DFS Playbook: How to Pick a Running Back

Aug 16, 2017
DFS Playbook: How to Pick a Running Back

You should be able to nail your DFS RB picks almost every time. That's not hyperbole. RB is predictable in a way no other position is. I'm going to show you how to leverage that predictability to maximize your DFS profits, in addition to:

  • How many DFS players get RB matchups wrong.
  • How Vegas odds are a RB cheat code.
  • How million-dollar GPP winners have approached RB in their lineups.

DFS Playbook 2017: QB | WR | TE | DEF | K | DFS Strategy Hub

3 Fundamentals of Accurate Running Back Projections

The NFL may have shifted to a pass-first league, but RB is still the most predictable fantasy position. Why? A run or catch out of the backfield has a lower range of potential outcomes than a downfield pass. This blunts the degree to which efficiency can impact bottom-line production; opportunity becomes the driving factor. And opportunities for running backs follow predictable patterns based on game script.

1. Leverage the Predictability of Touches

Given that 2.2 yards per carry—0.22 fantasy points—separates Jamaal Charles, the league's post-merger leader in per-carry average, from Trent Richardson, a colossal bust who was couch-bound by age 25, we shouldn't be surprised that opportunity trumps all when it comes to RB fantasy scoring:

Correlation of In-game RB DFS Points to In-Game Attempts & Efficiency
Actual Stats Correlation to DK Pts Actual Stats Correlation to FD Pts
Touches .69 Touches .67
Rush Att .57 Rush Att .57
Snaps .56 Snaps .52
Yards/Touch .41 Yards/Touch .44
Targets .42 Targets .34
Yards/Rush .31 Yards/Rush .33
Yards/Rec .21 Yards/Rec .24

Data from 2013-16 and does not include RBs projected below 9.0 points by 4for4 in a given game.

On average, roughly three-quarters of RB fantasy scoring comes from yardage. More often than not, yardage will grow from a steady diet of touches rather than one-off long gains. In fact, runs of 20+ yards occurred 311 times during all of 2016—just 0.61 times per game. And only four running backs had a run of 20+ yards in even half their games: Ezekiel Elliott, Jay Ajayi, LeSean McCoy, and Jordan Howard; all solid DFS plays last season not because their big plays were foreseeable, but due to their bankable weekly touch volume.

As a weekly stat, touches provide a refreshing air of predictability among game logs mostly polluted with volatility. The correlation of touches from one game to the next is .5331 moderate in the larger world of correlations, but extremely strong in the daily fantasy realm—and only three game's worth are necessary to achieve maximum predictiveness. Due to this predictiveness, fantasy points in the most recent game better predicts fantasy points in the next game at RB than at any other position. And in certain cases, a RB's last game is more predictive than an entire season’s worth of games at another position:

Single-Game Fantasy Point Correlations: Last Game and Optimal Sample Size
DK Pos Optimal Amt of Gs Correl (Optimal Gs) Correl (Last G) FD Pos Optimal Amt of Gs Correl (Optimal Gs) Correl (Last G)
RB 13 .369 .278 RB 13 .371 .265
TE 12 .333 .131 TE 12 .338 .118
QB 15 .217 .090 QB 15 .275 .091
WR 15 .306 .083 WR 13 .260 .068

Data includes all top-30 QBs/TEs and top-50 RBs/WRs from 2014-16.

The correlation of single-game fantasy points to season-to-date fantasy points per game is .3 or greater in 13 of the 15 possible in-season sample sizes for RB; at no other position is it .3 or greater in more than four.2

2. Analyze Matchup in Terms of How It Will Affect Usage

Despite RB not being the position with the narrowest range of weekly outcomes—that's QB—RB is still the easiest position to predict. Why? Because we can more precisely predict which part of the range a given RB will land in than we can any other position.3

While looking at offensive line metrics like adjusted line yards may at times provide a small edge, offensive line analysis is on the wrong side of the Pareto principle for the most part. When thinking about RB matchups, the opponent's effect on touch volume is of primary concern; RBs can still put up points on a good defense if given enough opportunity. For example, David Johnson punched in 3 TDs in a Week 16 loss last year to the Seahawks, who finished the season No. 1 in yards per carry allowed (3.4).

