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NFL Week 2 RB Market Share Report

Welcome to the Week 2 edition of the RB Market Share Report. In this column, I report usage statistics and advanced metrics for all NFL running backs. I will also summarize RB workload statistics for all 32 NFL teams and highlight key trends as applicable.

I will publish updates to this column each week following the conclusion of Monday night’s games. As more games are played, our market share data become increasingly reliable — but at the expense of our foresighted edge on the public. Utilize this data to gain insight into play-calling trends and to target players with advantageous metrics before they break out.

To aid you in that effort, check out the Ultimate Zero RB Watchlist: AFC | NFC for more thorough analysis on RB depth charts and waiver wire adds. And for similar analysis on wide receivers, check out Neil Dutton’s Wide Receiver Target Report.

Team RB Stat Totals

TeamRush Att.TargetsOpportunitiesTotal YardsTotal TDPPR Points

Team RB Advanced Metrics

Below, I’ve provided definitions for some of the more obscure advanced metrics reported in this article. To learn more about these metrics and how to interpret them, check out my Passing Revolution series1 and my RB Game Script series.2

Team Opps% — The percentage of a team’s total offensive plays that ended in a RB opportunity (e.g. rush attempt or receiving target). This may be used to measure how frequently an offense utilizes its RBs in its offensive game plan.

Opps% (Tar) — The percentage of a backfield’s total opportunities that are receiving targets. This may be used to describe how an offense utilizes its RBs. For instance, pass-catching specialists like Theo Riddick report a career Opps% (Tar) of 70% or higher. Fantasy RB1s typically report an Opps% (Tar) between 25% and 30%.

Team PPR% — Similar to TS% and Rush%, this metric reports a backfield’s total PPR points as a percentage of the team’s total PPR points scored.

PPR% (Rec) — The percentage of a backfield’s total PPR points that derive from receiving statistics. Backfields with high PPR% (Rec) metrics provide ideal conditions for RBs to flourish.

TeamTeam Rush%Team TS%Team Opps%Opps% (Tar)Team PPR%PPR% (Rec)

Scouting Potential RB Breakouts

Over the last two seasons, we’ve witnessed the rise of a new fantasy RB1 paradigm. Modern fantasy RB1s derive about half of their PPR production from receiving statistics. Shawn Siegele elaborates on this trend in his Derrick Henry offseason breakdown:

“This trend directly results from the fact that, from 2000-2015, NFL teams were not getting the necessary value from their stud RBs because they were using them in ways that didn’t add to drive success. Savvy coaches have shifted the way they use their star runners. If you have weapons like Todd GurleySaquon BarkleyAlvin KamaraChristian McCaffrey, and David Johnson, it’s imperative to deploy them in the service of scoring points.”

More than raw opportunity or PPR scoring, what we’re really looking for is evidence that a coaching staff gets it. Whether or not a player is the current lead-back in his offense, what’s most important is that his coach is utilizing RBs in the passing game. For context, here are metrical averages for PPR RBs over the last two years:

 Team Rush%Team TS%Team Opps%Opps% (Tar)Team PPR%PPR% (Rec)

A couple key takeaways to keep in mind from the chart above:

  1. The primary differentiator between RB1s and RB2s is receiving acumen. Fantasy RB1s average a 15.3% team target share, whereas RB2s average just 7.6%. This difference is mirrored in Opps% (Tar) and PPR% (Rec).
  2. The primary differentiator between RB2s and RB3s is rushing volume and/or total opportunity. Both groups report similar target shares, but RB2s average an 11.7% improvement in Team Rush% and a 5.3% improvement in Team Opps%.
  3. Fantasy RB3s are more similar to RB1s than to RB2s. Ideally, we want to target fantasy RBs with borderline starting value that would inherit grand opportunity contingent on depth chart disruption. Examples include Dion Lewis in 2017, James Conner in 2018, and Austin Ekeler this season.

