It’s DFS Week at SI.com. All week, we and our 4for4 colleagues will help provide you with a foundation for DFS success this season. In this installment, 4for4’s T.J. Hernandez gives you his best practices for understanding DFS salaries and building winning lineups in both cash games and tournaments.
When it comes to building lineups in NFL DFS, deciding how to allocate salary across positions largely depends on which type of game you are playing: a cash game or a tournament, which is often referred to as a guaranteed prize pool, or GPP.
A cash game generally refers to head-to-heads, 50/50s, and double-ups, all games where roughly half of the field wins about twice their buy-in, depending on the exact game structure.
Tournaments are games where 30% or less of the field wins money, and most of the prize pool is concentrated near the top of the standings. The exact structure of tournaments can vary wildly, but there are basic strategy concepts that apply to all tournaments, no matter the size of the field or the payout structure.
When building lineups for cash games, value is king. Because you only have to beat about half of the field and there is no extra reward for having the highest score in the field (except for in a head-to-head, of course), the goal in cash games should be to raise your team’s floor and narrow your range of potential scoring outcomes, rather than maximizing your point expectation. In other words, you want to build lineups that consistently score above average, not have the highest average.
Here’s an example. Two DFS players, Carl and Gary, both play exclusively 50/50s every week. Carl averages 124.4 points per lineup and Gary’s average is 130.3 points per lineup. The average score needed to cash in the 50/50s that Carl and Gary play in is about 120 points. Over the course of a season, Carl never scored fewer than 95 points and didn’t top 140 points. Gary made lineups that scored as many as 181 points, but he also had weeks where his team barely broke 80. By making lineups with a narrow range of outcomes, Carl broke the 120-point mark and cashed 12 times; Gary only hit 120 points in nine weeks. Even though Gary has a higher average score than Carl, it’s Carl that is more profitable in 50/50s.
This scenario isn’t uncommon when comparing an experienced DFS grinder to a novice who knows how to put together a good fantasy team, but isn’t adjusting for game type.
So how does one build a lineup with a narrow range of outcomes?
In short, by paying for predictability, saving at high-variance positions, avoiding players that are susceptible to game-script issues, and targeting value as much as possible.
Typically, quarterbacks and running backs offer the highest level of predictability. Quarterbacks touch the ball on every offensive play. Because they have so many trials, even in a single game, their results generally fall pretty close to expectation. Of course there are disappointments and surprises, but more than any other position, quarterbacks offer both the highest floor and ceiling, especially the top-tier ones. It’s relatively easy to forecast how a quarterback will perform in a given matchup, and that means spending up at the position is not only common, but often preferred in cash games.
Running backs offer a similar level of predictability to quarterbacks, but understanding player types is paramount when selecting running backs in cash games. The value at running back lies in volume of touches, but also in the types of touches that those backs see. Usually, the most expensive running backs are going to garner the most touches, making those players worth the high price tag. Avoiding players that risk being sidelined if their team is trailing is a major part of building a high-floor lineup, though.
A player like LeGarrette Blount might carry a salary near the top tier of backs after a few big touchdown weeks, but Blount is a classic example of a running back to generally avoid in cash games. A bad matchup can have a huge impact on Blount’s snaps and overall usage—if his team is up big, Blount is they type of player that might get an extra 10 carries late in the 4th quarter. If his team falls behind, Blount usually finds himself on the bench in favor of a pass-catching specialist. This is the perfect example of a player with a high average, but a devastating floor.
Rather than counting on a positive game script or a couple touchdowns from a Blount-type, the ideal cash game running back is involved heavily in both the run game and the passing game. David Johnson and Le’Veon Bell are the prototypical cash game backs because they are immune to game script, making them centerpieces of their team's game plan who won’t be deemed useless if their team is in catchup mode. Obviously, salary restrictions usually prevent owners from rostering Johnson or Bell every week, but when deciding on running backs in cash games, always ask yourself if the player that you are choosing will remain involved in the offense even if things don’t go as planned.
One final note about running backs. An underpriced running back expected to see a large workload is a value that should almost never be avoided in cash games. This scenario is most common when a starter is declared out in the middle of the week and his backup, who is usually priced near the minimum salary, will suddenly see upwards of 20 touches. No matter what values are available elsewhere, a cheap running back offers affordable volume that immediately raises the floor of an entire DFS lineup.