Since a team attempting a lot of rushes in a given game is largely a byproduct of winning rather than a cause of it, running back carries will fluctuate from week to week based on game script. When analyzing RB matchups, two main game-script related questions should be considered:

  • How will matchup affect running back snaps and overall usage? The league average offense rushed 47.1% of the time when leading or tied in 2016, but just 33.6% of the time when trailing. Whether due to a lack of pass-blocking prowess or receiving skills relative to other options on the active roster, certain running backs will scurry to the sideline in passing situations. These early-down backs—think LeGarrette Blount—have greater odds of success when their team remains in positive game script, which is best predicted by the point spread (more on that later). Passing-down specialists—think James White—are more likely to flourish in the opposite scenario. Every-down feature backs—think David Johnson or LeVeon Bell—will of course not be affected.
  • How will the matchup affect goal-line usage? Of the 444 rushing TDs scored during the 2016 season, 297 (66.9%) occurred at/inside the opponent's 5-yard line, and 392 (88.3%) occurred in the red zone. In the red zone when leading or tied, the league average offense rushed on greater than one-half of its plays; when trailing, it did so less than 40% of the time. Again, the point spread can serve as a valuable predictor: Favorites combined to average 0.98 rushing TDs per game while underdogs combined to average 0.74 rushing TDs per game.

3. Decrease Expectation for a Running Back Playing with a Lower Body Injury

Running backs suffer roughly a 9% dip in fantasy performance when playing in a game after being listed on the final injury report. The worst injury culprits are to lower-body joints—knee, ankle, foot, toe, etc. Hamstring injuries are not a cause for concern unless they are of the severe variety.

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3 Keys to Running Back Cash Game Lineup Construction

Due to the elevated confidence with which we can forecast RBs, they provide the best opportunity to maximize the scoring floor of a lineup. The higher you keep your lineup's scoring floor, the more cash games you will win over the long term, so it's critical to hit on the right RBs in cash games. But the amount of points it takes for RBs to "hit" differs from other positions and isn't linearly related to salary. To account for this, I ran a series of regressions on the relationship between salary, position, and fantasy scoring to derive a formula that quantifies "hitting value" for RBs at FanDuel and DraftKings' most common cash line benchmark:4

RB cash game target score for 150 DraftKings Points (3x) = 10.1 + (salary * 0.00135)

RB cash game target score 120 FanDuel Points (2x) = 5.9 + (salary * 0.00127)

For example, even if you were aiming for 3x, or 150 points, overall on DraftKings in Week 14 last season, you wouldn't have needed LeVeon Bell to score 27 points to hit value just because his salary was $9,000. Because scoring expectation relative to salary is nonlinear, 22 points from Bell would be deemed a good value, and your lower-salaried players would be expected to make up the 5-point gap. 5

RB Cash Game Target Score Examples

DK Salary ($)

DK Cash Target

DK Value

FD Salary ($)

FD Cash Target Score

FD Value

























Understanding this concept is especially crucial in regard to RBs; almost every slate dictates you make a decision about some chalk RB play who is either extremely expensive or extremely cheap. You do not want to be the person who fades a stud like David Johnson and then turns around and plays some minimum-priced scrub like Travaris Cadet.

1. Target Home Favorites to Maximize Consistency

Anyone who had trouble pegging Devonta Freeman in 2016 would have done well to use him exclusively when he was as a home favorite, where he scored 20+ DraftKings points in five of seven games while doing so in only two of nine games otherwise. Same goes for Melvin Gordon, who scored 20+ in four of five games as a home favorite but two of eight games otherwise. Latavius Murray scored 20+ three of six home-favorite games but one of eight non-home-favorite games; the list goes on and on. The point is this: Both playing at home and being the favorite have strong positive correlations to point differential, and since positive game script leads to more running back usage, which leads to more fantasy points, home-favorite RBs are the most consistent RB plays in DFS:

Data from 2013-16 and does not include RBs projected below 9.0 points by 4for4 in a given game.

