DFS Playbook 2017 Strategy: How to Pick a Wide Receiver

DFS Playbook 2017 Strategy: How to Pick a Wide Receiver

By Chris Raybon (Senior Daily Fantasy Expert), last update Dec 17, 2018

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Chris Raybon is the Senior Daily Fantasy Editor at 4for4 Fantasy Football.

Follow Chris Raybon on Twitter: @ChrisRaybon.

If you're not good at picking wide receivers, you're not good at daily fantasy football. Period.

Three starters mean DFS players make more decisions about WRs than any other position. I will present proven ways to ensure those decisions lead to max profits.

First up will be how to make the most accurate wide receiver projections. Next, how to maximize the rate at which your wide receivers hit value relative to their salary. After that, interesting data that says fantasy points allowed leads us astray. Finally, the deconstruction of first-place lineups to reveal winners' million-dollar secrets at WR.

DFS Playbook 2017: QB | RB | TE | DEF | KDFS Strategy Hub | DFS Subscription Overview

The 2 Fundamentals of Accurate Wide Receiver Projections

Projecting any oter position involves a straightforward process and clear point of emphasis. But projecting WR is complex because they score in more ways and situations.

1. Weight Production More Than Volume as Sample Size Increases 

Gadget plays aside, every scoring opportunity for a wide receiver has to start with a target. But average target depth varies. It's less than 7 for a high-percentage route runner like Jarvis Landry. And it's more than 17 for a lid-lifting deep threat like DeSean Jackson. The result? Not all opportunities are created equal.

No particular type of efficiency will ensure fantasy success. And no particular type of inefficiency will prevent fantasy success. Take the top 12 last season, for instance. It included catch rates from Mike Evans' 55.5% to Michael Thomas' 76.1%, yards per catch averages from Larry Fitzgerald's 9.6 Julio Jones' 17.0, and TD rates from T.Y Hilton's 3.9% Davante Adams' 9.9%.  

Emphasizing target volume while mostly disregarding efficiency will best predict upcoming production over a limited sample size. 

But production itself becomes the best barometer as sample size grows:

In-season Per-game Average with Highest Correlation to WR DFS Points in Next Game For Each Possible In-season Sample Size
 Sample Size Most Predictive Correl (DK Pts) Most Predictive Correl (FD Pts)
1 Targets .124 Targets .112
2 Targets .155 Targets .139
3 Targets .205 Targets .189
4 Targets .207 Targets .190
5 DK Pts .221 Rec Yds .201
6 DK Pts .239 FD Pts .218
7 DK Pts .249 FD Pts .229
8 DK Pts .251 FD Pts .231
9 DK Pts .245 FD Pts .226
10 DK Pts .236 FD Pts .222
11 DK Pts .265 FD Pts .249
12 DK Pts .251 FD Pts .234
13 DK Pts .288 FD Pts .260
14 DK Pts .283 Rec TD .257
15 Rec Yds .308 Rec Yds .256

Data from top 50 WRs in each of the last three seasons (2014-16).

A target, unlike other usage stats such as pass attempts and carries, often involves skill. Save for bubble screens and so on, a target requires gaining separation and getting open. Then the quarterback has to be able locate the open man, while blocking has to give all this time to develop. Skill of the other receivers on the field also plays into which receiver is the target. And because some targets are deeper downfield, production becomes more predictive than targets.

Take the struggles of Allen Robinson, Brandon Marshall, and DeAndre Hopkins in 2016. Going into Week 10, all three ranked outside the top 30 in fantasy scoring despite top-12 ranks in targets. While eight or nine games is not a large sample size in the big picture, it's enough in daily fantasy football. The trio's struggles were indicative of a larger problem, and none of them managed to rebound. Nine-plus targets per game? That's nice—unless they're from Blake Bortles, Ryan Fitzpatrick, or Brock Osweiler.

It works both ways of course. Tyreek Hill was still a DFS afterthought to many last season as late as Week 12. Despite top-25 numbers, Hill averaged only 6.0 targets per game in Weeks 7–11. But that production on limited volume was a precursor to a top-five fantasy finish the rest of the way.

Unbeknownst to you and I, Jeremy Maclin played with a torn groin in 2016. Unreported injuries are yet another reason to note recent production. Regression to the mean occurs not only due to random statistical luck. Many very real factors affect production, and they will take time to even out.

Getting targets in your lineup will make you a solid DFS player. But you won't have a true edge unless you play WRs who produce more than volume suggests.

2. Account for the Factors That Impact Wide Receiver Production

Below are critical factors that influence projected opportunity and/or efficiency.

  • Target market share. Adjusts for games with outlying pass attempts to clarify a team's target hierarchy. Only three top-20 WRs had a target share below 20% in 2016. Mike Evans led the league with 29.9%. 

