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Welcome to this new, weekly Draftkings feature on Footballguys. As the title suggests, the goal of this feature is to predict how DFS professionals will tweak their player exposures -- in either a bullish (or bearish) direction -- for the Sunday Main slate on Draftkings.
But who are the DFS professionals?
The pro roster percentages you will see in the tables below are based on a statistical algorithm that attempted to differentiate elite DFS players on Draftkings from the rest of the population. Based on a multitude of factors, this algorithm identified 205 "professionals" who play in low-to-mid stakes Guaranteed Prize Pool (GPP) tournaments. The primary characteristics that differentiated them were their percentage of max entry and their median top finish in a contest. Specifically, the vast majority of pros enter at least 90% of the entry maximum in a given GPP. If the contest allows for 150 lineups, they enter at least 135; if it allows for 20 lineups, they enter at least 18; etc. In addition, the vast majority of pros have their highest-finishing lineup end up in the Top 4% of entries in a given context.
In short, a low-to-mid stakes Draftkings GPP pro appears to be a player who plays the percentages more optimally than the rest. They apply a ton of volume, what's called "mass multi-entry" in a DFS context, and diversify their lineups enough to make it more likely than not that at least one entry finishes near the top of the standings -- where payouts are highest.
OK, but how can one possibly project the mass multi-entry roster percentages pros use to effect this profitable strategy?
Well, it turns out that, based on an analysis of historical contest entry data, pros reliably increase or decrease their exposures to players according to a small number of factors. The effects of these factors differ across positions, but a surprisingly short list gets you most of the way there:
- Steve Buzzard's projected roster percentages. The higher Buzzard's projection, the higher a pro roster percentage will be for a given player.
- This author's value probabilities. This system uses salaries and Footballguys' point projections to calculate the likelihood that players achieve the 4x GPP value threshold (e.g., a $4,000 player must score 16 points to achieve value). The higher the value probability, the higher a pro roster percentage will be for a given player.
- Projected roster percentage for the opponent's defense. The lower Buzzard's projection for a defense, the higher a pro roster percentage will be for a given player facing that defense.
- For quarterbacks and running backs, projected roster percentage for the same team's wide receivers. The higher Buzzard's projection for a wide receiver, the higher a pro roster percentage will be for his quarterback. The opposite is true for running backs.
- For defenses, projected roster percentage for the opponent's quarterback. The lower Buzzard's projection for a quarterback, the higher a pro roster percentage will be for a given defense facing that quarterback.
If one were to step back and view these factors affecting pro roster percentages from 30,000 feet, one will notice the following: Pros gain their edge by exploiting inefficiencies in the interactions between positions. For example, they see a quarterback and their opposing defense both projected for a low roster percentage and realize that can't be correct. If the defense does well, the quarterback won't; and vice versa. One should be highly rostered and the other not. This observation is intuitive and not reflective of some wizardly wisdom. Rather, what sets the pros apart is that, by virtue of their mass multi-entry strategy, they're able to finely tune their exposures to the quarterback and defense in this example.
So with the methods of this madness explained, it's time to try to project the pros, one position at a time.
quarterbacks
Below are the projections for quarterbacks. The "Overall" column is Steve Buzzard's projected roster percentage. The "Pros" column is the projection for professional, low-to-mid stakes GPP players on Draftkings. Finally, the "Diff Ratio" column is the difference between the "Pros" column and the "Overall" column, divided by the "Overall" column. It represents the proportional increase (or decrease) in pro roster percentage based on one or more factors listed in the introduction. So, for instance, Alex Smith's "+95.8%" means that various factors result in his pro roster percentage nearly doubling above and beyond Buzzard's projection.