The discrepancy between home-favorite RBs and the rest of the pack is so large that you should seriously consider fading almost every RB in cash if his team is not a home favorite—save for feature backs like David Johnson or mispriced punt plays slated for feature-back volume. In between those two extremes, a lot of bust-causing variance exists.

2. Tailor Your Selections to Site Scoring Format (and Pricing)

Differences in running back prototypes are magnified by differences in DFS site scoring formats: Pass-catching RBs are more valuable on sites like DraftKings that have PPR/yardage-heavy scoring formats, and early-down/goal-line RBs are more valuable on sites like FanDuel that have 0.5-PPR/TD-heavy scoring formats.

DraftKings: Pay Up for a Stud, Use a Running Back in the FLEX

Owing usually to their multi-purpose, game-script agnostic roles, RBs priced $7,500+ on DraftKings have hit cash game value more consistently than any other position or salary range on the site:

DraftKings Cash Game Target Score Consistency Rate (2015-16)
Salary ($) QB Cons % n (QB) RB Cons % n (RB) WR Cons % n TE Cons % n (TE)
9000+ 72.7% 11 44.7% 47
8500–8900 16.7% 6 71.4% 7 52.5% 61
8000–8400 50.0% 14 40.0% 15 23.8% 42 75.0% 4
7500–7900 37.7% 61 46.8% 47 30.0% 110 28.6% 7
7000–7400 31.8% 110 30.8% 65 32.3% 130 50.0% 8
6500–6900 32.4% 136 33.3% 69 29.7% 155 31.6% 19
6000–6400 33.6% 137 24.2% 99 33.7% 169 46.7% 15
5500–5900 27.9% 165 24.6% 134 24.4% 180 40.0% 35
5000–5400 18.2% 379 28.1% 139 22.6% 190 14.6% 48
4500–4900 24.5% 212 21.8% 229 35.6% 90
4000–4400 30.1% 219 23.7% 266 32.5% 77
3500–3900 21.9% 178 27.0% 230 25.2% 119
3000–3400 25.0% 100 22.6% 186 28.7% 188
2500–2900 24.0% 175

Data does not include non-starting QBs, RBs/WRs projected under 9.0 points, and TEs projected under 7.5 points by 4for4 in a given game.

There's been no more guaranteed source of points on DraftKings than a high-volume stud RB. The top-tier RB pricing sample size is small, but the aforementioned fact rings true even if the sample sizes is doubled by expanding it to the past four years. In fact, the .33 correlation between RB salary and DraftKings points in the corresponding game is the strongest among the four skill positions.6 Paying up for RB works because not many backs receive a large workload in both the run game and the pass game. Pass-game usage becomes increasingly important with full-PPR scoring; when compared with FanDuel, RBs on DraftKings have required an additional 0.3 receptions per game to hit cash game value.

The data also suggests that using RBs in the FLEX is a sound strategy. RBs have maintained an edge consistency-wise over WRs in the $4,000–$5,000 range, which is generally the range in which you'll end up shopping for a FLEX option.

FanDuel: Lock in Volume and Goal-Line Work

Even though it awards a half-point less per reception than DraftKings, FanDuel is also a site where expensive running backs have offered unparalleled consistency:

FanDuel Cash Game Target Score Consistency Rate (2013-16)
FD Salary ($) QB Cons % n (QB) RB Cons % n (RB) WR Cons % n (WR) TE Cons % n (TE)
9000+ 46.7% 192 51.2% 123 40.4% 114
8500–8900 33.5% 209 43.4% 145 45.1% 175 11.1% 9
8000–8400 34.5% 258 36.3% 146 37.0% 211 58.5% 41
7500–7900 32.9% 356 25.3% 182 36.4% 269 33.3% 36
7000–7400 29.7% 306 34.1% 293 28.5% 389 30.6% 36
6500–6900 22.1% 312 27.8% 399 26.6% 537 30.1% 28
6000–6400 24.1% 220 31.2% 337 30.9% 560 31.8% 170
5500–5900 34.5% 55 29.6% 240 31.6% 383 31.0% 248
5000–5400 25.0% 68 22.7% 141 31.2% 237 32.0% 197
4500–4900 39.7% 68 32.3% 96 32.6% 89

Data does not include non-starting QBs, RBs/WRs projected under 9.0 points, and TEs projected under 7.75 points by 4for4 in a given game.