  • Red zone targets. Roughly half of all receiving TDs come on plays that start at or inside the opponent's 10-yard line. Seventy percent begin within the red zone. Relative to a target outside the red zone, a red zone target was worth 64% more on FanDuel and 48% more on DraftKings.

  • Deep targets. Defined as when a pass travels 16+ yards beyond the line of scrimmage, deep targets get caught 40% of the time. Deep targets are worth double on FanDuel and one-third more on DraftKings.

  • Cornerback matchups. By my count, wide receivers performed below their fantasy average in 57% of games shadowed in 2016. The average production drop-off was 13%. A size advantage over a corner or a speed/agility advantage over a larger one tends do pay fantasy dividends, as does a matchup against an inexperienced backup cornerback filling in for a starter.

  • Defensive scheme. Doubling, zone, blitzing, etc., funnels the ball to specific types of receivers or areas of the field.

  • Injuries. Wide receivers suffer a 15 percent dip in fantasy production after a week on the injury report. All types of injuries tend to hamper both volume and efficiency. Foot or toe injuries tend to be the most problematic.

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3 Keys to Wide Receiver Cash Game Lineup Construction 

To optimize your DFS lineup, you need to account for the volatile scoring expectation of WR. Below is a formula that adjusts for positional- and salary-based expectation. It calculates the amount of points to target from a WR in cash games: 

WR cash game target score for 150 DraftKings points (3x) = 10.6 + (salary * 0.00116)

WR cash game target score for 120 FanDuel points (2x) =  6.1 + (salary * 0.00111)

For instance, at $9,000, Mike Evans' expectation was 21 points rather than 27 points in Week 10, 2016 on DraftKings.

Examples of WR Cash Game Target Score (for Lineup to Score 150 DraftKings/120 FanDuel Points)

DK Salary ($)

DK Cash Target

DK Value

FD Salary ($)

FD Cash Target Score

FD Value

























The data suggests a minimum-priced WR needs to score ~14 points on DraftKings and ~11 on FanDuel to hit value. For context, to score 14 DraftKings points or 11 FanDuel points, a WR has needed an average of ~8 targets and 5 catches.

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

Will a WR be an ideal play on a PPR format that emphasizes catches and yardage like DraftKings? Or a 0.5-PPR format that emphasizes TDs like FanDuel? Depends on the type of targets he gets.

DraftKings: Target Receptions and Don't Shy Away from Paying Up for Studs

Every week, you will inevitably have to decide whether to play or fade an expensive WR. Instances of a WR priced $8,000+ have occurred more at WR than every other position combined over the past two years. While WRs in the low-$8,000s have struggled, those priced in the mid-$8,000s and above have been consistent:

DraftKings Cash Game Target Score Consistency Rate (2015-16)
Salary ($) QB Cons % n (QB) RB Cons % n (RB) WR Cons % n (WR) 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 in a given game by 4for4.

Provided it has not been at the expense of a stud RB, paying up at WR has been a +EV move in DraftKings cash games.

WR hit cash value less than RB from the low-$4,000s to mid-$5,000s, so going RB over WR in the FLEX is a sound approach.

WRs needed almost a half-reception more on DraftKings (6.92) than on FanDuel (6.49) to hit value. To hit value at a salary below $5,000, a WR has needed an average of 5.8 receptions. But roughly 30% of WRs hit value without a TD, higher than on FanDuel. That means DraftKings scoring favors high-volume types that don't necessarily score many TDs. Think Jarvis Landry, Stefon Diggs, etc.

FanDuel: Target Red Zone Threats

Emphasizing red zone targets works well to maximize the floor of a FanDuel lineup. I know, I know. That may be counterintuitive since TDs have a lot of variance. But it's difficult for a WR to score enough FanDuel points without a trip to the paint.

For example, a WR would need 10 catches for 100 yards, or 7-115, to score 15 points without a TD. In fact, over the last four seasons, 80% of WRs to hit cash game value on FanDuel needed at least one TD.

WRs priced $9,000+ have failed to justify their cost at a comparable rate to QBs and RBs in the same range. Instead, it's been the mid-$7,000-to-high-$8,000 range that's been the best pocket of WR value.

FanDuel Cash Game 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 below 9.0 points, and TEs projected below 7.75 points in a given game by 4for4. 

A salary of $7,500 has been a crossroads of sorts for WR. A sharp increase in consistency occurs above that mark, but a sharp decrease occurs below it.

Salary algorithms consider recent performance, and that's the effect of TD-dependent scoring. WRs may endure TD droughts, but don't drop below the mid-$7,000s before regression causes a correction. At the same time, TD luck is unsustainable for WRs who belonged in the $6,000s to begin with. Again, here's a situation in which you don't want to overreact to recent production over a few games. But as the sample size of games begins to mount, you want to start to take it more serious.

