Welcome back to our FantasyAces feature article, wherein we identify value plays in both cash games and tournaments. The process we use starts with the statistical method described here, which results in a percentage that represents the likelihood a given player will achieve value based on his salary, his projection, and historical variation in scoring at his position. From there, we take a look at statistics related to his individual matchup, as well as any other situational factors that might affect his value likelihood (e.g., injuries, coaching tendencies, game scripts, ownership rates, etc.). This combination of stats and context allows us to narrow things down to a select group of players worth fully recommending.
Note: The value probability tables will be published on Thursday. Commentary based on the situational factors described above will be added on Friday.
QUARTERBACKS
Below are the quarterbacks with the highest (and lowest) probabilities of achieving value in cash games and GPPs:
MOST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
Dak Prescott | DAL | 6200 | 21.0 | 65.8% | Russell Wilson | SEA | 6500 | 22.5 | 27.3% |
Russell Wilson | SEA | 6500 | 20.2 | 54.7% | Dak Prescott | DAL | 6200 | 21.1 | 26.1% |
Carson Palmer | ARI | 6800 | 21.1 | 54.4% | Carson Palmer | ARI | 6800 | 23.0 | 23.4% |
Marcus Mariota | TEN | 6150 | 19.0 | 53.4% | Marcus Mariota | TEN | 6150 | 20.1 | 21.8% |
Aaron Rodgers | GB | 7850 | 23.8 | 51.8% | Blake Bortles | JAX | 6000 | 19.4 | 21.3% |
Jay Cutler | CHI | 6200 | 18.9 | 51.7% | Jay Cutler | CHI | 6200 | 19.8 | 19.4% |
Alex Smith | KC | 6000 | 17.9 | 49.4% | Alex Smith | KC | 6000 | 19.0 | 19.4% |
LEAST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
Drew Brees | NO | 7600 | 19.8 | 30.1% | Drew Brees | NO | 7600 | 21.6 | 6.4% |
Brock Osweiler | HOU | 6200 | 15.7 | 30.9% | Brock Osweiler | HOU | 6200 | 16.5 | 7.6% |
Ryan Tannehill | MIA | 5700 | 15.0 | 35.5% | Kirk Cousins | WAS | 6550 | 18.5 | 9.2% |
Philip Rivers | SD | 6750 | 18.3 | 36.7% | Matt Ryan | ATL | 7300 | 21.8 | 10.0% |
Colin Kaepernick | SF | 6300 | 17.1 | 37.4% | Jameis Winston | TB | 6550 | 18.9 | 10.3% |
Kirk Cousins | WAS | 6550 | 17.8 | 37.5% | Philip Rivers | SD | 6750 | 19.8 | 10.7% |
Jameis Winston | TB | 6550 | 17.9 | 37.8% | Colin Kaepernick | SF | 6300 | 18.3 | 11.6% |
Among quarterbacks in the high-value side of the table, four have favorable matchups. The first is Carson Palmer. Although the 49ers are notorious at this point for their awful run defense, it turns out that they're also awful across quarterback-related stats: 24th in FantasyAces points allowed to opposing quarterbacks; 29th in overall defensive efficiency (per DVOA). Yes, David Johnson is the matchup focus of anyone and everyone, but running preserves a lead; passing builds it.
The second quarterback with a favorable matchup is Aaron Rodgers. His opponent, the Titans, rank 26th in efficiency on pass defense and 27th in overall defensive efficiency. The third is Jay Cutler, who faces a Buccaneers defense that ranks 31st in points allowed to quarterbacks, 20th in pass defense efficiency, and 20th in overall defense efficiency. And finally, the fourth value quarterback with a favorable matchup is Alex Smith: Carolina ranks 26th in points allowed to quarterbacks and 23rd in pass defense efficiency.
