Category: NFL DFS Tips

Offensive injuries can torpedo a DFS lineup, while defensive injuries can ignite an opponent’s offense faster than a 4th of July rocket. So, before you lock in those rosters, get a leg up with DFS Hub’s Week 3: NFL Defense Injuries and Sharp Bettor Report.

Roll this week’s highlights (60 seconds):

Biggest Week 3 Sharp Action

• CAR has massive sharp money action on its +200 moneyline (Sharp%: 65)
• Sharps are all over IND at +8.5 (Sharp%: 44)

If you’re one of those folks who loves to analyze defensive injuries and sharp money bets over your morning coffee, this might just streamline your weekly ritual.

Introducing DFS Hub’s fresh-off-the-press NFL Defense Injuries & Sharp Bettor Report.

It’s got two simple purposes:

1. To tell you who’s hurt—that matters—on NFL defenses.
   • That way, you can avoid these defenses (DSTs) if appropriate, and/or exploit them with opposing offensive players
2. To lend a sense of who the smart money is backing this week.
   • Use these clues to adjust player expectations in cases where sharps are heavily investing in a team, relative to the percentage of bets on that team.

Give these new reports a spin. They may be worth ditching the morning donut over.

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“I do all of my lineup building without any of the DFS optimizers.”—David Bergman, $2.5-million winner in the 2020 DraftKings’ Fantasy Football World Championship

New daily fantasy players often ask, “What is the best DFS lineup optimizer?”

That’s often followed by the question, “How do you use a DFS optimizer?

But those aren’t the questions new DFS players should be asking. What they should be asking is, “Is an Optimizer something I should even be usingl?”

Relying on “off-the-shelf” optimizers is virtually guaranteed to result in underperformance versus astute hand-crafted lineups, for the reasons that follow. We’d urge all readers to carefully consider the facts below before risking any money with an NFL DFS optimizer.