2. Leverage Vegas Implied Team Totals to Increase Consistency

In poor game script, WRs tend to get opportunities at the expense of runners. And of course, fantasy scoring rewards receivers more than passers. That's why, more than any other position, wide receivers can flourish in poor game script.

Thus, WR fantasy production is not changed much whether his team is the favorite or the underdog. WR scoring and Vegas odds have a less pronounced relationship than other positions:

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

WR scoring and implied points has somewhat of a tenuous relationship. Still, the data reveals three key takeaways about wide receiver consistency:

An implied team total below 22 has been where consistency has fallen off a cliff. I'm inclined to go with this benchmark because quarterback consistency also has a sharp dip at 22.

Consistency dipped on DraftKings at 28–30 implied points and FanDuel at 27–30. This dynamic is likely due to implied total being a variable in salary algorithms. It suggests paying up at WR for an extra implied point or two could end up being a trap at times.

Once an implied team total has cracked 30, there is a massive rise in consistency. Vegas doesn't project a team for 30+ often, but when it does, you should treat it as a wide receiver cheat code.

3. Analyze Individual Matchup, Not Fantasy Points Allowed 

Fantasy points allowed contains noise—especially when not adjusted for strength of schedule. Even so, it's still worthwhile to be aware of since it influences the decision making of many DFS players. Turns out you would have been best off targeting a defense with a mediocre ranking than a poor ranking.

WR Cash Game Target Score Consistency vs. Defense WR Fantasy Points Allowed Ranking Coming Into Game
WR DK PA Rk (Def vs. WR) Tot (Wk 2+) Wk 5+ Wk 9+ Wk 13+ WR FD PA Rk (Def vs. WR) Tot (Week 2+) Week 5+ Week 9+ Week 13+
1-5 22.2% 22.8% 24.7% 23.3% 1-5 28.2% 28.6% 30.3% 27.8%
6-10 27.0% 27.2% 25.8% 23.3% 6-10 30.9% 32.4% 33.9% 36.3%
11-15 29.5% 28.0% 28.1% 27.4% 11-15 29.0% 28.5% 28.4% 24.3%
16-20 28.7% 29.7% 29.0% 28.4% 16-20 36.0% 35.9% 35.8% 35.9%
21-25 27.1% 27.1% 26.9% 22.7% 21-25 32.9% 31.2% 33.9% 33.1%
26-30 28.4% 28.2% 27.4% 25.9% 26-30 33.8% 35.2% 34.3% 30.5%
31-32 24.2% 23.6% 21.7% 23.5% 31-32 34.4% 33.8% 30.3% 28.6%

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

A WR who straight-up flops in what looked like a great matchup on paper has no doubt prompted many a tilt. The data above shows why. Consistency is not guaranteed from a great on-paper matchup any more than it is from a so-so one. Raw fantasy points allowed data shows top-five defenses are not to tangle with. Besides that, it does not provide an edge. Strength of schedule has a major impact—using schedule-adjusted fantasy points is crucial.

Wide receiver matchups are complex. Another way to gain an edge is drilling down to individual matchups. Last season, 14 of 32 teams had a gap of at least 10 between their ranking versus No. 1 wide receivers and and No. 2 wide receivers, according to Football Outsiders' DVOA. Being keen on if a defense is vulnerable against No. 2s or slot receivers is key—those players often carry lower salaries and ownership in DFS.

Looking to optimize your cash game lineups by projected floor and expert picks/analysis? Subscribe to 4for4 now!

3 Strategies for Picking Wide Receivers 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.

You need to have the nuts at WR if you don't want to end up drawing dead in a GPP. In a typical first-place lineup, WRs score the most points and have the most correlation with other players.

There was nothing fancy about how first-place lineups have went about locking in upside at WR—they simply paid up more often than not. Spending at WR was more balanced in the FanDuel lineups. On DraftKings, lineups tended towards a stars-and-scrubs approach favoring two studs, which makes sense given the position's increased upside due to PPR scoring.

Average Salary & Score by Lineup Slot, First-place DraftKings Millionaire Maker & FanDuel Sunday Million GPPs (2015-16)

Dk Pos

Dk Sal ($)

DK Sal Rk

Avg DK Pt

DK Pt Rk

FD Pos

FD Sal ($)

FD Sal Rk

Avg FD Pts

FD Pts Rk



























































































In salary column: WR1, WR2, etc. determined by relative price of all WRs in lineup. In points column: WR1, WR2, etc. determined by relative score among WRs in lineup. (These are not necessarily always the same player.)

What is a good benchmark for wide receiver upside? One or more WRs scored 30+ in ~90% of the Millionaire Maker first-place lineups. At least one WR hit 25+ in 80% of the Sunday Million lineups. Two or more WRs hit those benchmarks in over half of each site's first-place lineups.