Quarterback | Team | Salary | Overall | Pros | Diff Ratio |
Ryan Fitzpatrick | TB | 5000 | 1.6% | 3.3% | +108.0% |
Alex Smith | WAS | 5600 | 1.7% | 3.3% | +95.8% |
Sam Bradford | ARI | 5200 | 1.8% | 3.4% | +88.5% |
Joe Flacco | BAL | 4900 | 2.1% | 3.8% | +79.5% |
Case Keenum | DEN | 5100 | 2.4% | 4.0% | +66.1% |
Ryan Tannehill | MIA | 5300 | 2.1% | 3.4% | +63.3% |
Blake Bortles | JAX | 5600 | 3.8% | 5.7% | +50.3% |
Andy Dalton | CIN | 5800 | 3.2% | 4.7% | +48.3% |
Jimmy Garoppolo | SF | 5700 | 1.6% | 2.3% | +44.6% |
Dak Prescott | DAL | 5500 | 2.6% | 3.1% | +17.4% |
Philip Rivers | LAC | 6400 | 9.8% | 10.6% | +7.9% |
Russell Wilson | SEA | 6200 | 2.8% | 2.8% | +1.7% |
Tyrod Taylor | CLE | 5400 | 3.8% | 3.9% | +1.4% |
Ben Roethlisberger | PIT | 6600 | 6.3% | 6.3% | +0.7% |
Patrick Mahomes II II | KC | 6000 | 3.0% | 2.9% | -3.1% |
Marcus Mariota | TEN | 6300 | 2.7% | 2.6% | -4.2% |
Kirk Cousins | MIN | 6500 | 6.9% | 6.5% | -5.3% |
Drew Brees | NO | 6800 | 10.8% | 9.8% | -9.6% |
Andrew Luck | IND | 6100 | 5.0% | 4.3% | -13.9% |
Tom Brady | NE | 7200 | 11.7% | 9.8% | -16.5% |
Cam Newton | CAR | 6900 | 5.1% | 3.5% | -30.8% |
Deshaun Watson | HOU | 6700 | 7.7% | 4.9% | -35.9% |
Alex Smith ($5,600, 1.7% Overall Roster Percentage, 3.3% Pro Roster Percentage)
Based on his salary and Draftkings point projection, Smith's probability of achieving 4x value is 27.5%, which ranks 6th of 26 quarterbacks in the Sunday Main slate. According to Steve Buzzard, Smith's opponent, the Arizona Cardinals defense, is only expected to be rostered in 1.7% of tournament lineups, which ranks 17th out of 24 defenses. Despite Smith's wide receivers only having an aggregate 3.7% roster projection, the aforementioned indicators nevertheless translate to Draftkings pros having nearly twice as much exposure to Smith as the overall public.
Philip rIVERS ($6,400, 9.8%, 10.6%)
Rivers' probability of achieving 4x value is 21.4%, which ranks 11th in the Sunday Main slate. The defense he's facing, Kansas City, is projected to be in only 1.0% of tournament lineups, which ranks 20th. Furthermore, Rivers' receivers rank second in aggregate projected roster percentage (28.0%), which ranks second behind only Pittsburgh's wide receiver corps (30.8%).
DeShaun Watson ($6,700, 7.7%, 4.9%)
Although Watson's wide receivers having a sixth-ranked 18.1% combined roster projection, Draftkings pros are likely to take a bearish position on him in Week 1. Watson's probability of achieving 4x value is a 19th-ranked 17.2%. In addition, the Patriots defense that he's facing ranks fourth in projected roster percentage.
cAM nEWTON ($6,900, 5.1%, 3.5%)
The only quarterbacks who rank lower than Newton in terms of 4x value probability are Week 1 backups Josh Allen and Josh Rosen. Meanwhile, only five quarterbacks in the Sunday Main slate rank lower than Newton with respect to the projected roster percentages for his wide receivers.
