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Zero RB Shangri La: How Season-Long Game Script Affects Running Back Production, Part 5

Welcome back to my NFL Game Script series, where I examine how game script affects running back fantasy production in season-long redraft and best ball formats.

In Part 1, I broke up our running back sample into quartiles based on their teams’ preseason Vegas Win Totals:

Quartile 1 is composed of players from teams with a Vegas Win Total of 9.5 or higher. Quartile 2 is 8.5 to 9.0; Quartile 3 is 7.5 to 8.0; and Quartile 4 is 7.0 and lower.

In this final installment, I’ll be examining players from Quartile 4, the quartile typically composed of the league’s worst overall teams. Additionally — since this is the final installment of this series — I will also be reviewing the key differences between each of our four quartiles from both team- and player-based perspectives.

Be sure to check out this series’ previous installments:

Run-Pass Splits for Each Quartile

To begin, let’s review season-long play-calling tendencies for each quartile in our analysis.

As expected, Quartile 1 averages the most overall plays per season and spends the highest percentage of its plays leading (41.4%). Meanwhile, Quartile 4 averages around 40 fewer plays per season and spends 54.9% of its total offensive plays while trailing.

* Keep this average play disparity in mind as we examine Q4 running backs a bit later. Since Quartile 4 averages 4.0% fewer offensive plays per season, elite Q4 RBs must either 1) boast incredible per-touch efficiency1 or 2) command an even greater portion of their teams’ total offensive usage than an average RB1.

Contrary to popular belief, Quartile 1 does not average the highest rush attempts per season. Instead, Quartile 3 ranks first in rush attempts and last in pass attempts. This helps explain our discovery in Part 4 that Q3 running backs offer exceptional fantasy upside.

Summary Statistics for PPR Running Back Tiers in Each Quartile

The chart below helps illustrate the core differences between RB1s, RB2s, and RB3s in each quartile. Remember that each quartile is composed of players from teams with different preseason Vegas win totals. So, these average differences reflect season-long game script’s effect on RB usage in each group. There’s a lot to unpack here, so bear with me as I highlight the most important takeaways from the data below.


Quartile 4 RB1s average nearly exactly the same total rush attempts as RB1s from Quartile 1. This result is somewhat surprising, especially in light of the team statistics we reviewed in the first section. Moreover, consensus public sentiment suggests that elite running backs on poor teams may suffer from low rushing usage while frequently playing from behind. The results above do not support that narrative.

Additionally, Q4 RB1s report the lowest average target volume of any group. This result also flies in the face of collective game script theory, which would suggest that running backs playing from behind more often should benefit from increased targets on a game to game basis.

Revising the Game Script Narrative

So, allow me to posit a new thesis based on the data above. First, note that Q3 RB1 is the group that suffers the greatest decline in rush attempts per season. This quartile of teams is slightly below average and may frequently face heightened competition throughout the season as these teams fight for playoff contention. That seasonal arc may facilitate more aggressive, pass-heavy play-calling, which could explain Q3 RB1s’ decline in total rush attempts.

Quartile 4, by contrast, represents teams that typically do not have an inside shot at playoff contention. So, perhaps coaching staffs on these teams prefer a conservative game plan that limits turnovers and insulates the offense from mistakes. Furthermore, these teams are likely most at risk of going into “tank mode” mid-season. As teams’ playoff prospects fade, so too does their incentive to win. So, in these situations, coaches may still prefer a conservative game plan that seeks to evaluate and develop players rather than emphasizing winning.

Regardless of interpretation, the data presented above paints a much more positive outlook for Q4 RB1s than anticipated. Indeed, despite their relative lack of targets, Q4 RB1s still average the second-most total opportunities among RB1s in any quartile.

RB2 and RB3

The most glaring takeaway from these groups is how differently RB2s are utilized in Quartile 3 and Quartile 4. Q3 RB2s actually report higher average rush attempts over their RB1 counterparts. However, this group also reports the lowest average target volume, which helps explain why these players typically finish as PPR RB2s rather than RB1s. This finding supports my assertion in Part 4 that Derrick Henry best projects as a PPR RB2 due to his rush-heavy historical usage.