Reasons You Should Not Use a DFS Optimizer

1. You think they simply work…like magic.
   • Optimizers don’t think. They use common algorithms to generate random lineups. And those lineups aren’t even perfectly “optimized” (more on that below). Optimizers don’t know which players are not playing at a peak level. They don’t know player trends. They don’t know historical relationships. Those things are gathered from experience, research and modeling, which off-the-shelf optimizers won’t give you. Optimizers are anything but set-and-forget tools. Apart from faulty inputs (e.g., bad projections), operator error is their biggest risk.
2. You like to build just a few lineups
   • If your game of choice is single-entry contests, optimizers simply aren’t as useful — especially for cash gamesA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More. For double-upsA DFS contest where entrants must beat around 55-56% of competitors to win. Winners double their money. More and 50/50s50/50s are DFS contests where entrants win if they beat at least 50% of competitors. Winners receive $1.80 back for every $1.00 bet. With a 10% rake, 50/50 players must win 55.6+% of the time to grow their bankroll. More, you rarely need more than 1-3 lineups. After all, you’re searching for players with the highest floors. A proficient single lineup DFS player will easily beat your typical optimizer-generated single lineup the majority of the time. But wait, the pros swear by the optimizers they sell. How can they not work? Well, it’s not that the automated optimizers don’t work. It’s that they probably won’t work for you. Pros with fat bankrolls use optimizers to create dozens, even hundreds, of lineups. They rely on correlations and variance and build complex algorithms into their optimizers. In any event, you can be darned sure they’re not selling the secret sauce that makes them pros for $49 a month.
3. Optimizers rely too heavily on projections
   • All fantasy point projections are inaccurate—be they total points, ceilings, floors, or what have you, they’re inaccurate. Yet, those same projections are the main variable in optimizer calculations. Worse yet, most optimizers use projected fantasy point averages by default, with little regard for: (A) upside, and (B) how often a player hits his upside. Obviously, what everyone wants/needs are the least wrong projections — those with the least bias (since they’re all biased). A successful optimization system must have more consistent and accurate projections than the crowd. Otherwise, an optimizer will simply magnify projection errors — due to the large number of lineups being created. Relying too heavily on mass-market projections that hundreds of thousands of your competitors rely on dilutes your edge. That’s especially true in GPPs.
4. Managing variance isn’t easy
   • It’s not just projections you need to worry about. If you’re building multiple lineups in an optimizer, managing variance is essential. Among other things, it means adjusting player projections up and down by the right amount to get the optimal diversity of lineups. But here’s the problem. What if you adjust a projection higher because you think the opponent’s poor defense is not fully factored into the projection? But then again, what if it is actually factored in?  What you’ve just done is boost the projection error.
5. Optimizers hinge on exposures
   • Determining the correct percentage of rosters that a given player will appear in is fundamental to optimization. You don’t want to be overexposed or underexposed to anyone. Getting this part of the process wrong significantly reduces the chances of success. So does over-limiting the player pool your optimizer can pull from (i.e. excluding too many players from your “short list”). If you’re making these kinds of foundational decisions, you could just as easily spend that effort on perfecting a manual lineup construction process.
6. Optimizers rely on ownership optimization
   • You have to set limits on aggregate ownership (i.e., the total combined ownership of all players in your lineup). There’s more science than art in that. Moreover, game theory and projecting the crowd’s opinion of player value remain paramount. This is but one more complexity of optimization prone to error.
7. Optimizers are only quantitative
   • “Qualitative” factors often get dismissed by optimizer pushers. We touched on this above. Optimizers don’t adequately factor in variables like player and team motives, psychology, shifts in team strategy, environment (e.g., what sort of contests does a player thrive in), the impact of lost teammates, player matchup details, player utilization and so on. How can you find the best DFS QB, for example, if you’re not considering each player’s context that week? The reason optimizers are mainly number crunchers and not context analyzers is that qualitative factors are not like yards or TDs. They cannot be as easily quantified. As a result, qualitative factors can’t be readily plugged into an algorithm. That’s good for you, however, because it creates inefficiency in the market—and exploiting inefficiency is how you win. To put this all another way, optimizers rely too heavily on mass-market data. The more people who know a piece of DFS information, the less valuable that information becomes.
8. Most People Lose
   • Roughly 73% of DFS players lose, as of the time this is being written. The top 1% make 45% of the money on DraftKings, as of this writing. More interestingly, a 2015 report found that the top 11 DFS players spend $2 million+ in entry fees a year on average, and they’re all using optimizers of some sort. But if you’re trying to exploit Draftkings inefficiencies, you don’t want to toil away competing against stat geniuses who run multi-million-dollar quant models on a custom NFL DraftKings optimizer. You want to do something different, like find a consistent niche methodology (possibly a more qualitative approach) and refine it. And remember, increasing your entries with an optimizer may boost your win probability, but does it boost your probability more than it boosts your lineup costs? For most people, the answer is no.
9. You have limited resources
   • To make optimization worth it on a large scale, you need enough bankroll to deploy enough lineups. And enough time to manage it all. You can’t just create 150 lineups and not look at them before submission. For those with smaller bankrolls, searching for the best overall values can have a higher return on time.
10. You’re not getting the most optimized lineup
    • With practically infinite player combinations, processing power limitations prevent publicly available optimizers from generating true theoretical top lineups. What you get is an approximation of the most optimized lineup(s) using mathematical and programming shortcuts.

Conclusion: DFS optimizers

Too many optimizer users put too much faith in the simple logic that spits out optimizer recommendations. They see the shiny marketing and the big names associated with these tools, and then they click and pray….and lose.

An optimizer doesn’t just magically give you skill. An optimizer reflects skill. You have to make multiple decisions correctly to leverage an optimizer. Even top pros manually select 2-4 players as locks in all of their lineups. So if you’re going to do all that analysis work for 2-4 players, you might as well perfect your process and do it for the rest of the positions, with a hand-built lineup. At least that way you don’t have to get both your player picks right and get the optimizer settings right.

