### Running Back Overuse

by 'DeltaWhiskey'

INTRODUCTION

The following explores the notion that running backs are subject to "wear and tear." Football Outsiders has popularized and continues to promulgate the notion that carrying the ball over 370 times a season places a running back at "greater risk for significant decline or injury the next season." A full explanation of the "Curse of 370" can be found here. Brian Burke, at Advanced NFL Stats, has suggested the "Curse" is more of a "Myth," noting that the Football Outsiders made several statistical errors in developing the theory and that regression to the mean better explains "The Curse." Mr. Burke's critique can be found here.

The following further examines the validity of the "Curse of 370" and the

possibility that "overuse" of running backs may be a real phenomenon that

results in a performance decline.

METHODOLOGY

The primary sources of data for this study were Pro-Football-Reference.com's

list of "Single-Season Rushing Attempts Leaders." This list contains the Top 250 single-season records for attempts. When accessed for this study, the number of attempts ranged 286 to 416, with a mean of 326 and SD of 30. To test the potential effects of overuse theory, two groups were identified; Group 1 consisted of players who were one or more SD above the mean (356 or more carries). Group 1 was compared to Group 2, which consisted of running backs who were more than one SD below the mean (295 carries). This break conveniently resulted in two groups with 43 members each. It should be noted that several running backs' data were discarded because they: a.) didn't play the following year (e.g. Ricky Williams) or made the list in 2008 (e.g. Michael Turner). Also, Quarterbacks that made the list, were discarded.

For each RB, the data from individual player "cards" at Pro-Football-Reference.com was utilized. Data was gathered for the relevant season (i.e. the year they rushed either 356 or more carries, or less than 295 carries = "Year") and the following season ("Year+1"). This design allowed for testing of the hypotheses via Repeated Measures 2x2 factorial designs.

Two sets of statistical analyses were conducted. The first looked at the issue of overuse utilizing readily available standard measures of running back performance utilizing data from the above described data source. The second set of analyses, utilized Football Outsiders measures to assess

running back. This second analysis required creating a subset of data from the first because Football Outsider's data extends only back to the 1995 season. Therefore, all running back performances prior to 1995 were discarded from these analyses (sorry Jim Brown fans). This conveniently left two groups of 20 each after one of Jamaal Anderson's season was

discarded because he did not have enough carries in Year+1 to generate Football Outsider statistics. Football Outsider data for each RB was "Year"

and "Year+1" included the following measures: individual DVOA and DYAR.

DATA ANALYSIS

Standard Statistics

# CARRIES: The first analyses simply addressed whether or not the two

groups being analyzed differed in the number of carries.

Group Means

Group Year Mean Year+1 Mean

One 377.16 282

Two 290.18 240.74

Note that the average number of carries for Group 1 is actually greater than

370.

ANOVA results yielded the following

Between subjects F =39.63, df (1,84), 0.0001

Within subjects F=46.28, df (1,84), 0.0001

AxB F=4.63, df(1,84), 0.05

These results indicate that in terms of number of carries, there is a statistical difference between the Groups, between years and a year by group interaction. These results suggest that not only is there a difference from "Year" to "Year +1," but that the magnitude of the decrease is significantly different between the groups.

# of GAMES: A central component of "The Curse" proposes that more carries (specifically greater than 370) will result in a decline in the number of games a running back will play the following year (Year+1). The following analysis compared the two groups' number of games played in Year and Year +1.

Group Year Mean Year+1 Mean

One 15.674 13.534

Two 14.953 13.116

ANOVA results yielded the following

Between subjects F =1.95, df (1,84), p <ns.

Within subjects F=27.99, df (1,84), p<0.0001

AxB F=, df(1,84), p<ns.

These results indicate that high use, whether above or below 370 carries results in a decline. This is most consistent with Mr. Burke's findings. There is no statistical difference between the groups, nor is the magnitude of decline between the groups different. If a "Curse" exists, the bar is much lower than 370.

Y/A: Next, yards per attempt were assessed. Yards per attempt provide an indicator of a RB's effectiveness on a carry per carry basis.

Group Year Mean Year+1 Mean

One 4.3419 4.086

Two 4.3163 4.093

As pointless as it seems, here are the results of the analysis.

Between subjects F =0 df (1,84).

Within subjects F=10.74, df (1,84),0.01

AxB F=0.04, df(1,84),

In sum, a running back that carries a lot, on average, will experience a decline the following year - again, there is nothing magic about 370.

"DVOA Era Statistics"

Perhaps the measures utilized above are simply too crude to properly detect the effects of "370." To address this possibility, similar analyses were conducted utilizing Football Outsiders stats. First a series of analyses utilizing "Standard Statistics" were conducted to ensure that the sub-groups being analyzed were relatively the same as the original groups.

Standard Statistics

#Carries:Group Year Mean Year+1 Mean

One 375.5 291.4

Two 291.65 242.7

ANOVA results yielded the following

Between subjects F =19.83, df (1,38), p <0.0001

Within subjects F=17.11, df (1,38), p<0.001

AxB F=, df(1,38), p<ns.