Meanwhile, Q4 RB2s report by far the lowest overall rushing volume but nonetheless impressive receiving usage. In fact, there’s very little difference in rushing usage between Q4 RB2s and RB3s. Instead, the point of differentiation between those two groups is entirely due to RB2s’ receiving acumen. So, when targeting Q4 RBs that lack strong overall opportunity, it is vital that you target players with receiving upside.

Quartile 4 Running Backs’ Historical Performance

As with each of our previous installments, I correlated Q4 players’ team rush share and team target share with end-of-season PPR position rank. These results inform us if a player’s rushing or receiving volume is more important to PPR scoring based on whether the player’s team is leading or trailing more often during the season.

I performed these correlations for all Quartile 4 players. Then, I re-ran the correlations for two subsets of our sample population: (1) players with a high share of their team’s total opportunities (defined as 25.0% opportunity share or higher), and (2) players with a moderate share of their team’s total opportunities (defined as 15.0% to 24.9% opportunity share).

Refer back to Part 2 for a more thorough explanation of my methods and recommendations for how to interpret these results.

Quartile 4 Correlation Results

For all Q4 RBs, team rush share (aka: Team Rush %) dominates correlations for both game script conditions. This result reinforces the summary statistics from the first section that showed that Q4 RB1s boast elite rushing volume.

Additionally, the overall correlation results for Quartile 4 look eerily similar to our results for Q1 running backs. I’ve reproduced Quartile 1’s results below for the sake of comparison.

Quartile 1 Correlation Results

Quartiles 1 and 4 are by far the most similar groups analyzed. The only major difference between their correlation results is Q1 high opportunity players’ higher correlation for target share while leading. This difference is once again reflected in our original summary statistics, wherein Q1 and Q4 RB1s average the same rush attempts per season, but Q1 RB1s report a 6.6 increase in average targets.

On the surface, the similarity between these two running back groups seems odd. But, if we return to my game script hypothesis from earlier, we can begin to understand this connection.

I proposed that Q4 RB1s may earn high rushing volume due to conservative play-calling. Well, conservative play-calling would also affect Q1 RB1s — just for a different reason. Teams playing with a lead are more likely to play conservatively in order to chew up clock. Meanwhile, Q4 teams are likely to play conservatively in order to avoid turnovers and mistakes. While the rationale for playing conservatively is different for each group, the desired effect is the same: Denying the opponent additional possessions.

So, if we take a Q1 player like Alvin Kamara and compare him to a Q4 player like Saquon Barkley, we shouldn’t expect significant differences in each player’s season-long game script. Both players are likely to face a similar ratio of conservative vs. aggressive offensive play-calling across their entire season.

Team Share and Opps% Splits for Q4 Running Backs

Below, I report average team rush share, target share, opportunity share (aka: Opps Share), and Opps% splits for Q4 running backs in each game script condition.

This team share data synergizes well with our raw summary statistics data. It also provides rough benchmarks for evaluating Q4 running backs’ projected opportunity in their respective offenses.

RB1s command a team rushing share between 55.0% and 58.0% on average across each game condition. They also boast around a 12.0% team target share and over a 30.0% share of their team’s total opportunities. As I hinted at in the opening to this piece, elite Q4 running backs must control dominant shares of their team’s total offensive opportunities in order to achieve PPR RB1 status. The data above serves as confirmation for that assertion.

Also notably, Q4 RB1s do not report extreme Opps% splits favoring rushing or receiving too heavily. Instead, RB1s are typically players with a balanced skillset — which, in turn, lends itself to three-down usage. For a player to ascend to PPR RB1 status, he must likely offer a balanced Opps% profile2 that is amplified by an elite team opportunity share.

Additionally — and importantly — we once again see the distinct difference in usage between PPR RB2s and RB3s. Across each game script condition and total season usage, RB2s and RB3s report almost precisely the same team rush share. However, RB2s separate themselves based on their higher team target share and higher Opps% (Tar). So, when we evaluate potential RB2 targets in this quartile, we should try to find players with a career total Opps% (Tar) of around 24.0% and a career trailing Opps% (Tar) that exceeds 26.0% conservatively.

Quartile 4 is a Zero RB Oasis

Below, I’ve reproduced a chart from Part 1 reporting average end-of-season PPR position rank for each ADP tier3 of running backs from each quartile.