With respect to game theory among these four, Cutler absolutely can't be used in cash games given his fourth-ranked projected ownership rate ...and the fact that he's uber-consistently "meh" Jay Cutler. The other three offer more flexibility. Smith is also "meh", embodying the high-floor, low-ceiling, cash game-only quarterback, but he has a projected ownership rate low enough to use in tournaments. Palmer and Rodgers are the near-converses of Smith: high floor and high ceiling, but low ownership, which means they're the two value options I'd use in tournaments and sprinkle into my cash game lineups.
Running Backs
Below are the running backs with the highest (and lowest) probabilities of achieving value in cash games and GPPs:
MOST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
David Johnson | ARI | 6400 | 24.0 | 64.6% | David Johnson | ARI | 6400 | 25.7 | 50.3% |
Melvin Gordon | SD | 5900 | 19.7 | 57.2% | LeVeon Bell | PIT | 6150 | 21.5 | 41.0% |
LeVeon Bell | PIT | 6150 | 19.8 | 54.7% | Melvin Gordon | SD | 5900 | 19.9 | 38.7% |
Devonta Freeman | ATL | 5100 | 15.7 | 51.5% | Jordan Howard | CHI | 5000 | 16.1 | 35.7% |
Jordan Howard | CHI | 5000 | 14.7 | 48.6% | Devonta Freeman | ATL | 5100 | 15.9 | 33.7% |
Ezekiel Elliott | DAL | 6200 | 18.0 | 47.6% | Ezekiel Elliott | DAL | 6200 | 19.2 | 33.3% |
Darren Sproles | PHI | 4650 | 12.7 | 43.8% | Darren Sproles | PHI | 4650 | 14.2 | 32.4% |
DeMarco Murray | TEN | 5950 | 15.7 | 41.4% | DuJuan Harris | SF | 3500 | 10.6 | 31.9% |
Matt Forte | NYJ | 5500 | 14.0 | 38.9% | DeMarco Murray | TEN | 5950 | 16.8 | 27.8% |
Mark Ingram | NO | 4950 | 12.4 | 38.0% | Todd Gurley | LA | 4850 | 13.5 | 27.0% |
LEAST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
Ronnie Hillman | MIN | 4100 | 4.7 | 5.2% | Jerick McKinnon | MIN | 4100 | 5.6 | 3.5% |
Benny Cunningham | LA | 3500 | 4.1 | 5.8% | Ronnie Hillman | MIN | 4100 | 6.0 | 4.5% |
Carlos Hyde | SF | 4800 | 5.7 | 5.9% | Ryan Mathews | PHI | 4200 | 6.7 | 6.0% |
Peyton Barber | TB | 4500 | 5.7 | 7.4% | Benny Cunningham | LA | 3500 | 5.7 | 6.5% |
Damien Williams | MIA | 3700 | 4.8 | 7.8% | Peyton Barber | TB | 4500 | 8.1 | 8.9% |
Jerick McKinnon | MIN | 4100 | 5.4 | 8.0% | James White | NE | 4300 | 8.0 | 9.8% |
Ryan Mathews | PHI | 4200 | 5.5 | 8.2% | Christine Michael | SEA | 4700 | 9.3 | 11.7% |
James White | NE | 4300 | 6.0 | 9.6% | Tim Hightower | NO | 4550 | 9.1 | 12.1% |
Tim Hightower | NO | 4550 | 7.6 | 16.1% | Dion Lewis | NE | 3500 | 7.0 | 12.1% |
Christine Michael | SEA | 4700 | 8.5 | 19.6% | Jeremy Hill | CIN | 5000 | 10.0 | 12.1% |
David Johnson has an astronomical projected ownership percentage (i.e., around 60 percent), but a matchup against San Francisco's historically bad run defense means using him in tournaments as well as cash games -- as long as the rest of your tournament lineup is low-usage. For instance, here's a low-usage candidate to pair with Johnson: Mark Ingram. He's only expected to be in about 2 percent of tournament lineups. Furthermore, Denver ranks 25th in run defense efficiency (per DVOA) and 20th in FantasyAces points allowed to opposing running backs.