Pass-catchers are the most volatile skill-position players on a weekly basis, which means it’s usually best to try and save salary at wide receiver and tight end whenever possible. On full PPR sites, the absolute top receivers can be great cash game plays, but when choosing between a top receiver and top running back, the running back almost always wins out. Even the most high-volume receiver is only going to see roughly 10 targets per game. In a contest where a high floor is key, paying up for questionable volume can lead to a very wide range of outcomes.
In order to find predictable value at receiver, search for those who tend to get short targets, usually over the middle of the field. These types of receivers tend to be much more reliable than receivers that see deep, low-percentage looks. In cash games, a Jarvis Landry is much more valuable than a DeSean Jackson.
Tight ends rely heavily on touchdowns for scoring. Thus, it’s rarely wise to pay up at the position in cash games. Tight ends simply won’t offer the same value as other positions in a similar price range. Because tight end is such a low-scoring, volatile position, it’s often best to save as much as possible in order to free up salary elsewhere.
More so than any of the skill positions, defense/special teams is the most high-variance position in fantasy. This doesn’t mean that owners should simply be plugging in the cheapest option available though—look for a D/STs playing on a team that is the favorite according to betting odds. The D/ST does not necessarily have to be minimum-priced—extremely cheap D/STs are often horrible units that don’t offer much fantasy value even when their team wins.
If you play on a site that uses kickers, the formula for success is relatively simple: target kickers that are on teams that are the favorite while avoiding kickers on teams that one on the underdog—and do so while saving as much salary as possible.
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Allocating salary in a GPP is more art and less science. The one constant in tournaments is that the goal is to maximize upside, though to what degree depends on the structure of the tournament. A game like a qualifier, where only one entry wins a significant prize, calls for more of a Hail Mary approach to roster construction. A 1,000-person tournament that pays out 30% of the field with the prize pool spread relatively evenly might call for more balance between value and upside.
Still, there are some concepts that can be universally applied to help maximize upside in a tournament. Unlike cash games, the goal of a GPP isn’t to build lineups that would consistently beat the average. Remember, most GPPs pay 30% of the field or less, and it’s hard to find even those. A game where 20% of the field wins money is more common.
One of the best ways to allocate salary in a manner that puts a first-place finish in a lineup’s range of outcomes is to embrace the inherent volatility of football. In practice, that often means paying up for pass-catchers, namely wide receivers. While receivers aren’t as consistent as running backs, when they hit, they hit big.
Over the last five seasons, there have been 131 instances of a non-quarterback scoring 35 or more PPR fantasy points—88 of those, or 67.2%, were scored by a wide receiver.
Beyond flip-flopping the positions at which you spend the most money, another roster-building technique in GPPs is to stack positions. Stacking is the concept of pairing highly correlated teammates or players in the same game on a single roster. The most common stack is a quarterback and his top receiver. The logic behind that stack is simple— if one has a huge day, it’s likely that the other will, too, which maximizes the upside of your overall lineup.
Some other popular, but less effective stacks include:
QB + TE or WR2
QB + 2 pass catchers
QB + WR + RB
QB + RB
QB + K
RB + DEF
DEF + K
QB + WR + opposing WR
Of these combinations, quarterback/running back is generally the most effective, as a lineup can get every touchdown from a single team. All other stacking combinations should be used sparingly on a case-by-case basis.
Understanding salaries and values is the foundation for being a profitable DFS player, but GPPs revolve around ownership.
Evaluating public perception may give a DFS player more of an edge in a large-field GPP than any projection model can. Predicting ownership and implementing it into the lineup-building process can take a lifetime to master, but I'll leave you with this example to illustrate how you can think about ownership when making tournament lineups.
Assume that Julio Jones and Antonio Brown have the same salary in a given week. Jones is facing a lock down, shadow cornerback, while Brown is facing one of the worst secondaries in the league. Because of the matchup, the expectation is that anywhere from 35% to 45% of owners will roster Brown, while Jones is expected to be owned in somewhere between 5% to 10% of lineups. The reality is that, no matter the matchup, Brown is almost never four to seven times more likely than Jones to be the top receiver in a given week. In this situation, the optimal play is to roster Jones. By embracing the uncertainty of football—especially at one of the most volatile positions—the reward for rostering Atlanta’s top receiver in this situation is much greater than rostering Brown, who offers little edge over the field if he has a big game since he will be on so many other rosters.
In daily fantasy football, there are few, if any, hard and fast rules, but this should serve as a great foundation to understanding the nuances of building profitable lineups.