  With that in mind, there are just a few more notes before I reveal the Index:

1.) Each player’s age as of the 2013 season opener was utilized.

2.) Only running backs in the top 200 of the March ADP were considered.

3.) If a year (or years) wasn’t (weren’t) used for this study, it is noted in the far right column. Examples of this are serious injury (ex. Jamaal Charles in 2011), divergent rookie usage (ex. Ray Rice only receiving 107 carries as a rookie), and dramatic scheme shift (ex. Darren Sproles’ usage upon switching from the Chargers to the Saints).  I attempted to be as “objectively subjective” as possible.

4.) Due to a lack of evidence, only players with over 75 career PPR fantasy points were considered for the “touchdown percentage” category.  Players failing to achieve that status are denoted with an “N/A,” and received the average score of 5.4 for that category.

5.) Finally, and most importantly, this is NOT a rankings list!  This is not the order I would select players in a startup draft, and neither should you.  This is merely an unbiased culmination of the combinatory data and suggestive indicator of potential upside and relative value that does NOT take situation into account.

Without further adieu, the Index is presented below.  Be sure to check out the ADP comparisons and explanations in part two tomorrow.

Rank

Name

Age

Score

Career Touches

Score

% TD Points

Score

Avg.  Finish

Score

Years

Score

Total

Notes

1

CJ Spiller

26

6

494

9

18.2

7

17.5

8

2

5.4

35.4

Ignore Rookie

2

D. Martin

24

8

368

9

23

5

2

10

1

3.3

35.3

T-3

J. Charles

26

6

946

7

16.4

7

8

9

3

6

35

Ignore Rookie/Injury 2011

T-3

D. Murray

25

7

386

9

12.2

9

28

6

2

4

35

T-3

J. Rodgers

23

9

251

9

11.2

9

29

6

1

2

35

Ignore Rookie

6

R. Mathews

25

7

675

8

15.9

8

23

7

3

4.7

34.7

T-7

T. Richardson

22

10

318

9

28.3

3

8

9

1

3

34

T-7

M. Forte

27

5

1584

4

16.9

7

8.8

9

5

9

34

9

J. Bell

27

5

134

10

11.3

9

23

7

1

2.3

33.3

T-10

L. McCoy

25

7

1077

6

23

5

7

9

3

6

33

Ignore Rookie

T-10

C. Johnson

27

5

1705

4

21

6

7.8

9

5

9

33

T-10

D. Richardson

23

9

122

10

0

10

46

3

1

1

33

T-13

R. Rice

26

6

1755

3

17.1

7

3.8

10

4

6.7

32.7

Ignore Rookie

T-13

V. Ballard

23

9

251

9

13.7

8

33

5

1

1.7

32.7

15

M. Leshoure

23

9

249

10

28.5

3

18

8

1

2.6

32.6

Injury 2011

16

J. Dwyer

24

8

200

10

10.1

9

40

4

1

1.3

32.3

Ignore 2010/2011

17

A. Morris

24

8

362

9

30.3

3

7

9

1

3

32

18

R. Bush

28

4

1402

5

19.9

6

17.5

8

6

8

31

Injury 2010

T-19

A. Foster

27

5

1305

5

27.9

4

2.3

10

3

6.7

30.7

Ignore Rookie

T-19

K. Moreno

26

6

713

8

23.7

5

24

7

3

4.7

30.7

Injury 2011

21

S. Ridley

24

8

425

9

29.5

3

15

8

1

2.6

30.6

Ignore Rookie

T-22

B. Brown

22

10

128

10

24.2

5

42

4

1

1.3

30.3

T-22

B. Pierce

23

9

155

10

8.5

10

58

1

1

0.3

30.3

24

D. Sproles

30

2

779

7

20.6

6

9

9

2

6

30

Exclude Chargers Years

25

B. Tate

25

7

275

9

18.3

7

31

5

1

1.7

29.7

Injury 2012

