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DFS Strategy: Identifying Soft Pricing Areas and Exploiting Them (Fantasy Football)

by Isaiah Sirois | @is_sirois | Featured Writer
Jun 18, 2020

Brian Hill and DeAndre Washington offer a good case study for the proper exploitation of soft pricing in DFS.

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Every week, cheap players in daily fantasy sports (DFS) will outperform their salaries to give you massive returns on investment. Often, the DFS community will pounce on these players, and their considerable ownership rates will make them “chalk,” or consensus plays. These two forces — salary value and ownership rate — combine to determine how successful your DFS lineup will be.

So when you’re playing DFS, you’ll need to both evaluate value and think like a contrarian. So yes, while a minimum-salary player vaulted into a starting role has upside, it still could be smart to bet against him. That said, there’s always a chance for him to pay off, so you’ll need to be aware of the risk you’re taking.

For example, here are two chalk plays from 2019.

Player Week DK Salary DK Own%* DK Points FD Salary FD Own%* FD Points
Brian Hill Week 11 $4,800 54.8% 4.8 $5,900 46.8% 4.3
DeAndre Washington Week 16 $4,000 67.5% 18.6 $5,600 47.0% 17.6

 
*Ownership data comes from FantasyPros’ projected ownership tool. These projections are available to premium members as they set their DFS lineups.

As you can see, buying Washington paid off, but buying Hill did not. So how can we avoid busts like Hill while trusting studs like Washington? Here are some best practices for exploiting soft pricing areas.

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Look for Expected Volume

In fantasy sports, volume stats are king. While a touchdown can make or break your lineup, players will only have the chance to score if someone gives them the ball, so you should evaluate DFS plays based on their shares of the offense.

Logically, injuries have a significant impact on how a team distributes the workload. While injuries can cause an uptick in another player’s usage, they don’t have to — teams can spread the ball out or emphasize a different aspect of their offense. So what factors could’ve kept us from buying Hill without forcing us to avoid Washington?

The Stater’s Volume Stats
The starter a player replaces is the best place to start your evaluation. If a starter only gets a moderate workload, then why bother playing their backup? You’re essentially betting that a less talented player will do more with less than what the starter gets each week.

Before Week 11, Falcons starter Devonta Freeman was averaging 11.89 carries and 16.1 touches per game. In contrast, Raiders starter Josh Jacobs was averaging 18.61 carries and 20.69 touches per game before Week 16.

Since backups are not guaranteed to get the full share of their starter’s workload, these numbers give us a good idea of their ceiling. So how many looks did Hill and Washington each receive in these respective weeks? Hill earned 15 carries and 18 touches; Washington earned 23 carries and 25 touches.

From this data, we could’ve correctly anticipated a sub-20 touch game for Hill, which would’ve made him less of a fantasy asset. We also could’ve anticipated roughly 20 touches for Washington, which is a good benchmark for fantasy value.

Team Stats
Beyond individual player stats, you can also determine how often a team emphasizes a specific part of their offense. To do so, look at where a team earns their yards and touchdowns.

Before Week 11, the Falcons were averaging 377 yards per game — that’s pretty good! However, 80% of that yardage came through the air, and Atlanta was averaging just 76.8 yards per game on the ground. The Raiders, meanwhile, were averaging 333.9 yards per game before Week 16, and 33 percent of that (112.25 yards per game) came on the ground.

Again, this data also would’ve helped us identify Hill as a risky play and Washington as a value. The Falcons struggled to run the ball last year, so it should’ve been no surprise that Hill failed to capitalize on his increased workload.

Look at Projected Ownership Data

Finding high expected volume is crucial to exploit soft pricing successfully, but contrarianism often is, too. To get a sense of how many DFS players are buying a particular option, you can check out our projected ownership tool. This can help you gauge whether your play is contrarian or chalk.

If your low-priced sleeper for the week is a popular pick, then you may want to pivot elsewhere in tournament leagues. Double-check the data, and only commit to the player if you’re certain that you can find contrarian upside elsewhere.

However, there are times when it’s smart to exploit chalk. If you’re playing in cash leagues, then, by all means, commit to it! If that player’s ownership rate exceeds 50 percent, you’re not hurting yourself as much, since most other players are taking that risk alongside you. Also, you probably wouldn’t want to give a majority of others an advantage over your lineup by avoiding the high-upside chalk play, either.

Contextualize Player Pricing

Sometimes a DFS site may increase the price for your high-upside sleeper. For example, Brian Hill’s $4,800 DK salary and $5,900 FD salary certainly wasn’t the player minimum. While it might be low enough to help you find value at other positions, you’re still taking on some expense if a player’s salary is above the minimum.

For DK lineups, a good rule of thumb is to get three-to-four times a player’s salary in points. With Hill’s price of $4.8k, you’d have needed 14.4 to 19.2 points for him to meet that benchmark. He scored just 4.3. But with Washington, you would’ve needed 12 to 16 points for him to recoup value on his salary, and his 17.6 points actually exceeded that mark. As such, Washington’s price made him a less risky play.

That said, you may still be able to construct your ideal lineup while paying for your sleeper’s above-minimum salary. That’s fair, but you should only commit to a lineup after you’ve carefully evaluated how much value you stand to gain from targeting the soft pricing area.

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Isaiah Sirois is a featured writer at FantasyPros. For more from Isaiah, check out his archive and follow him @is_sirois.

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