Don’t get me wrong, optimizers are an incredibly powerful tool in the right hands, with the right logic built in. In fact, once you reach pro level, one might argue that optimizers are the best way to scale your winnings. They’re practically indispensable for the algorithmic selection of 10+ lineups. For the best of the best who may submit 150 lineups in a given contest, imagine the gargantuan effort of creating all those rosters by hand!

But until you graduate to that point, to the point where you’ve refined your winning formula to beat the house edge, where you’re routinely cashing and handily beating the rake, optimizers are better left for another day.

People make a healthy living by hand-curating lineups using reliable disciplined methods that marry qualitative and quantitative analysis. Focus hard on learning what stats matter and improving your process. Whether your system is manual or automated, the DFS game boils down to successfully finding inefficiencies — inefficiencies that most people are too casual or inexperienced to exploit. An optimizer simply won’t be an optimal way for you to return on your investment.

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It takes serious value hunting to win NFL DFS contests on DraftKings or FanDuel. That means identifying players able to rack up significantly more fantasy points than their salaries imply.

One common way to measure NFL DFS value plays is with salary multipliers. Below is a guide on how they work, and bargain shopping tips for building winning lineups this 2023 NFL DFS season.

The Basics of Salary Multipliers

If you want to cash in NFL DFS contests, step one is knowing how many points it’ll take.

For example, to place in a typical Draftkings cash gameA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More (i.e., 50/50, double up, or head-to-head), you’ll want to aim for 150+ total points, assuming a classic 9-man roster.

Sometimes it’s as low as 130 or less. Sometimes it’s more. But 150 points is a safe guideline.

That means each of your players needs to score almost 17 points on average.

In salary terms, each player must therefore average three times his salary for you to “cash” in a cash gameA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More — given the average player costs $5,555 (i.e., $50,000 salary cap / 9 roster slots).

Put another way, you need to score an average of 3 points for every $1,000 you spend on a player. That equals the target of 17 points per player divided by 5.555 (the average player’s salary divided by 1,000).

So if Mike Evans costs $7,100, for example, you want to be confident he’ll score at least 21.3 points to justify adding him to your lineup.

Think of this 3.0x as your minimum required return on investment (ROI) for drafting a player. This is the salary multiplier you’ll need to grow your capital in cash gamesA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More.

Value Fields on DFS Hub

The value target (i.e., what you should shoot for) varies by contest type. To help you quickly determine the performance needed for a player to “hit value” at a given salary, DFS Hub offers three fields:

[2-5xSal] — which stands for 2.5 times salary: a bare minimum your player should hit in a classic cash gameA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More
[3-0xSal] — which stands for 3.0 times salary: a conservative fantasy point target for classic cash gamesA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More
[3-5xSal] — which stands for 3.5 times salary: a minimum target to place in the top 10% of GPPGPP stands for guaranteed prize pool. It is a daily fantasy sports contest where the prize money is guaranteed, regardless of how many players participate. The prize payouts are generally skewed heavily to a small number of winners who win a large share of the pot. GPPs are often... More tournaments

The minimum theoretical fantasy-points-to-salary ratio that a player must hit (to help you win) is sometimes called the breakeven value. Cash gamesA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More seldom have a “breakeven” value lower than 2.5x. Going 3.0x value is more common, especially with the DFS market getting more efficient in 2023.

Once you understand how high of a hurdle you have to leap, you can then estimate the probability that a player in question will exceed that minimum.

Get in the habit of mentally running these estimates for every player in your lineup. If a player’s fantasy point [FP] target seems high, ask yourself why. In some cases, you may need to evaluate alternatives.

Cash Game Value

In principle, winning cash gamesA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More is straightforward. You essentially want to pick “safe” players with:

• high floors
• ample opportunities (passes, rushing attempts and/or targets), and
• the greatest chance of hitting breakeven value (thus beating at least half your opponents).

One way to size up cash gameA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More candidates is to compare the player’s floor ( [FloorL4] ) to their 3x value target ( [3-0xSal] ). When you find a player with a floor that’s almost 3x their salary (or better), you’ve likely found a player with a favorable risk/reward ratio. Players with floors that are 3x their salary aren’t a sure thing, but they’re often ‘sure enough’ to bet on in cash gamesA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More.