Running Backs
Running Back | Team | Salary | Overall | Pros | Diff Ratio |
Devontae Booker | DEN | 4600 | 0.7% | 3.2% | +359.9% |
Mike Gillislee | NO | 3400 | 0.9% | 3.5% | +291.6% |
Marlon Mack | IND | 4800 | 1.0% | 3.0% | +201.4% |
Chris Carson | SEA | 4500 | 1.6% | 4.0% | +152.1% |
Latavius Murray | MIN | 4800 | 1.2% | 3.0% | +149.6% |
Chris Thompson | WAS | 4700 | 1.7% | 4.2% | +144.6% |
Sony Michel | NE | 5100 | 1.2% | 2.8% | +136.8% |
Dion Lewis | TEN | 4900 | 2.0% | 4.2% | +110.3% |
Matt Breida | SF | 4600 | 2.1% | 4.2% | +101.5% |
Royce Freeman | DEN | 4500 | 3.1% | 5.7% | +84.3% |
Kalen Ballage | MIA | 3500 | 1.8% | 3.3% | +82.7% |
Carlos Hyde | CLE | 4500 | 2.8% | 4.9% | +76.4% |
Derrick Henry | TEN | 5400 | 2.4% | 4.0% | +67.8% |
James White | NE | 4000 | 3.9% | 6.3% | +61.8% |
LeSean McCoy | BUF | 6000 | 2.9% | 4.4% | +52.0% |
Jordan Wilkins | IND | 3700 | 3.5% | 5.3% | +50.6% |
Peyton Barber | TB | 4100 | 4.0% | 5.8% | +44.2% |
Lamar Miller | HOU | 5200 | 4.5% | 5.9% | +32.1% |
Adrian Peterson | WAS | 4700 | 3.6% | 4.7% | +31.6% |
Rex Burkhead | NE | 4200 | 9.7% | 11.5% | +18.4% |
Alvin Kamara | NO | 8500 | 23.2% | 27.2% | +17.2% |
Saquon Barkley | NYG | 6700 | 5.9% | 6.3% | +6.3% |
Alex Collins | BAL | 5600 | 11.5% | 11.7% | +1.6% |
Christian McCaffrey | CAR | 6400 | 13.9% | 14.0% | +0.5% |
Kenyan Drake | MIA | 5900 | 5.8% | 5.7% | -0.9% |
Kareem Hunt | KC | 6900 | 5.9% | 5.8% | -2.3% |
Dalvin Cook | MIN | 6200 | 5.6% | 5.3% | -4.8% |
Melvin Gordon | LAC | 6800 | 15.1% | 14.0% | -7.6% |
Joe Mixon | CIN | 6100 | 6.4% | 5.7% | -10.8% |
Ezekiel Elliott | DAL | 7700 | 10.0% | 8.8% | -12.0% |
David Johnson | ARI | 8800 | 12.7% | 11.2% | -12.1% |
Leonard Fournette | JAX | 7100 | 9.5% | 7.2% | -24.2% |
Ronald Jones II II | TB | 4900 | 8.3% | 6.0% | -27.5% |
Chris Thompson ($4,700, 1.7% Overall, 4.2% Pros)
Thompson's 11.4% probability of achieving 4x value may only rank 18th (of 83) among running backs in the Sunday Main slate, but Buzzard projects his opponent's defense to be rostered in only 1.7% of lineups. Even more importantly, Washington's wide receivers are only projected to be on 3.7% rosters in the aggregate. In other words, Draftkings pros are likely to exploit the fact that someone has to catch passes against an underwhelming Cardinals defense.
mIKE gILLISLEE ($3,400, 0.9% Overall, 3.5% Pros)
Similarly, Gillislee's 12.1% value probability ranks 16th this week, but the Buccaneers defense is one of only four with an expected roster percentage of zero according to Buzzard. To boot, it's worth noting that these stats provide a welcome complement to the more subjective analysis of Sean Payton erring towards limiting Alvin Kamara's workload in the running game, especially around the goal line -- which New Orleans figures to be in proximity of frequently.