The remaining running backs in the top half of the table that have favorable statistical matchups are Jordan Howard and Darren Sproles, although their projected ownership rates (around 20 percent) imply that they're viable mainly in cash games. Howard faces a Tampa Bay defense that ranks 26th in points allowed to opposing running backs and 28th in pass defense efficiency on running back targets. Similarly, Sproles faces a Falcons defense that ranks 24th in points allowed and 26th in pass defense efficiency on running back targets.
Wide Receivers
Below are the wide receivers with the highest (and lowest) probabilities of achieving value in cash games and GPPs:
MOST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
Mike Evans | TB | 5900 | 18.1 | 51.6% | Tyreek Hill | KC | 3000 | 10.1 | 38.6% |
Tyreek Hill | KC | 3000 | 9.0 | 49.7% | Mike Evans | TB | 5900 | 19.5 | 37.4% |
Larry Fitzgerald | ARI | 5100 | 15.2 | 49.3% | Tyrell Williams | SD | 4250 | 13.6 | 35.3% |
Alshon Jeffery | CHI | 4850 | 13.6 | 45.2% | J.J. Nelson | ARI | 3750 | 11.5 | 32.7% |
J.J. Nelson | ARI | 3750 | 10.5 | 45.1% | Larry Fitzgerald | ARI | 5100 | 15.4 | 31.8% |
Tyrell Williams | SD | 4250 | 11.8 | 44.9% | Alshon Jeffery | CHI | 4850 | 13.8 | 28.3% |
Antonio Brown | PIT | 6200 | 17.1 | 44.4% | Antonio Brown | PIT | 6200 | 17.3 | 27.2% |
Demaryius Thomas | DEN | 5550 | 14.6 | 41.3% | Jordan Matthews | PHI | 4750 | 13.1 | 26.5% |
Stefon Diggs | MIN | 4750 | 12.4 | 40.7% | Demaryius Thomas | DEN | 5550 | 15.3 | 26.5% |
Jordan Matthews | PHI | 4750 | 12.2 | 39.8% | Jarvis Landry | MIA | 4800 | 13.2 | 26.4% |
Jarvis Landry | MIA | 4800 | 12.3 | 39.5% | Stefon Diggs | MIN | 4750 | 13.0 | 26.1% |
A.J. Green | CIN | 6250 | 15.6 | 37.6% | John Brown | ARI | 4500 | 12.3 | 26.0% |
Kelvin Benjamin | CAR | 4800 | 11.9 | 37.5% | Cole Beasley | DAL | 4550 | 12.4 | 25.9% |
Ty Montgomery | GB | 4800 | 11.9 | 37.1% | Dontrelle Inman | SD | 4150 | 11.3 | 25.8% |
Dez Bryant | DAL | 5000 | 12.3 | 36.8% | Randall Cobb | GB | 5100 | 13.8 | 25.5% |
LEAST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
Cordarrelle Patterson | MIN | 4200 | 7.1 | 16.8% | DeVante Parker | MIA | 4150 | 8.0 | 10.9% |
DeVante Parker | MIA | 4150 | 7.3 | 18.2% | Kendall Wright | TEN | 4150 | 8.1 | 11.3% |
Jermaine Kearse | SEA | 4100 | 7.2 | 18.5% | Cordarrelle Patterson | MIN | 4200 | 8.2 | 11.3% |
Tavon Austin | LA | 4200 | 7.5 | 18.8% | DeSean Jackson | WAS | 4300 | 8.6 | 12.1% |
DeSean Jackson | WAS | 4300 | 7.7 | 19.2% | Will Fuller | HOU | 4500 | 9.0 | 12.1% |
Quincy Enunwa | NYJ | 4500 | 8.1 | 19.2% | Quincy Enunwa | NYJ | 4500 | 9.0 | 12.1% |
Kendall Wright | TEN | 4150 | 7.8 | 21.5% | Eli Rogers | PIT | 4000 | 8.3 | 13.4% |
Will Fuller | HOU | 4500 | 8.5 | 21.7% | DeAndre Hopkins | HOU | 6000 | 12.7 | 14.2% |
Willie Snead | NO | 4550 | 8.7 | 22.3% | Tavon Austin | LA | 4200 | 9.1 | 15.1% |