If you’re looking for deep sleeper running back candidates, this is definitely the quartile to target. Q4 RBs drafted in the RB37 to RB48 ADP range report an average end-of-season PPR finish of 28.7. That average PPR finish reflects high-end RB3 status with upside for low-end RB2 production.

As we examined in the previous section, Q4 RB2s and RB3s average around the same total rush attempts (167) but differ markedly in their receiving usage. So, when targeting these late round Q4 RBs, prioritize receiving aptitude.

Let me think: Is there some kind of fantasy draft philosophy that emphasizes targeting late-round RB options with receiving upside? Oh, silly me, of course: Zero RB.

Quartile 4 offers the ideal conditions for Zero RB prospects to flourish. Notable Q4 running backs currently being drafted in the RB37 to RB48 ADP range include: Royce Freeman (RB39)Ronald Jones (RB41), and Kalen Ballage (RB48).

Quartile 4 Player Averages by Career Opps% (Tar)

This chart reports average statistics for Q4 running backs based on their Career Opps% (Tar). In layman’s terms, Career Opps% (Tar) reports a player’s career receiving usage as a percentage of his total opportunities (rush attempts plus targets).

The chart above mostly serves as reinforcement to target Zero RB prospects in Quartile 4. All three Career Opps% (Tar) tiers report similar average end-of-season PPR ranks, but players with higher Opps% (Tar) boast the best production relative to their ADP rank.

Importantly, these high-quality receiving backs still return excellent value on their draft capital despite poor total opportunity. Running backs in the 23.9% and higher range report an average team opportunity share of only 19.4% and a relatively low team rushing share of just 30.1%. Instead, their 11.4% average team target share drives their PPR value.

So, as we analyze potential Zero RB targets from this quartile, we may excuse poor projected overall usage — as long as the player demonstrates solid receiving potential in his respective offense.

2019 Quartile 4 Running Backs

2019 Quartile 4 NFL Franchises: Buffalo Bills, Cincinnati Bengals, Denver Broncos, Detroit Lions, Miami Dolphins, New York Giants, Oakland Raiders, Tampa Bay Buccaneers, and Washington Redskins.

Below, I have highlighted Quartile 4 players who are likely to excel this season — and those who are likely to underperform expectation — based on their career Opps% splits and projected team usage.

As we examined in the previous sections, elite players must report a balanced Opps% profile and must face little competition for touches in their respective backfields. Quartile 4 also offers ideal conditions for Zero RB candidates to flourish. So, we should also be targeting high-ADP players with elite receiving acumen.

Each player below has his current ADP position rank indicated in parentheses.

“Can’t Miss” Players

Saquon Barkley (RB1)

In Part 1 of this series, I began our discussion of game script by poking rhetorical fun at the Twitter debate over Barkley this season. So, it’s only fitting that we conclude our series by addressing him specifically.

I spent the better half of this article arguing that game script does not affect Q4 RBs the way people may expect. And, I’ll be honest: My primary reason for harping on that so much was to alleviate anxiety regarding Barkley in particular. So what if the Giants may suck this season? The data analyzed herein demonstrates that the Giants’ potential offensive deficiencies likely won’t hinder Barkley’s campaign for the overall PPR RB1 title.

His rookie season team share stats are off the charts. He posted a 73.5% team rushing share, 20.8% target share, and 40.7% total opportunity share. Those marks rank fourth, fifth, and fifth, respectively, among all 273 running backs examined in this study. His Opps% splits were 68.3% rush vs. 31.7% targets, which confirms what we already knew: Barkley is perhaps the most balanced and versatile running back in the NFL.

David Johnson (RB5)

David Johnson is nearly as strong a PPR RB1 lock as Barkley is. Johnson posted a 72.1% team rushing share, 15.4% target share, and 39.2% opportunity share last season — and it was a down year for him! His career 27.5% Opps% (Tar) is elite for running backs with his historical touch volume. And, there are plenty of reasons to believe he will improve markedly on last season’s statistics in head coach Kliff Kingsbury’s new air raid system.

Don’t be scared away by Johnson’s potential game script. Draft him with confidence with an early first-round draft pick, perhaps even as early as 1.04.

Kerryon Johnson (RB15)

Barkley and David Johnson both checked the “opportunity” box last season, but Kerryon Johnson is a slightly different story. He posted an excellent 24.8% Opps% (Tar), which places him in company with Todd Gurley and Melvin Gordon as versatile RBs with a balanced overall profile.