Advanced Metrics for All NFL RBs

PlayerTeamPPRTeam Rush%Team TS%Team Opps%Opps% (Tar)Team PPR%PPR% (Rec)
David JohnsonARI34.173.5%9.0%26.8%24.2%18.5%54.3%
Chase EdmondsARI4.25.9%3.4%4.1%60.0%2.3%83.3%
Devonta FreemanATL15.555.9%9.2%22.3%29.6%7.5%73.5%
Ito SmithATL11.529.4%4.6%11.6%28.6%5.6%45.2%
Mark IngramBAL32.434.2%3.3%20.9%6.9%11.8%15.4%
Gus EdwardsBAL6.725.3%0.0%14.4%0.0%2.4%0.0%
Justice HillBAL5.110.1%3.3%7.2%20.0%1.9%39.2%
Devin SingletaryBUF26.516.9%9.5%13.1%37.5%14.4%29.4%
Frank GoreBUF18.350.8%3.2%26.2%6.3%10.0%19.1%
Patrick DiMarcoBUF4.31.7%4.8%3.3%75.0%2.3%97.7%
Christian McCaffreyCAR50.283.3%20.2%41.3%32.7%30.7%43.2%
Alex ArmahCAR6.12.4%0.0%0.8%0.0%3.7%0.0%
David MontgomeryCHI19.354.5%5.9%25.0%14.3%16.7%27.5%
Tarik CohenCHI17.49.1%22.1%17.0%78.9%15.0%89.7%
Mike DavisCHI9.718.2%10.3%13.4%46.7%8.4%79.4%
Cordarrelle PattersonCHI6.16.8%4.4%5.4%50.0%5.3%21.3%
Giovani BernardCIN10.639.4%6.7%15.4%31.6%5.1%74.5%
Joe MixonCIN9.451.5%8.9%20.3%32.0%4.5%71.3%
Ezekiel ElliottDAL33.356.3%6.6%32.0%10.0%13.0%14.7%
Tony PollardDAL5.926.6%1.6%14.4%5.6%2.3%22.0%
Royce FreemanDEN22.344.7%10.0%22.8%27.6%13.0%50.7%
Phillip LindsayDEN21.251.1%16.3%29.1%35.1%12.3%62.7%
Kerryon JohnsonDET25.046.7%7.0%25.2%15.2%12.1%64.0%
Ty JohnsonDET6.210.0%2.8%6.1%25.0%3.0%41.9%
J.D. McKissicDET4.63.3%2.8%3.1%50.0%2.2%95.7%
C.J. AndersonDET4.326.7%0.0%12.2%0.0%2.1%0.0%
Nick BawdenDET1.00.0%1.4%0.8%100.0%0.5%100.0%
Aaron JonesGNB29.965.5%11.5%37.1%16.3%19.6%28.1%
Jamaal WilliamsGNB16.625.5%9.8%17.2%30.0%10.9%83.1%
Carlos HydeHOU18.556.6%1.8%28.2%3.2%11.1%6.5%
Duke JohnsonHOU16.128.3%10.5%19.1%28.6%9.6%45.3%
Marlon MackIND31.767.2%5.7%40.0%6.3%17.9%10.1%
Jordan WilkinsIND9.67.5%1.9%5.0%16.7%5.4%14.6%
Nyheim HinesIND8.19.0%11.3%10.0%50.0%4.6%72.8%
Leonard FournetteJAX26.175.7%18.2%38.8%30.0%14.0%56.7%
Ryquell ArmsteadJAX0.72.7%1.5%1.9%50.0%0.4%0.0%
Damien WilliamsKAN27.145.8%14.3%26.4%33.3%10.4%65.3%
LeSean McCoyKAN15.643.8%5.2%20.0%16.0%6.0%33.3%
Anthony ShermanKAN2.50.0%1.3%0.8%100.0%1.0%100.0%
De'Anthony ThomasKAN1.60.0%1.3%0.8%100.0%0.6%100.0%
Darwin ThompsonKAN1.42.1%1.3%1.6%50.0%0.5%92.9%
Austin EkelerLAC64.763.0%19.1%36.8%31.0%32.4%62.3%
Justin JacksonLAC14.528.3%5.9%14.9%23.5%7.3%20.0%
Derek WattLAC1.74.3%2.9%3.5%50.0%0.9%76.5%
Todd GurleyLAR26.848.4%7.8%27.8%14.3%15.0%17.9%
Malcolm BrownLAR23.027.4%1.6%14.3%5.6%12.9%8.7%
Darrell HendersonLAR0.01.6%0.0%0.8%0.0%0.0%0.0%
Kenyan DrakeMIA14.537.0%12.7%19.4%47.4%15.1%78.6%