Ted Ginn Jr | CAR | 3900 | 7.6 | 23.1% | Quinton Patton | SF | 3800 | 8.3 | 15.4% |
Pierre Garcon | WAS | 4200 | 8.2 | 23.2% | Allen Hurns | JAX | 4300 | 9.5 | 15.8% |
Adam Humphries | TB | 3800 | 7.4 | 23.3% | Pierre Garcon | WAS | 4200 | 9.3 | 15.9% |
Eli Rogers | PIT | 4000 | 8.0 | 24.4% | Michael Thomas | NO | 4900 | 11.1 | 16.9% |
John Brown | ARI | 4500 | 9.0 | 24.9% | Mohamed Sanu | ATL | 4500 | 10.3 | 17.3% |
Adam Thielen | MIN | 3800 | 7.7 | 25.6% | Davante Adams | GB | 4900 | 11.4 | 18.0% |
This is a unique week. There are only two wide receivers in the "most likely" half of the table that will enjoy anything resembling a favorable matchup based on my usual stat criteria. The first is Alshon Jeffery, who faces a Tampa Bay pass defense that ranks 26th in efficiency (per DVOA) and 20th in FantasyAces points allowed to opposing wide receivers. To boot, he'll also be running most of his routes against rookie Vernon Hargreaves (per Pro Football Focus). The second wide receiver is Tyreek Hill, who faces a Carolina pass defense that ranks 23rd in points allowed and 26th in efficiency. He'll also be running most of his routes in the slot against someone named Leonard Johnson.
Tight Ends
Below are the tight ends with the highest (and lowest) probabilities of achieving value in cash games and GPPs:
MOST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
Jimmy Graham | SEA | 4750 | 12.2 | 35.7% | Jimmy Graham | SEA | 4750 | 14.9 | 28.7% |
Greg Olsen | CAR | 4850 | 12.0 | 32.5% | Tyler Eifert | CIN | 4900 | 13.6 | 19.9% |
Tyler Eifert | CIN | 4900 | 11.8 | 30.5% | Rob Gronkowski | NE | 5750 | 15.9 | 19.7% |
Rob Gronkowski | NE | 5750 | 13.8 | 30.4% | Antonio Gates | SD | 4100 | 11.1 | 18.4% |
Travis Kelce | KC | 4700 | 10.7 | 26.4% | Greg Olsen | CAR | 4850 | 12.2 | 14.2% |
LEAST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
Virgil Green | DEN | 4000 | 5.7 | 4.4% | Julius Thomas | JAX | 4000 | 6.3 | 1.6% |
Julius Thomas | JAX | 4000 | 5.8 | 4.8% | Coby Fleener | NO | 4100 | 6.8 | 2.1% |
Coby Fleener | NO | 4100 | 6.3 | 6.1% | Virgil Green | DEN | 4000 | 7.1 | 3.0% |
Martellus Bennett | NE | 4400 | 7.4 | 8.9% | Zach Ertz | PHI | 4200 | 7.9 | 4.1% |
Cameron Brate | TB | 4250 | 7.6 | 11.6% | Cameron Brate | TB | 4250 | 8.1 | 4.4% |
Among the high-value options, Jimmy Graham is the clear choice in both formats based on his statistical matchup, and Travis Kelce is a viable backup plan. With respect to Graham, New England's pass defense ranks 26th in overall efficiency and 24th in efficiency on tight end targets. He also has a tournament-friendly projected ownership of only around 5 percent. Meanwhile, Kelce faces a Panthers pass defense that ranks 29th in FantasyAces points against to opposing tight ends, 23rd in pass defense efficiency (per DVOA), and 29th in pass defense efficiency on tight end targets.
