Advice

Who Led the League in Rushing Efficiency in 2016?

A few weeks ago I looked at 2016’s most efficient pass catchers, both from a raw perspective, as well as from a depth-adjusted perspective. Now it’s time to dive into the ball carriers that led the league in rushing efficiency. First I’ll just start with raw production, and in a follow-up article, I’ll look at a special kind of adjustment to provide further insight into the most efficient backs.

Methodology

Like yards per target over expectation (YPTOE), I fit a model to regress carries, TDs, and field position against rushing fantasy points over expectation (reFPOE), which is a metric showing how many fantasy points a player scored above or below expected based on the down, distance, and field position for each play. This regression allows us to remove TDs and field position from the fantasy points equation, to get an expectation for yards gained, and then attempt-adjust this number to get yards per carry over expected (YPCOE).

There are some things you’ll notice that pop out when we do this, and I’ll explain some other adjustments I’ve made in the next article. Let’s take a look at YPCOE for 2016.

2016 Rushing Efficiency Results

I grabbed the z-scores for both ruTDRT1 and YPCOE and summed them up (Sum.Z) in order to identify which players were the most efficient in a combination of both metrics. Here are the results for all players with at least 80 carries (16 games multiplied by five carries per game).

PLAYERruATTSruTDSruTDRTruFPOEYPCOEYPCOE.ZruTD.ZSum.Z
Mike Gillislee10187.9%39.81.972.662.164.82
Tyrod Taylor9566.3%27.51.662.231.593.83
Cam Newton9055.6%12.50.831.091.292.38
LeSean McCoy234135.6%66.30.550.701.291.99
DeAndre Washington8622.3%151.592.14-0.401.73
Isaiah Crowell19773.6%18.70.941.240.341.58
Devonta Freeman227114.8%18.60.430.540.981.52
Ryan Mathews15585.2%-0.30.180.191.121.32
Mark Ingram20562.9%21.40.941.24-0.021.22
Ezekiel Elliott321154.7%740.260.300.901.21
Jordan Howard25162.4%28.71.161.54-0.361.18
Christine Michael14874.7%16.30.190.200.931.14
Rob Kelley16863.6%10.70.550.700.351.05
David Johnson293165.5%25.4-0.12-0.221.251.03
Jalen Richard8411.2%14.31.692.27-1.261.02
Tevin Coleman11886.8%31.6-0.53-0.791.770.98
Latavius Murray195126.2%17.2-0.4-0.611.530.92
Bilal Powell13132.3%140.861.13-0.430.70
Derrick Henry11054.5%14-0.14-0.250.840.59
Tim Hightower13343.0%-10.10.410.510.030.54
C.J. Anderson11043.6%-4.40.150.150.390.54
Jay Ajayi26083.1%30.70.340.410.070.48
Le'Veon Bell26172.7%26.90.410.51-0.170.34
LeGarrette Blount299186.0%5.6-0.81-1.171.480.31
Melvin Gordon254103.9%-6-0.14-0.250.540.29
Matt Asiata12165.0%-28.2-0.55-0.821.040.22
Matt Jones9933.0%6.50.140.140.040.18
DeMarco Murray29393.1%7.60.070.040.070.11
Jeremy Hill22294.1%-5.2-0.37-0.570.600.04
Darren Sproles9422.1%2.90.450.56-0.540.03
Jonathan Stewart21894.1%-6.1-0.47-0.710.64-0.06
Carlos Hyde21762.8%12.90.070.04-0.12-0.08
DeAngelo Williams9844.1%7.4-0.47-0.710.62-0.09
Chris Ivory11732.6%-110.140.14-0.25-0.11
Kenneth Dixon8822.3%2.40.150.15-0.44-0.29
Zach Zenner8844.5%-0.3-0.8-1.160.84-0.32
Jacquizz Rodgers12921.6%-10.50.63-0.96-0.33
Matt Forte21873.2%-5.4-0.32-0.500.15-0.35
Terrance West19352.6%-3-0.09-0.18-0.23-0.41
Spencer Ware21431.4%-17.60.290.34-1.08-0.74
Devontae Booker17442.3%-10.5-0.48-0.72-0.42-1.14
Giovani Bernard9122.2%-5.9-0.47-0.71-0.49-1.19
Lamar Miller26851.9%-14.3-0.38-0.58-0.72-1.31
Thomas Rawls10932.8%-8-0.85-1.23-0.13-1.36
Frank Gore26341.5%-23.5-0.28-0.44-0.99-1.43
Alfred Blue10011.0%-12.4-0.07-0.15-1.42-1.57
Doug Martin14432.1%-27.5-0.85-1.23-0.57-1.80
Theo Riddick9211.1%-8.9-0.3-0.47-1.34-1.81
Rashad Jennings18131.7%-23.5-0.72-1.05-0.88-1.93
T.J. Yeldon13010.8%-12.7-0.32-0.50-1.63-2.13
Todd Gurley27862.2%-34.3-1.16-1.66-0.52-2.17
Paul Perkins11200.0%-9.70.160.16-2.42-2.25
Jerick McKinnon15921.3%-19.3-0.77-1.12-1.20-2.32
Justin Forsett8711.1%-9.7-0.78-1.13-1.29-2.42
Charcandrick West8811.1%-19.3-0.99-1.42-1.30-2.72
Dwayne Washington9011.1%-21.4-1.13-1.62-1.32-2.94