Leonard Fournette ($7,100, 9.5% Overall, 7.2% Pros)
Although his opponent's defense, the New York Giants, has a nonexistent projected roster percentage, which bodes well for Fournette, the third-ranked 27.2% aggregate roster projection for Jacksonville's wide receivers bodes ill. If Keelan Cole and company perform as expected, it will be difficult to Fournette to earn enough points per reception to justify his salary in Draftkings tournaments.
Melvin Gordon ($6,800, 15.1% Overall, 14.0% Pros)
Similarly, at 28.0% aggregate ownership, San Diego's wide receivers rank second in aggregate roster percentage according to Buzzard. This is enough to offset Gordon's more-favorable stats, which include the sixth-highest value probability among running backs (19.6%) and the fifth-lowest opponent roster percentage projection (1.0%).
Wide Receivers
Wide Receiver | Team | Salary | Overall | Pros | Diff Ratio |
Laquon Treadwell | MIN | 3400 | 1.3% | 3.5% | +169.5% |
D.J. Moore | CAR | 4100 | 1.2% | 3.2% | +163.5% |
Danny Amendola | MIA | 4200 | 2.0% | 5.2% | +159.5% |
Sterling Shepard | NYG | 4500 | 1.5% | 3.5% | +130.8% |
Tyrell Williams | LAC | 4200 | 1.6% | 3.6% | +127.4% |
Donte Moncrief | JAX | 4000 | 1.8% | 4.1% | +127.0% |
Ryan Grant | IND | 3900 | 1.4% | 3.1% | +121.1% |
Pierre Garcon | SF | 4900 | 1.4% | 2.9% | +110.0% |
Sammy Watkins | KC | 5100 | 1.4% | 2.9% | +106.3% |
Michael Gallup | DAL | 4000 | 1.4% | 2.9% | +106.2% |
John Brown | BAL | 3700 | 2.9% | 5.9% | +103.5% |
DeSean Jackson | TB | 4600 | 1.3% | 2.6% | +102.8% |
Phillip Dorsett | NE | 3700 | 2.1% | 4.1% | +97.0% |
Tyler Lockett | SEA | 4300 | 2.2% | 4.2% | +90.7% |
Marquise Goodwin | SF | 4600 | 2.3% | 4.2% | +81.6% |
Allen Hurns | DAL | 4700 | 1.7% | 3.1% | +81.4% |
Doug Baldwin | SEA | 6200 | 1.7% | 3.0% | +76.0% |
Cameron Meredith | NO | 4400 | 1.8% | 3.0% | +66.5% |
Josh Gordon | CLE | 5800 | 1.5% | 2.5% | +65.8% |
Rishard Matthews | TEN | 4800 | 1.9% | 3.1% | +63.7% |
Dede Westbrook | JAX | 3900 | 2.9% | 4.4% | +52.7% |
Mike Williams | LAC | 3900 | 3.4% | 5.1% | +50.0% |
Keelan Cole | JAX | 3800 | 22.5% | 32.4% | +44.0% |
Kenny Stills | MIA | 4700 | 5.3% | 7.3% | +38.1% |
Kelvin Benjamin | BUF | 5000 | 1.7% | 2.2% | +31.7% |
Chris Godwin | TB | 4100 | 2.5% | 3.1% | +25.4% |
Jamison Crowder | WAS | 5000 | 3.7% | 4.4% | +19.4% |
Keenan Allen | LAC | 7500 | 23.0% | 26.1% | +13.4% |
Demaryius Thomas | DEN | 5700 | 4.3% | 4.9% | +13.0% |
Devin Funchess | CAR | 5200 | 3.4% | 3.8% | +11.4% |
John Ross | CIN | 3900 | 5.6% | 6.0% | +7.7% |
Antonio Brown | PIT | 8600 | 20.3% | 21.6% | +6.3% |
Michael Crabtree | BAL | 5400 | 5.0% | 5.1% | +1.2% |
Corey Davis | TEN | 5600 | 3.8% | 3.8% | -0.1% |
A.J. Green | CIN | 7300 | 12.8% | 11.4% | -10.6% |
T.Y. Hilton | IND | 6800 | 5.8% | 5.1% | -12.0% |
Odell Beckham Jr/td> | NYG | 7000 | 6.4% | 5.6% | -12.9% |
Jarvis Landry | CLE | 5500 | 6.8% | 5.9% | -13.6% |
Emmanuel Sanders | DEN | 5000 | 7.9% | 6.8% | -13.7% |