These results suggest the groups are different in the number of carries. The nonsignificance of the interaction effect is the only difference and suggests that the previously detected difference may be due to a larger sample size.

#Games

Group Year Mean Year+1 Mean

One 15.5 13.85

Two 15.4 14.2

ANOVA results yielded the following

Between subjects F =.04, df (1,38).

Within subjects F=6.89, df (1,38), 0.01

AxB F=.17, df(1,38), p<ns.

These results are similar to those found above.

Y/A (Yards/Attempt)

Group Year Mean Year+1 Mean

One 4.355 3.94

Two 4.165 3.89

ANOVA results yielded the following

Between subjects F =.52, df (1,38),.

Within subjects F=11.33, df (1,38), p<0.01

AxB F=0.48, df(1,38), p<ns.

Results are again similar to above. These results then suggest that the sub-group of players, post 1995, are statistically, fairly similar to the group as a whole.

DVOA Statistics

To test validity of Football Outsider's "Curse of 370," it seems appropriate to utilize some of Football Outsider metrics. For an explanation of these metrics - http://www.footballoutsiders.com/info/methods.

Individual DVOA: This analysis tests the difference in DVOA between running backs in Group 1 and Group 2 based on Year and Year+1. DVOA is usually expressed as percent, in the following, it is expressed in decimal fashion.

Group Year Mean Year+1 Mean

One 0.0755 -0.026

Two -0.000 -0.062

ANOVA results yielded the following

Between subjects F =6, df (38,1), p <.05.

Within subjects F=13, df (38,1), p<0.001

AxB F=1.0, df(38,1), p<ns

These results suggest that there is a difference in Year and Year+1 (wear and tear or regression) and a difference between Group 1 and Group 2; however, the ns interaction effect indicates that the magnitude of the wear and tear is nonsignificant between groups. That is, the 0.1015 drop between Year and Year+1 observed in Group 1 is not significantly greater in magnitude than the approximately 0.062 drop observed in Group 2.

DYAR

Group Year Mean Year+1 Mean

One 260.1 93.05

Two 105.95 55.45

ANOVA results yielded the following

Between subjects F =7.06, df (38,1), p <.01.

Within subjects F=10.46, df (38,1), p<0.01

AxB F=3, df(38,1), p<ns

These results are similar to those for DVOA.

DISCUSSION

This study analyzed "the Curse of 370" by comparing two groups comprised of RBs who accumulated enough carries to be ranked in the top 250 single-season attempts list. The first group consisted of 43 running backs that were at least one SD above the mean in number of carries. The second group consisted of 43 running backs who were one SD below the mean. This process yielded two groups that had a high likelihood of being significantly different regarding the number of carries in a season, and if a high-number of carries is the cause for decline in subsequent seasons, then there should be significant detectable differences in the magnitude of decline. None of the results suggested this to be the case. Simply stated, this study did not detect any evidence to support "the Curse of 370." The study did find that a large number of carries are associated with decline the following year; however, that decline does not become magnified as the number of carries increases - at least not in this data set.

Mr. Burke has asserted that the decline is probably due to regression to the mean; however, further analyses utilizing this data set suggest other factors may be associated with the decline and will be examined in future posts.

## 2 comments:

Phew. Very data intensive. they don't call it 'advanced nfl stats' for nothing.

My theory on the decline is not necessarily a regression to the mean, but common personnel changes at a club. Most coaches like to have 2 good quality RBs in order to give the main guy a break. Even LT gave way to Michael Turner for a number of carries in his record breaking season.

It is therefore quite rare for a coach to let his star take all those carries and would likely only happen if the backup RB broke down and the coach didn't have confidence in the 3rd guy. By the time the next season rolls around, the coach has got the 3rd guy up to speed and the backup is fit again - meaning that the star RB doesn't need to take as many carries.

i.e. he does regress to the mean, but there is a physical reason for it rather than a purely statistical one.

Question about the sampling method:

A running back had 356+ carries in year Y and less than 290 in Y+1. Years Y and Y+1 will show up in Group 1, but would Y+1 and Y+2 be in Group 2 as well?

A thought stemming from that question: Maybe it's not one year of overuse but multiple years of overuse that kills a RB. Is there some threshold for the number of carries over 2 or 3 years that will cause a total break down the following year?

For example, James Wilder had 407 carries in 1984 for the Bucs. In 1985, he had 365 carries. His yards per carry and yards per reception were down a little, but he still started all 16 games. He never has more than 200 carries or starts for more than 12 games in a season afterwards. Of course, that may be because he was never very good to begin with.

Larry Johnson, who was a good running back, broke down after 752 carries in 2 seasons.

Michael Turner, on the other hand, just went through his first season as a feature back. He may not break down until 2010. He'll regress to the mean just because of opponent strength, but his knees may not burst into flames like Johnson's.

Michael Turner, on the other hand,

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