Jordy Nelson was in the first-place Sunday Million lineup a staggering six times in 2016. Over one-third of WRs to appear in either site's first-place lineup in a given week did so again later that season. Over 40% of WRs to hit either benchmark in a given season have repeated in the same season at least once.

1. Exploit Volatility with Red Zone Targets and Deep Targets

How did Jordy end up in so many first-place lineups? He was the only player in the NFL to have more than 25 red zone targets and 15 inside-the-10 targets. League-wide scarcity of close-proximity targets for any one receiver results in variance. That variance has an effect on both volume and efficiency. This can lead to down weeks, and oftentimes a depressed salary. Exploit this by targeting receivers who get a large share of targets in scoring position.

Deep targets are more common1 than red zone targets. Both are volatile due to a sub-50% average completion rate. Some of the deep-ball WRs that made it into 2016's first-place lineups include J.J. Nelson, Sammie Coates, Travis Benjamin, Mike Wallace, and DeSean Jackson.

Deep targets are more common than red zone targets. But they're also more difficult to execute. So you can get a wide receiver who gets deep target volume at a lower salary than one who gets red zone target volume.

Make sure that there's not a mismatch from a pass-rushing standpoint in the given game. This would will fail to afford the quarterback time to look deep.

2. Use a Chalk Play and a Contrarian Play

As far as ownership, first-place lineups have ridden the barbell approach to victory. They combined a highly owned player at the position with one that's low owned:  

Average Highest Owned-Lowest Owned WR, First-place DraftKings Millionaire Maker & FanDuel Sunday Million GPPs (2015-16)
Site/GPP WR1 WR2 WR3 WR4 Avg

DraftKings Millionaire Maker

26.0% 13.0% 6.7% 5.3% 12.8%
FanDuel Sunday Million 22.0% 11.3% 4.6%   12.6%

WR1 determined by most expensive WR in lineup, WR2 determined by second-most expensive WR in lineup, and so on.

You want to make sure your lineup has differentiation—enough to take down the grand prize. You could go about this by classifying potential WR plays as chalk, contrarian, and other, then making sure you use at least one contrarian play, as well as (usually) no more than one chalk play.

  • Chalk WR prototype: The majority of highly owned WRs in the first-place lineups have a salary of $8,000+. Many times, it is not possible to get enough upside without paying up for a stud. At others, it is unnecessary not to given the value available at other positions. A more subtle takeaway is that highly owned inexpensive WRs make for good fades.
  • Contrarian WR prototype: Roughly 70% of first-place lineups used a WR with under 6% ownership. These contrarian plays were typically inexpensive, with an average salary of $6,608 on FanDuel and $3,894 on DraftKings. A good contrarian play will marry low projected ownership with other favorable situations. I already mentioned high target volume; there's also efficient production sustained over a decent sample size, favorable cornerback matchups, deep targets, red zone usage, perceived difficult on-paper matchup, and previous high-upside performances, among other things.

3. Utilize Correlation by Stacking with Teammates and Opponents

Over three-quarters of first-place lineups paired a WR with a teammate (usually the QB). Diving deeper reveals three key strategies first-place lineups use when stacking WR:

  • Limit stacking with studs: An expensive WR is often tied to a QB that too is pricey. That can offset some of the benefits that correlating two players in a lineup provides. Of WRs priced $8,000+, only 6-of-30 on FanDuel and 3-of-23 on DraftKings ended up stacked with their QB.

  • Stack with the opposing offense: Opposing passing games are correlated. Roughly one-quarter of each site's first-place lineups had a WR with an opposing player.

  • Stack with a RB instead of a second WR: Let's say an offense has a big day. A production split between its top runner and receiver is most likely. Pairing WRs on the same team was in only 14% and 6% of FanDuel and DraftKings lineups, respectively. Meanwhile, 37% of the DraftKings lineups and 22% of those on FanDuel paired a WR with RB on the same team.

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WR Daily Fantasy Playbook (Recap)

WR projection strategy:

  • Weight overall production (not just targets) as sample size increases.

  • Account for the factors that impact WR production: target market share, red zone targets, deep targets, cornerback matchup, defensive scheme, injury.

WR cash game strategy:

  • Tailor your selections to site scoring format (and pricing).

    • DraftKings: Target receptions and don't shy away from paying up for studs.

    • FanDuel: Target red zone threats.

  • Leverage Vegas implied team totals to increase consistency.

  • Analyze individual matchup, not fantasy points allowed.

WR tournament/GPP strategy:

  • Exploit volatility with red zone and deep targets.

  • Use a chalk play and a contrarian play.

  • Utilize correlation by stacking with teammates and opponents.

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1. Mike Evans led the league with 59 in 2016. (back

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