Chris Hogan | NE | 6100 | 15.2% | 13.0% | -14.7% |
Stefon Diggs | MIN | 6300 | 10.9% | 9.3% | -15.0% |
Michael Thomas | NO | 7800 | 15.0% | 12.7% | -15.2% |
Will Fuller | HOU | 5100 | 4.9% | 4.2% | -15.2% |
JuJu Smith-Schuster | PIT | 5900 | 10.5% | 8.8% | -15.7% |
Tyreek Hill | KC | 6500 | 7.0% | 5.7% | -17.9% |
Mike Evans | TB | 6700 | 4.9% | 4.0% | -19.2% |
Larry Fitzgerald | ARI | 6600 | 10.5% | 8.5% | -19.4% |
Adam Thielen | MIN | 6900 | 10.2% | 8.1% | -21.0% |
DeAndre Hopkins | HOU | 8300 | 13.2% | 8.7% | -33.9% |
Keelan Cole ($3,800, 22.5% Overall, 32.4% Pros)
At 26.9%, Cole has the second-highest probability of achieving 4x value this week. And with Buzzard projecting the New York Giants defense to be on zero percent of rosters (with inentional rounding), Draftkings pros are likely to take a long position on Cole.
dANNY aMENDOLA ($4,200, 2.0% Overall, 5.2% Pros)
Amendola's 25.5% value probability ranks fourth in the Sunday Main slate, and the Titans defense is projected to appear in only 1.9% of GPP lineups according to Buzzard. If you wish, one can add in the narrative of playing at home while occupying a position that's averaged nearly 10 targets per game under Adam Gase.
DeAndre Hopkins ($8,300, 13.2% Overall, 8.7% Pros)
In contrast, Hopkins' 7.4% value probability ranks 46th among wide receivers, and his opponent's defense is projected to be the third-most rostered on Sunday (8.7%).
Mike Evans ($6,700, 4.9% Overall, 4.0% Pros)
Subjective considerations already render Evans a likely fade in tournaments. That said, the objective numbers agree, as his value probability is even lower than Hopkins' (5.9%), and the Saints defense -- playing at home, to boot -- is projected to be the seventh-highest rostered (6.0%).
Tight Ends
Tight End | Team | Salary | Overall | Pros | Diff Ratio |
Cameron Brate | TB | 3000 | 1.2% | 3.3% | +177.3% |
Ricky Seals-Jones | ARI | 3000 | 1.5% | 4.0% | +169.9% |
Ben Watson | NO | 3100 | 2.4% | 4.4% | +81.6% |
Eric Ebron | IND | 3300 | 2.3% | 3.8% | +63.7% |
George Kittle | SF | 3300 | 2.3% | 3.6% | +56.9% |
Tyler Eifert | CIN | 3400 | 3.8% | 5.1% | +34.3% |
Rob Gronkowski | NE | 6900 | 20.0% | 24.9% | +24.7% |
David Njoku | CLE | 3400 | 4.1% | 4.7% | +14.5% |
Jack Doyle | IND | 3600 | 13.1% | 14.8% | +12.7% |
Jordan Reed | WAS | 4000 | 10.1% | 10.8% | +7.0% |
Evan Engram | NYG | 4700 | 3.4% | 3.5% | +3.9% |
Vance McDonald | PIT | 3200 | 2.9% | 3.0% | +3.2% |
Charles Clay | BUF | 3500 | 2.4% | 2.4% | +0.9% |
Kyle Rudolph | MIN | 4500 | 5.3% | 5.1% | -3.0% |
Austin Seferian-Jenkins | JAX | 3200 | 4.0% | 3.6% | -9.5% |
Travis Kelce | KC | 6400 | 7.2% | 6.2% | -14.5% |
Delanie Walker | TEN | 4900 | 6.7% | 5.3% | -21.5% |
Greg Olsen | CAR | 5400 | 5.2% | 4.1% | -21.6% |
Ricky Seals-Jones ($3,000, 1.5% Overall, 4.0% Pros)
At 1.7%, Washington's defense has the eighth-lowest projected roster percentage of the Sunday Main slate. And at 22.9%, Seals-Jones himself ranks third in likelihood of achieving 4x value.