GPP Value

GPPs vary in size and maximum entries, and in large tournaments, a smaller percentage of entrants win.

As a result, it’s hard to generalize, but the minimum score to cash is usually over 10 points higher than in cash gamesA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More. You want to target roughly 18 FPsFantasy points More per rostered player, minimum.

Compared to cash gamesA cash game refers to a DFS contest in which roughly half the field wins a prize. The last place winner wins the same prize as the first place winner. While the prize payouts aren't as sexy as tournament contests (GPPs), the probability of placing in the money is usually higher. ... More, ownership and ceiling matter far more in GPPGPP stands for guaranteed prize pool. It is a daily fantasy sports contest where the prize money is guaranteed, regardless of how many players participate. The prize payouts are generally skewed heavily to a small number of winners who win a large share of the pot. GPPs are often... More contests. To land in the top 10 in big GPPs you need most of your players to exceed their ceilings, going over 4x salary on average (over 200 total points).

• Pro Tip: One way to narrow down such players is to look for those who’ve gone 4x salary in the not-too-distant past, who have good matchups but not outlandish salaries.

To bag the top prizes in the biggest tournaments, you usually need to nail all the breakout performances on the slateA slate is a list of games, typically starting around the same time of day. The most popular NFL slate in DFS is the "Main" slate, which usually has 10 or more games in the regular season. This is an example of DraftKing's main slate for NFL Some slates includes as few as one gam... More. If a player goes 7x value and he’s not in your lineup, your chances of taking first place plunge. Such players are often involved in games that end up in shootouts.

If, for example, one of Josh Allen‘s usual targets is out of the Buffalo Bills high-scoring lineup, the next man up could provide uncommon value. And they’ll do so with a lower DFS salary than the Bill’s normal top option.

Salary Multiplier Examples

Here are some simple examples to illustrate what it takes to strike big value.

To achieve a 4x ROI on DraftKings on a $7,000 wide receiver, that player needs to amass 28 fantasy points. This requires a stat line equivalent to:

• 8 receptions (resulting in 8 points)
• 110 receiving yards (i.e., 11 points for the yards + a 3-point bonus for a 100-yard game)
• 1 TD (6 points)

To achieve a 4x ROI on DraftKings on a $6,000 running back, he needs 24 points. That takes a stat line equivalent to:

• 110 rushing yards (11 points for the yards + 3 points bonus for a 100-yard game)
• 2 receptions (2 points for the receptions)
• 20 receiving yards (2 points for the receiving yards)
• 1 TD (6 points)

…or, 2+ TDs with fewer yards.

To win the Millionaire Maker you may need to average over 5x! To reach that threshold, add another TD to the above examples.

Value by Salary

As a player’s price goes up, his value target drops. That’s hard for most NFL DFS rookies to wrap their heads around.

What this means is, you need less “value” (a lower salary multiplier) from a higher-priced player than a lower priced player, in order to generate the same output.

A 3x performance on a high-salary player is, therefore, more valuable than a 3x on a low-salary player.

By contrast, for less reliable bargain basement players, you need opportunities to generate a higher-than-average return on salary, i.e., 3.5x to 4.0x or more.

Value on FanDuel Versus DraftKings

How you go about leveraging value depends on what platform you play on.

Winning on FanDuel requires fewer fantasy points relative to salary. That’s because it allots fewer points for performance and has higher salaries, including higher minimum salaries.

For these reasons:

• Target salary multipliers are smaller on FanDuel than DraftKings
• It often takes about 0.5x to 1.0x less to hit value on FanDuel (i.e., as low as 2.0x on FanDuel versus 3.0x on DraftKings).

This also impacts player selection. On FanDuel, for example, running backs exceed 3x value almost twice as often as receivers, and more than three times as often as TEs, according to Numberfire (source). That’s largely because FanDuel is only half-PPR, meaning they award only 1/2 point for catches.

Here’s a quick guideline for minimum value targets at each position on DraftKings and FanDuel. Note: These values are based on the classic 9-player format.