He was also incredibly efficient with his opportunities, ranking second in the NFL in yards per carry (5.4). His receiving usage is also criminally underrated. Among running backs who played in at least six games last season, he ranked 20th in targets per game (3.9) and 17th in receptions per game (3.2).

However, Johnson missed his final six games due to a knee injury. As a result, he only achieved a 29.2% team rushing share, 6.8% target share, and 16.1% total opportunity share. Nonetheless, there’s cause for optimism this season. Detroit parted ways with Theo RiddickLeGarrette Blount, and Ameer Abdullah, and now only C.J. Anderson and Ty Johnson remain to compete with Johnson for touches. Luckily for Johnson, neither Anderson nor Ty Johnson project as meaningful threats to Kerryon Johnson’s target share.

I first highlighted Johnson as a sneaky RB1 candidate on July 9. Since then, his ADP has climbed dramatically — especially over the last three weeks.

He would have been a “buy” contender just a few weeks ago, but his recent ADP increase now likely offers true value. He projects as a high-end RB2 with strong RB1 upside. His profile screams “breakout” player, and he’s among my most-drafted running backs this offseason.

Players to “Buy” at Current ADP

Kenyan Drake (RB28)

Speaking of sneaky RB1 options,4 Kenyan Drake also profiled well in my Passing Revolution series last month. And, once again, his metrics continue to shine in this game script series. Despite splitting about 50% of the Dolphins’ touches with Frank Gore last season, Drake still achieved a 32.3% rush share, 16.0% target share, and 23.4% opportunity share. He also boasts a ridiculous 31.5% career Opps% (Tar), which is uncannily similar to Barkley’s mark last season. If Drake unexpectedly commands an even stronger share of the Dolphins’ touches this season, his Opps% splits suggest he could legitimately challenge for low-end RB1 status. Crazy, right?

Altogether, Drake projects as a solid RB2 based on the trends examined in this piece. He fits the “23.9% and higher career Opps% (Tar)” trend, which boasts an ADP over-rate of 66.7%. That particular group of players only averaged a 19.4% team opportunity share, which Drake exceeded last year by 4.0%.

Just like last offseason, concerns continue to mount regarding Drake’s projected opportunity in the Miami backfield. But, instead of Gore, now Kalen Ballage has emerged to challenge Drake’s RB1 depth chart status. Ballage profiles as an excellent Zero RB target at ADP RB48, but concerns over Drake’s potential usage may be overblown. If Drake simply maintains the same opportunity share he achieved last season — or even if his share drops several percentage points — his elite target share still makes him a fantastic mid-round buy.

Chase Edmonds (RB76)

Chase Edmonds lacks an easy path to strong opportunity in a backfield with David Johnson. However, the talented rising sophomore still achieved a strong Opps% (Tar) of 27.7% as a rookie, and his closest player comp is Ronald Jones.

Edmonds is a buy candidate for me for three reasons:

  1. His Opps% (Tar) last season falls in line with expectation for historical Q4 RB3s.
  2. He’s an antifragile option who would inherit extraordinary opportunity if Johnson suffers injury.
  3. He’s essentially free in redraft.

Moreover, while I respect the argument for Jones as a potential second-year breakout, I cannot justify Jones’ ADP in comparison to Edmonds. Edmonds was more productive as a rookie, he will likely play in an equally high-powered offense this season, and you can draft him in the final two rounds with ease rather than spending approximately ninth-round capital to draft Jones.

To be fair, Edmonds is mostly a flier rather than a breakout candidate given his backfield situation. Nonetheless, he’s still a fantastic stash on your bench due to his statistical profile, draft cost, and overall potential.

Players with Uncertain Outlooks

Joe Mixon (RB9)

Joe Mixon was really close to making the “Can’t Miss” section, but he does have a couple red flags in his profile. Most importantly, his 17.7% career Opps% (Tar) falls short of historical RB1 expectation. And, his 8.5% career team target share falls well short of what we typically expect from a Q4 RB1. His career profile most closely resembles Carlos Hyde, which is also somewhat discouraging.

But, there’s also a counterargument to be made here. Mixon’s rookie season was mired in offensive line struggles and coaching ineptitude. So, his rookie inefficiency and poor receiving usage may be excused due to those extenuating circumstances. Furthermore, he missed three games due to injury last season, which also likely lowers his career target share percentage.