Delanie Walker ($4,900, 6.7% Overall, 5.3% Pros)
In contrast, the much higher-priced Walker has both a lower value probability (10.1%; ranked 21st), and a much higher projected roster percentage for his opponent's defense (4.1%; ranked ninth).
Defenses
Defense | Team | Salary | Overall | Pros | Diff Ratio |
Kansas City Chiefs | KC | 2300 | 1.0% | 2.5% | +151.9% |
Indianapolis Colts | IND | 2400 | 1.5% | 3.3% | +117.0% |
Arizona Cardinals | ARI | 2500 | 1.7% | 3.5% | +108.7% |
Buffalo Bills | BUF | 3000 | 1.5% | 3.0% | +100.7% |
Tennessee Titans | TEN | 2900 | 1.9% | 3.4% | +81.0% |
Baltimore Ravens | BAL | 3800 | 23.1% | 38.8% | +67.9% |
Washington Redskins | WAS | 2800 | 2.1% | 3.5% | +65.9% |
Carolina Panthers | CAR | 3200 | 2.0% | 3.2% | +59.8% |
Dallas Cowboys | DAL | 2300 | 2.6% | 3.7% | +42.7% |
Cincinnati Bengals | CIN | 2700 | 2.2% | 3.0% | +37.5% |
Cleveland Browns | CLE | 2000 | 2.7% | 3.5% | +30.7% |
Seattle Seahawks | SEA | 3100 | 2.8% | 3.6% | +27.0% |
Miami Dolphins | MIA | 2400 | 4.1% | 4.6% | +12.9% |
Denver Broncos | DEN | 3300 | 4.7% | 4.5% | -3.4% |
Los Angeles Chargers | LAC | 2800 | 6.2% | 5.7% | -8.4% |
Jacksonville Jaguars | JAX | 3700 | 9.8% | 8.8% | -9.9% |
New Orleans Saints | NO | 3600 | 6.0% | 5.3% | -12.2% |
Minnesota Vikings | MIN | 3500 | 6.5% | 5.7% | -13.1% |
New England Patriots | NE | 2400 | 8.7% | 7.4% | -14.5% |
Pittsburgh Steelers | PIT | 3400 | 6.4% | 5.2% | -19.2% |
Baltimore Ravens ($3,800, 23.1% Overall, 38.8% Pros)
Baltimore's defense checks all the boxes. They're a heavy home favorite, so their likelihood of achieving 4x value is still 20.5% despite their exorbitant salary. Most importantly, however, is the fact that Buzzard projects Nathan Peterman to be persona non grata in GPP lineups.
Pittsburgh Steelers ($3,400, 6.4% Overall, 5.2% Pros)
In contrast, the similarly priced Steelers defense has a 16.4% value probability, which ranks second-lowest in the Sunday Main slate; not despite their salary but because of it. And surprisingly perhaps, Tyrod Taylor ranks in the middle of the pack in terms of projected roster percentage, which furthers suppresses the likelihood that pros will roster Pittsburgh at a level commensurate with their salary and perceived matchup.