Kalen BallageMIA4.433.3%8.5%15.3%40.0%4.6%88.6%
Mark WaltonMIA3.814.8%2.8%6.1%33.3%4.0%57.9%
Dalvin CookMIN54.163.1%13.2%44.7%10.9%36.8%17.7%
Alexander MattisonMIN7.420.0%0.0%12.6%0.0%5.0%0.0%
Ameer AbdullahMIN1.04.6%0.0%2.9%0.0%0.7%0.0%
CJ HamMIN0.00.0%7.9%2.9%100.0%0.0%0.0%
James WhiteNWE25.110.9%16.9%14.0%61.1%11.5%85.7%
Rex BurkheadNWE22.320.3%15.4%17.8%43.5%10.2%70.9%
Sony MichelNWE15.956.3%0.0%27.9%0.0%7.3%0.0%
Brandon BoldenNWE0.71.6%0.0%0.8%0.0%0.3%0.0%
James DevelinNWE0.33.1%0.0%1.6%0.0%0.1%0.0%
Alvin KamaraNOR30.963.4%15.5%33.0%29.7%17.5%54.0%
Latavius MurrayNOR16.026.8%5.6%13.4%26.7%9.1%31.3%
Zach LineNOR0.00.0%1.4%0.9%100.0%0.0%0.0%
Saquon BarkleyNYG40.478.4%14.6%33.3%31.0%20.5%29.0%
Wayne GallmanNYG13.15.4%4.5%4.8%66.7%6.6%41.2%
Elijhaa PennyNYG0.35.4%0.0%1.6%0.0%0.2%0.0%
Josh JacobsOAK34.274.5%1.6%32.7%2.8%21.3%11.1%
DeAndre WashingtonOAK6.310.6%3.2%6.4%28.6%3.9%73.0%
Jalen RichardOAK2.86.4%4.8%5.5%50.0%1.7%78.6%
Darren SprolesPHI11.817.3%7.0%10.9%40.0%5.8%60.2%
Jordan HowardPHI11.126.9%4.7%13.0%22.2%5.5%44.1%
Miles SandersPHI10.440.4%7.0%19.6%22.2%5.1%49.0%
James ConnerPIT24.072.4%10.1%26.9%27.6%16.3%52.5%
Jaylen SamuelsPIT5.717.2%3.8%7.4%37.5%3.9%61.4%
Benny Snell Jr.PIT2.33.4%0.0%0.9%0.0%1.6%0.0%
Chris CarsonSEA37.851.7%18.5%35.7%25.0%19.2%56.1%
Rashaad PennySEA17.027.6%1.9%15.2%5.9%8.6%17.6%
C.J. ProsiseSEA5.03.4%5.6%4.5%60.0%2.5%86.0%
Raheem MostertSFO29.129.7%9.4%21.3%18.5%15.4%57.7%
Matt BreidaSFO17.936.5%3.8%22.8%6.9%9.5%11.7%
Jeff Wilson Jr.SFO15.413.5%0.0%7.9%0.0%8.2%0.0%
Tevin ColemanSFO7.68.1%5.7%7.1%33.3%4.0%69.7%
Kyle JuszczykSFO2.11.4%3.8%2.4%66.7%1.1%71.4%
Peyton BarberTAM22.454.4%9.1%32.1%13.9%16.3%21.9%
Ronald JonesTAM11.229.8%1.8%16.1%5.6%8.2%25.0%
Dare OgunbowaleTAM9.20.0%10.9%5.4%100.0%6.7%100.0%
Derrick HenryTEN46.265.4%11.4%40.6%12.8%27.9%38.3%
Dion LewisTEN6.711.5%11.4%11.5%45.5%4.0%76.1%
Chris ThompsonWAS24.916.7%22.5%20.9%78.3%12.2%94.8%
Adrian PetersonWAS11.233.3%2.5%10.9%16.7%5.5%24.1%
Derrius GuiceWAS6.833.3%3.8%11.8%23.1%3.3%73.5%
Wendell SmallwoodWAS3.33.3%2.5%2.7%66.7%1.6%87.9%
Nick ChubbCLE31.385.4%12.1%37.7%18.6%17.9%37.1%
Dontrell HilliardCLE8.82.4%3.0%2.6%66.7%5.0%27.3%
D'Ernest JohnsonCLE13.69.8%9.1%8.8%60.0%7.8%84.6%
Le'Veon BellNYJ44.184.4%27.1%48.7%33.3%34.0%71.0%
Ty MontgomeryNYJ7.411.1%4.3%6.8%37.5%5.7%60.8%

Notable Backfield Situations to Monitor

In this section, I highlight backfield competitions and key statistical trends to follow during next week’s NFL games.