First, we can see the Buffalo Bills really stand out. Mike Gillislee, LeSean McCoy, and Tyrod Taylor made up three of the top-four spots in combined rushing efficiency in 2016.2 That right there points to an awesome offensive line, but also probably some talented ball carriers as well.

Three Raiders also ended up in the top-17 as well, with DeAndre Washington leading the way in overall rushing efficiency, with a Sum.Z of 1.73, over Jalen Richard (1.02) and then teammate Latavius Murray (0.92). Combine that with a low sack rate for QB Derek Carr, and you can see that Oakland’s offensive line was rock solid, paving the way to their 12-win season.

Speaking of Latavius Murray, he heads to the Vikings, who failed to impress. Jerick McKinnon and Matt Asiata were both in the bottom-11 qualified rushers in YPCOE. And while Adrian Peterson only had 37 totes of the ball in 2016, he came in even worse in YPCOE over his limited sample than McKinnon and Asiata. Yikes! Unless the Vikings show some serious improvement, I can’t imagine Murray goes for over 4.3 yards per carry (his career average) on his new team. He only managed a 4.0 YPC with a -0.4 YPCOE and a -0.61 YPCOE.Z behind the impressive Raiders front five in 2016, worse than former teammates DeAndre Washington and Richard.

Who else impressed? Well, when sorting by YPCOE, Jordan Howard stands out as the first back that didn’t benefit from a stellar offensive line. Teammate Jeremy Langford managed a -0.43 YPCOE, which is nearly 1.6 yards per attempt worse than Howard’s 1.16. Yes, Langford only had 62 carries and didn’t qualify for my cutoff, but over two years he has now managed a -0.62 YPCOE on 210 carries, compared to Howard’s 1.16 on 251 carries.

Of the big three (Le’Veon Bell, Ezekiel Elliott, and David Johnson), Johnson had the worst YPCOE at -0.12, compared to 0.41 for Bell and 0.26 for Elliott. When we factor in that the rest of Johnson’s RB teammates combined for 0.65 YPCOE on 56 carries, it makes his mark look even worse. Not that he was poor, but his gaudy fantasy numbers were less due to his yardage efficiency, and more due to his sheer volume, his TD efficiency, and his receiving prowess.

Finally, Todd Gurley finished dead last. I don’t think that’s an indictment on him as much as it is the Rams poor QB play. If you don’t have to worry about the pass, you can cheat a bit more against the run. Gurley will be in another rough situation in 2017, with the same QB, a tough schedule, and less luck than they had last year.

Subscribe for a constant stream of league-beating articles available only with a Premium Pass.

  1. Since ruTDRT is not normally distributed, I first transformed to a normal distribution and then took the z-scores.  (back)
  2. Sum.Z  (back)
By RotoDoc | @RotoDoc | Archive

Comments   Add comment