NFL DFS Value By Position

The NFL DFS value formula is ever-changing, but here are some quick rules of thumb to maximize ROI in tournaments:

• QB: In big tournaments, the best-value NFL DFS QBs tend to be those with mid-range salaries or less.
  • See: How to Choose a DFS QB
• RB: Running backs who go for max value tend to be elite backs, or those otherwise expected to attract unusually heavy volume in a given week.
  • See: How to Choose a DFS RB (Running Back)
• WR: Receivers who go off in a given week tend to see deep ball completions and high expected target volume. The former can be hard to predict but the latter is easier to forecast, particularly if a WR is expected to see a greater role in a given game.
  • See: How to Choose a DFS WR (Wide Receiver)
• TE: Maximizing value at the tight end position usually requires finding TEs under $4,000 in TE-friendly game scripts. Tight ends usually require just one TD to hit value.
  • See: How to Choose a DFS TE (Tight End)
• DST: High-value defenses tend to be lower-cost DSTs who get a lot of pressureA “pressure” in NFL parlance is when the quarterback is hurried, hit or sacked. Defenses that pressure the opposing QB more than average allow fewer points and win more games, for obvious reasons. QBs under pressure throw away the ball more and make more mistakes (e.g., throw... More and a defensive touchdown.
  • See: How to Choose a DFS DST (Defense)

Maximizing Value

NFL DFS is a relatively efficient market, meaning that players who are widely expected to hit value or who hit value more consistently generally cost more.

But not always.

Your job as an NFL DFS analyst is to find the exceptions—the mispricings.

Mispricing can occur in all sorts of scenarios, for example:

• when a player substitutes for an injured starter
  • On DraftKings, given its higher scoring and lower salaries, a minimum-salary RB (or sometimes a WR or TE) who subs for an injured star is a must-start the majority of the time.
• when a player’s role grows within his team, e.g.:
  • when a rookie gets more reps
  • when a player is promoted after a breakout performance
• when a player’s salary drops materially after a bad performance or two.

When assessing situations like this for their 3x or 4x potential, be sure to adjust your value expectations to the:

• player’s salary
• player’s position (e.g., workhorse running backs in good matchups hit value more often than tight ends)
• contest
• site you’re playing on (DraftKings, FanDuel, etc.).

If you’re not confident a player can generate a large enough return on salary to help you win your contest, leave him out of your lineups. And remember, volume (opportunity) leads to value.

Analyzing Matchups and Trends to Find Value

With NFL DFS matchups, it’s important to look beyond just the overall strength of the opposing defense. You also need to consider factors like the opposing team’s defensive scheme, their recent performance, and any injuries or other factors that may impact their performance.

To supplement matchup analysis, it’s important to research a player’s recent performance, their historical performance, and any factors that may impact their productivity—such as injuries, coach comments or recent changes in coaching staff.

Factors like a player’s consistency over the course of the season, expected defensive coverage, PFF grades and any recent changes in their role or usage, can also be key signals.

Team trends are yet another vital element to consider, as they can heavily impact a player’s performance. This includes analyzing factors such as a team’s offensive scheme, game motivation and recent momentum.

The takeaway from the above is this. When hunting for value, looking beyond general statistics and Vegas lines isn’t just recommended, it’s mandatory. Everyone’s trying to do the same thing—find hidden gems. You’ve got to out-research and out-think your opponents.

The Impact of Weather on Player’s Value

Poor weather conditions have been proven to negatively change the game script. According to data by The Fantasy Footballers, rains tends to have a negative effect on quarterbacks and recievers. When raining, completion percentageAlso known as "catch rate" or completion percentage, reception percentage equals a player's total receptions by total targets. More drops by abour 3%, total game passing production dips by 45 yards and .6 fewer passing TDs are tossed. Those numbers are even worse when snowfall occurs.

When deciding between players with a similar price tag, you may get more value out of a QB or pass catcher that is in more favorable weather conditions. Additionally, in the rare instances of snowfall, flexing a running back over a reciever could provide you unexpected value over your opponents who may not pay as close attention to the words of the weatherman.