Arizona Cardinals

David Johnson still runs this backfield — even despite missing over a quarter of action due to an injured wrist against the Ravens in Week 2. He reports an ideal PPR% (Rec), but his Team Opps% and Team PPR% fall just short of the average RB1 standard. Arizona has been super pass-heavy to start 2019, but Johnson has earned only eight targets (for a 9% team target share). Contrast that with 19 targets for Le’Veon Bell and 17 for Christian McCaffrey this season. Johnson is still a PPR RB1, but he’s closer to borderline than elite status through two games. Poor backfield volume seems to be the culprit, so continue to monitor Arizona’s backfield usage over the coming weeks.

Atlanta Falcons

The headline here is Devonta Freeman’s woeful inefficiency, but Atlanta’s rush-aversion is a close second. Ito Smith is splitting snaps with Freeman in a near 50-50 committee, and Smith has been a much more efficient producer with his touches. Atlanta’s backfield usage boasts strong PPR% (Rec) and Opps% (Tar) metrics, but volume remains a huge issue so far this season. If the Falcons coaching staff reestablishes its running game over the coming weeks, Freeman’s and Smith’s receiving-based metrics suggest high fantasy upside. But until volume improves — and until Freeman corrects his poor rushing inefficiency — this is not a backfield to target in fantasy.

Baltimore Ravens

The Baltimore backfield came back down to earth in Week 2 as Mark IngramGus Edwards, and Justice Hill combining for 62 yards on 17 rush attempts. Meanwhile, QB Lamar Jackson gashed the Cardinals for 120 rushing yards, leaving only scraps for the rest of the backfield to fight over. Ingram remains the clear No. 1 RB in the Ravens backfield, but his Week 2 production is more indicative of his season-long median expectation. Poor receiving usage — plus Jackson’s dynamic rushing ability — stunts production for all Ravens RBs. Edwards and Hill are still worthwhile adds if Ingram suffers injury, but neither projects as knockout fantasy assets.

Chicago Bears

The Bears are the ultimate good news, bad news situation. The good news is that Matt Nagy is utilizing the Bears RBs in every facet of the offensive game plan. Chicago’s backfield boasts exceptional metrics across the board, including an encouraging PPR% (Rec) of 57.0% and an impressive Team Opps% of 60.7%. The bad news is twofold: 1) Many of these metrics are inflated due to the Bears’ cataclysmically embarrassing passing offense, and 2) Nagy is far too clever and cutesy with his player rotations, crushing the standalone value for all Bears RBs.

David Montgomery took the lead in Week 2 with 21 opportunities, 68 total yards, and 13.8 PPR points. So, if there’s one RB to ride in the offense, he’s likely the strongest option. Nonetheless, this backfield is fertile ground for a future Zero-RB play. The Bears’ metrics are fantastic, but usage is dispersed. If any of the Bears RBs suffers injury or falls out of favor, it would have massive implications for the other RBs in the rotation. Montgomery, Tarik Cohen, and Mike Davis have been frustrating early this season, but all three earn a strong “hold” recommendation.

Cincinnati Bengals

Frankly, I hate even looking at these Bengals metrics. Cincinnati is my least favorite backfield, and it’s really not even close. So far, Giovani Bernard and Joe Mixon have been used as interchangeable cogs in the offense, and neither has performed well to start the season. For two-plus years, everyone (myself included) has proclaimed that Mixon should own this backfield, and yet somehow he still doesn’t. Mixon’s ankle injury undoubtedly plays a role, but Cincinnati’s game planning is equally to blame. I see little evidence to suggest that Cincinnati’s backfield is prime real estate for fantasy success.