Encouragingly, Mixon posted an impressive 66.0% team rushing share and 32.4% opportunity share last season. Both of those marks fit the RB1 profile without question. And, while it’s rare to see players deviate from their career Opps% splits in an individual season, Mixon may be an exception to the rule.

He was a prolific receiving threat at Oklahoma, averaging 32.5 receptions, 447.0 receiving yards, 4.5 receiving touchdowns, and 13.8 yards per reception over his two seasons in Norman. His athletic profile and college receiving statistics suggest that he should be a dynamic all-purpose back in the NFL. But, for whatever reason, his coaches have failed to properly utilize him in the passing game sufficient to his ability.

I’d wager that Mixon breaks away from the historical trend and does see a major increase in receiving usage this season under a new coaching regime. But, given his statistical red flags, I can’t count him among the “buy” candidates at his RB9 ADP.

Josh Jacobs (RB18)

I hesitate to break down Jacobs simply because we haven’t yet seen him play a single NFL down. As a first-round draft pick with limited competition for touches, he projects as a strong RB2 candidate on paper. However, his college profile does not scream “three-down” asset like Mixon’s or Barkley’s does.

College target data is hard to come by, so I’ll have to settle for touch statistics here. Jacobs’ collegiate Touch% splits were 83.9% rushing vs. 16.1% receiving at Alabama. If we assume that Jacobs’ catch-rate was around 75.0%,5 then his Touch% splits would translate to an Opps% (Tar) of 25.5%. If he also maintains that style of usage in the NFL, then his outlook remains excellent. However, we have no research-based evidence that his collegiate Opps% (Tar) will directly translate in an NFL context.

But, I’m also somewhat concerned about Jacobs for another reason. Oakland recently lost OG Gabe Jackson to a knee injury in training camp,6 which further weakens an already shaky offensive line. On top of that, offensive line coach Tom Cable has a horrible historical track record in pass protection in particular.

The injury to Jackson creates uncertainty regarding the Raiders’ ability to effectively block for Jacobs. And, head coach Jon Gruden’s antiquated offensive scheme may not set Jacobs up for early career success. Altogether, I think there’s a non-zero chance that Jacobs finishes 2018 as a fantasy RB3 — and by no fault of his own. Mixon experienced a compellingly similar team situation as a rookie in 2017 and finished as the PPR RB34.

I’m not advising that you fade Jacobs, but I am urging some degree of caution. Meanwhile, Jalen Richard (ADP: RB60) profiles as a James White doppelgänger and remains an excellent late-round selection, especially for Zero RB teams.

Players to “Sell” at Current ADP

Derrius Guice (RB32)

After missing his entire rookie season with a torn ACL, Derrius Guice is now a reasonably hot commodity in the redraft world as a sophomore. However, he recently suffered an injury setback and has not yet been medically cleared for Week 1 action, per the Washington Times.

Injury concerns aside, his collegiate profile does not inspire confidence in his abilities as a pass-catcher. In three seasons at LSU, he only managed 32 receptions for 250 receiving yards and three touchdowns. Granted, LSU does not historically prioritize RB usage in the passing game. Nonetheless, Guice’s poor receiving production is still somewhat alarming. Even if he earns 150-plus rush attempts this season, that may not overcome his receiving shortcomings. And, as we examined earlier in this article, receiving usage is of paramount importance for Q4 RB2s and RB3s.

Given his injury concerns, poor receiving profile, and backfield competition with Chris ThompsonAdrian Peterson, and Bryce Love, he’s a strong sell for me.

Image Credit: Zach Bolinger/Icon Sportswire. Pictured: Kenyan Drake.

  1. Efficiency is notoriously difficult to project and is among the least sticky metrics from season to season.  (back)
  2. About 79% rushing to 21% receiving.  (back)
  3. RB1-RB12, RB13-RB24, RB25-RB36, RB37-RB48, RB49+  (back)
  4. This is somewhat tongue-in-cheek on my part, but I still stand by this take.  (back)
  5. This catch rate would place him around the 75th percentile among running backs last season, which is somewhat aggressive.  (back)
  6. Jackson is expected to miss eight weeks of action.  (back)

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