Given that Kelce also has a projected ownership rate of only around 5 percent and just missed the tournament side of the table [P(CASH) = 13.7%], he's as viable a value option in tournaments as he is in cash games.
Defenses
Below are the defenses with the highest (and lowest) probabilities of achieving value in cash games and GPPs:
MOST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
NY Jets | NYJ | 3000 | 10.9 | 65.2% | Jacksonville Jaguars | JAX | 2500 | 9.7 | 47.5% |
Jacksonville Jaguars | JAX | 2500 | 9.2 | 63.6% | Chicago Bears | CHI | 2500 | 9.4 | 45.1% |
Washington Redskins | WAS | 2700 | 9.8 | 63.6% | NY Jets | NYJ | 3000 | 11.2 | 43.5% |
Houston Texans | HOU | 3000 | 10.6 | 62.5% | Washington Redskins | WAS | 2700 | 10.0 | 43.5% |
Chicago Bears | CHI | 2500 | 8.9 | 60.9% | Tampa Bay Buccaneers | TB | 2500 | 8.8 | 40.2% |
LEAST LIKELY TO ACHIEVE VALUE | |||||||||
NAME | TM | SALARY | AVG | P(CASH) | NAME | TM | SALARY | MAX | P(GPP) |
Green Bay Packers | GB | 3000 | 8.1 | 42.6% | Green Bay Packers | GB | 3000 | 8.2 | 21.7% |
Kansas City Chiefs | KC | 3100 | 8.5 | 43.4% | Kansas City Chiefs | KC | 3100 | 8.7 | 22.3% |
Dallas Cowboys | DAL | 2800 | 7.7 | 43.8% | Dallas Cowboys | DAL | 2800 | 7.9 | 24.8% |
Denver Broncos | DEN | 2850 | 8.1 | 45.8% | Philadelphia Eagles | PHI | 2750 | 7.8 | 25.5% |
New England Patriots | NE | 3150 | 9.3 | 48.3% | New England Patriots | NE | 3150 | 9.5 | 26.1% |
Because of the teams on bye, this is an atypically bad week for finding value at defense. Among the most likely to achieve value, the Jets, Jaguars and Texans have the best matchups according to FantasyAces points allowed and/or opponent offensive efficency, but they themselves rank at the bottom of the league in FantasyAces points scored. In other words, their matchups are of the movable object vs. resistable force variety.
Then there's the group of defenses that have favorable matchups, but are on the road; a game situation that's seldomly favorable: Houston and Chicago. For Houston, Jacksonville is the Bottom 8 offenses of the week with respect to offensive efficiency, but that's it in terms of the four stat categories I look at. And to boot, the Texans are among the lowest-scoring defenses themselves. Likewise, Tampa Bay may be among the worst offenses in the league with respect to points allowed to defenses, but the Bears are middling or worse across all defensive stat categories.
So what to do? Well, from a game theory perspective, given that almost every defense offers value [i.e., lowest P(CASH) is still higher than 40 percent and lowest P(GPP) is still higher than 20 percent], which is a phenomenon we see every week, it's correct to go cheap in general. That's especially the case in tournaments, so one of Jacksonville or Tampa Bay is the way to go. (I'm omitting Chicago here because they're on the road.) In cash games, however, perhaps this is a rare week to lean more towards chalk. In that case, easily the best defense to use is Arizona, who faces a San Francisco offense that ranks among the worst offenses in the league with respect to fantasy points allowed and offensive efficiency. Furthermore, although the Cardinals' value probability isn't high enough to make the top of the table, it still ranks 11th, which is plenty high enough to consider in a week like this.