Dallas Cowboys

After one week evenly splitting work, Ezekiel Elliott pushed Tony Pollard back into reserve status in Week 2. Elliott toted the rock 23 times for 111 yards and a TD on his way to 20.0 PPR points. Pollard has been an inefficient rusher to start the season, and Dallas has failed to target him in the passing game despite Pollard’s college pedigree. His stock may be falling, but he is still the sole heir to Elliott’s elite usage, which makes him a low-value hold.

Meanwhile, Elliott’s four total targets is a big early-season red flag. He finally broke through as a pass-catcher last season, drawing 95 targets and amassing 567 receiving yards. New offensive coordinator Kellen Moore is not delivering that kind of receiving volume this season, which will absolutely limit Elliott’s season-long upside. Monitor this situation closely. If Elliott doesn’t improve his receiving production over the next two weeks, I would advise selling high on the strength of his name recognition. Right now, he’s a glorified version of Marlon Mack.

Denver Broncos

Glory be, look at all that green. Neither Royce Freeman nor Phillip Lindsay has separated himself in this 50-50 backfield split, but the Broncos’ offensive game plan is clearly working. Both backs have performed well given their volume of opportunities, and each player reports above average metrics in market share and PPR splits. Of all the backfields examined so far, Denver’s is the most promising for Zero-RB teams. If you were lucky enough to snag Freeman in the middle rounds, congratulations: You’re sitting on a sleeping giant if Lindsay misses time this season.

Houston Texans

To everyone’s dismay, Carlos Hyde rushed 20 times for 90 yards in Week 2, while Duke Johnson added six rushes for 31 yards and only one receiving target. Hyde is not a viable fantasy starter due to his abysmal receiving volume. By contrast, Johnson would be an ideal PPR asset if given sufficient opportunity. But, depressingly, Johnson may once again be locked in a committee as the change-of-pace back. Unfortunately for Johnson, Houston has a bevy of WR talent, so his week-to-week target volume could vary wildly.

Pittsburgh Steelers

You know that feeling when you’re playing NCAA 14 or Madden, and you go into a game with a rushing mindset, then you get down early and turn into an air raid offense? That’s Mike Tomlin in real life. Tomlin has become notorious for bailing on the run game in years past, and the Steelers backfield currently ranks dead-last in total opportunities this season. Further complicating matters, James Conner suffered a knee injury this week, and Ben Roethlisberger is out for the season with an elbow injury. Mason Rudolph will now command the Pittsburgh offense, which may funnel more play-calling towards the run.

On the other hand, Conner’s knee injury — while supposedly manageable — could introduce a more robust temporary committee with Jaylen Samuels and Benny Snell Jr. Samuels will likely be a hot waiver wire add this week, but I’m not sold on Tomlin’s commitment to the running game. Snell may actually hold the best overall upside if Conner’s knee injury proves more serious than expected.

San Francisco 49ers

Matt Breida delivered 121 rushing yards in Week 2, and Jeff Wilson Jr. pitched in two rushing TDs, but the real headline here is the ascension of Raheem Mostert. Mostert commanded four receiving targets this week, parlaying those opportunities into 68 receiving yards and a TD. He seems like the heir apparent to Tevin Coleman, whose high-ankle sprain could keep him out another two to four weeks. Breida is the obvious back to own in San Francisco, but Mostert may be the more valuable receiving asset. He’s likely worth a speculative add in deep leagues and would become a must-add with another good receiving showing and/or a Coleman injury setback.

Tampa Bay Buccaneers

Well, so much for #RonaldJonesSZN. Peyton Barber defiantly reclaimed his No. 1 RB role in Week 2, rushing 23 times for 82 yards and a TD. Barber has now drawn five receiving targets to Jones’ one this season, and Dare Ogunbowale has yet to earn a rush attempt. The Buccaneers backfield is clearly still a vortex of fantasy frustration, so it’s unwise to draw too many conclusions from such a small sample size. Nonetheless, Jones’ lack of receiving upside and Ogunbowale’s lack of rushing volume combine to create conditions wherein Barber is the most versatile RB on the roster. Trust me, I feel sick writing this sentence, but Barber could once again be the back to own in Tampa Bay.

Image Credit: Ric Tapia/Icon Sportswire. Pictured: Devonta Freeman.

  1. I introduce PPR% (Rec) in this series.  (back)
  2. I introduce Opps% (Tar) in this series.  (back)

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