The drop-off in success rate from the $9,000+ tier to the $7,000–$7,900 tier is steeper at RB than any other position; the latter range is where variance starts to take its toll if a matchup isn't completely optimal. RBs on FanDuel have needed roughly 5% more rushing TDs to hit value than those on DraftKings, so more often than not, you won't be able to afford to forego the bankable rushing TD rate of a favorite. RBs that don't get goal-line work should almost never be viewed as viable cash game options on FanDuel.

3. Know When to Pull the Trigger on a Cheap Running Back

Sometimes you just can't make things work elsewhere if you pay up at RB, while at other times you may need to save salary on one RB to afford paying up for another. Either way, the dilemma of whether or not to use an inexpensive RB will often present itself. How should you go about it? (For our purposes, I'll define "inexpensive" as less than $1,000 above site minimum.)

  • Aim for starter’s touches: Inexpensive RBs who hit cash game value on FanDuel/DraftKings have averaged 15.1/14.1 projected touches by 4for4. As mentioned earlier, punting with RBs who are strictly receiving specialists isn't a good move in cash games.
  • Matchup isn't as important as usual: Among RBs to hit cash value on each site, there was a relatively even distribution between home favorites and road underdogs. At extremely low price points, touch volume will offset a difficult matchup.

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4 Strategies for Choosing Running Backs That Win GPP Tournaments

Note: Data in this section was compiled from first-place lineups in the 2015–16 DraftKings Millionaire Maker and FanDuel Sunday Million guaranteed prize pool tournaments.

1. Use a Studs-and-Scrubs Approach at the Two RB Slots

First-place lineups have been absolutely nailing the RB1 slot. The highest-scoring running back in a winning lineup has averaged nearly 10 points more than the second-highest scoring back on each site:

Average RB Score in 1st-Place Lineup (2015–16)
Site/GPP Highest Scoring RB Next-Highest Scoring RB Scoring Differential
FanDuel Sunday Million 31.1 21.3 9.8
DraftKings Millionaire Maker 35.5 26.2 9.3

You almost have to think of your top running back as a separate entity from the other(s) and construct your lineup accordingly, which usually means not punting both RB slots. At least one running back priced $5,000 or more was used in 94% of first-place Millionaire Maker lineups on DraftKings, while at least one priced $6,500 or more was used in every single first-place Sunday Million lineup on FanDuel.

That said, the other, or next-highest-scoring RB in each of the sites' first-place lineups has averaged nearly 10 points fewer than the highest-score one, so it only makes sense that those lineups have dedicated far less cap space to the RB2 slot:

Average RB Salary in 1st-Place Lineup (2015–16)
Site/GPP Most Expensive RB Next-Most Expensive RB Salary Differential
DraftKings Millionaire Maker $6,850 $5,044 $1,806
FanDuel Sunday Million $7,938 $6,315 $1,623

Generally, the RB2 slot is where you want to find a back slated for cheap volume in a good situation. First-place Millionaire Maker lineups spent fewer than $6,000 on the RB2 over 80% of the time, while first-place Sunday Million lineups spent fewer than $7,000 on the RB2 nearly 90% of the time.

2. Avoid Being Overly Contrarian

Since RB is relatively predictable, it's not a position where deliberately being contrarian often pays off. RBs collectively have averaged the highest ownership percentage of any position in the first-place lineups on both DraftKings (17.6%) and FanDuel (17.1%). That makes sense given the high-low pricing split: Expensive studs and cheap value plays are going to be highly owned more often than not. Winning lineups haven't hesitated to take advantage of the RB value available. In fact, you may actually be doing yourself a disservice by not taking advantage of chalk RB value—roughly two-thirds of the first-place lineups on each site used a RB owned by at least 20% of the field.