26

R. Mendenhall

26

6

1006

6

27.2

4

16.3

8

3

5.4

29.4

Ignore Rookie/Injury 2012

27

M. Jones-Drew

28

4

1883

3

25.8

4

7.2

9

6

9

29

Injury 2012

28

D. McFadden

26

6

927

7

17.8

7

32.2

5

4

3.4

28.4

T-29

M. Lynch

27

5

1681

4

24.6

5

19.3

7

6

7

28

T-29

J. Stewart

26

6

922

7

24.7

5

27.3

6

4

4

28

Exclude 2012

T-29

S. Jackson

30

2

2824

1

18

7

10.9

9

8

9

28

Ignore Rookie

32

A. Bradshaw

27

5

1184

6

24

5

20

7

4

4.7

27.7

Ignore 2007/2008

33

D. Thomas

25

7

283

9

14.1

8

49

2

2

1.3

27.3

T-34

A. Peterson

28

4

2028

2

28.3

3

6.2

9

6

9

27

T-34

F. Gore

30

2

2333

1

20

6

10.6

9

7

9

27

Ignore 2005

T-34

B. Powell

24

8

141

10

23.4

5

43

3

1

1

27

Ignore Rookie

T-34

S. Greene

28

4

987

7

19.2

6

27.3

6

3

4

27

Ignore Rookie

T-38

L. Miller

22

10

57

10

N/A

5.4

82

1

1

0.3

26.7

T-38

R. Hillman

22

10

120

10

N/A

5.4

66

1

1

0.3

26.7

T-38

F. Jackson

32

1

1141

6

15.2

8

21.5

7

4

4.7

26.7

Ignore Rookie/Injury 2012

41

K. Hunter

25

7

220

10

22.7

5

44

3

1

1

26

Injury 2012

T-42

R. Williams

23

9

65

10

N/A

5.4

99

1

1

0.3

25.7

Injury 2011

T-42

R. Turbin

23

9

114

10

N/A

5.4

55

1

1

0.3

25.7

T-42

I. Pead

23

9

13

10

N/A

5.4

125

1

1

0.3

25.7

T-42

L. James

23

9

43

10

N/A

5.4

114

1

1

0.3

25.7

T-46

M. Ingram

23

9

295

9

31.2

2

43

3

2

2

25

T-46

De. Williams

30

2

1329

5

25.7

4

23.8

7

6

7

25

Injury 2010

48

C. Ivory

25

7

281

9

26

4

47

3

1

1

24

Injury/Inactive 2011/2012

T-49

D. Wilson

22

10

75

10

41

1

54

2

1

0.7

23.7

T-49

B. Green-Ellis

28

4

901

7

34.2

1

23

7

3

4.7

23.7

Ignore 2008/2009

T-49

B. Wells

25

7

672

8

32.1

2

41

4

3

2.7

23.7

Injury 2012

T-49

D. Harris

25

7

81

10

N/A

5.4

112

1

1

0.3

23.7

No Full Season Data

T-53

A. Brown

26

6

87

10

44.9

1

39

4

1

1.3

22.3

Ignore 2010/Injury 2011

T-53

S. Vereen

24

8

103

10

28.7

3

57

1

1

0.3

22.3

Injury 2011

55

W. McGahee

31

1

2280

1

26.3

4

21.7

7

7

7

20

Ignore 2009/2010

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References

  1. Berthelot G, Len S, Hellard P, et al. Exponential growth combined with exponential decline explains lifetime performance evolution in individual and human species. Age; August 2012, volume 34, Issue 4, pp 1001-1009.
  2. Korhonen MT, Cristea A, Alen M, et al. Aging, muscle fiber type, and contractile function in sprint-trained athletes. J Appl Physiol 2006;101:pp 906-917.
  3. Zamparo P, Gatta G and di Prampero P. The determinants of performance in master swimmers: an analysis of master world records. Eur J Appl Physiolo. 2012 Oct;112(10):3511-8.
  4. Rittweger J, Prampero PE, Maffulli N, et al. Sprint and endurance power and ageing: an analysis of master athletic world records. Proc Biol Sci. 2009 February 22;276(1657):683-689.
  5. Michaelis I, Kwiet A, Gast U, et al. Decline of specific peak jumping power with age in master runners. J Musculoskelet Neuronal Interact. 2008 Jan-Mar;8(1):64-70.
eric hardter