Highest Owned RBs in 1st-Place Lineup (2015–16)
Site/GPP Highest Owned RB Next-Highest Owned RB Ownership Differential
FanDuel Sunday Million 25.9% 8.2% 17.7%
DraftKings Millionaire Maker 28.2% 13.2% 15.0%

For the most part, doubling up on highly owned RBs hasn't been a strategy to appear in the first-place lineups often, especially on FanDuel. Only 14% of the winning Sunday Million lineups contained RBs who both ownership of 20% or more each; 33% of Millionaire Maker lineups did so. The time to go full-on contrarian at RB on DraftKings has been when using one in the FLEX: Over three-quarters of first-place Millionaire Maker lineups that used a running back in the FLEX deployed at least one RB that ended up with less than 6% ownership. (The FLEX spot in first-place lineups was split evenly between RB and WR.)

3. Target Favorites for the Highest Upside

In addition to more consistently hitting cash game value, RBs playing on favorites have shown more upside than those on underdogs, exceeding expectation significantly more when hitting value:

RB Points Above Target Score When Hitting Value vs. Home-Road/Favorite-Underdog Split
DK Split DK Pts Above Exp % Above Exp FD Split FD Pts Above Exp % Above Exp
Home Favorite 7.66 42.9% Home Favorite 6.90 46.1%
Road Favorite 7.31 40.1% Road Favorite 6.57 43.1%
Road Underdog 6.45 37.2% Home Underdog 5.99 40.9%
Home Underdog 6.31 37.1% Road Underdog 5.56 37.4%

Data from 2013-16 and does not include WRs projected below 9.0 points by 4for4 in a given game.

The highest-scoring RB in the first-place lineups has scored 30+ points on DraftKings or 25+ points on FanDuel roughly three-quarters of the time. Home-favorite RBs have accounted for nearly half of the games over the past four seasons that hit those benchmarks, while road underdogs have accounted for less than one-quarter of those games. (Keep in mind home favorites/road underdogs each make up roughly one-third of all NFL games.)

4. Don't Avoid Stacking

You might be surprised to hear that RB stacking is a perfectly viable strategy—one which appeared in first-place lineups fairly regularly. There was at least one RB stack in 52% of first-place lineups in the Sunday Million and 47% of those in the Millionaire Maker, frequencies that pale in comparison to QB-WR stacks, but are still significant nonetheless.

That said, I chose the phrasing “don’t avoid” deliberately because forcing RB stacks means chasing correlations that are not as strong as QB-receiver. But by not avoiding RB stacks when you arrive at them organically, you don't allow yourself to be restricted from using what you think are the best players. That's what Jrveurink did to win the Millionaire Maker in Week 17 of 2016, pairing Devonta Freeman with Julio Jones and Matt Ryan.

Choosing not to avoid RB stacks also has the added benefit of differentiating your lineup; many DFS players actively avoid pairing RBs with teammates other than D/ST.

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RB Daily Fantasy Playbook (Recap)

RB projection strategy:

  • Leverage the predictability of RBs.
  • Analyze matchup in terms of how it will affect usage.
  • Decrease expectation for RBs playing with a lower-body injury.

RB cash game strategy:

  • Target home favorites to maximize consistency.
  • Tailor your selections to site scoring format (and pricing).
    • DraftKings: Pay up for a stud, use RB in the flex.
    • FanDuel: Lock in volume and goal-line work.
  • Know when to pull the trigger on an inexpensive RB.

RB tournament/GPP strategy:

  • Use a studs-and-scrubs approach at the two RB slots.
  • Avoid being overly contrarian.
  • Target favorites to maximize upside.
  • Don't avoid stacking.

Photo by Don Juan Moore/Getty Images.

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1. When looking at all top-50 PPR running backs from 2014–2016. (back)

2. The same holds true for 4for4’s projections: our projected volume numbers all had a stronger correlation to actual fantasy points scored than our projected efficiency metrics over the last four seasons. (back)

3. As a gut check, I also compared the correlation of 4for4’s projected fantasy points to actual fantasy points scored for each position, and running backs led the way. (back)

4. Remember this is just a benchmark; cash lines will vary week-to-week and slate-to-slate. (back)

5. He scored 54.8. 4for4 was all over him in cash and GPP. (back)

6. Using 2013-16 data, not including non-starting QBs, RB/WRs projected by 4for4 for less than 9.0 points and TEs projected for less than 7.5 points. (back)

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