NFL DFS GPP Strategy Guide: Z-Scores, Stacking & Trends

In daily fantasy football, there are different things that I look for during the week when preparing for GPPs. I keep up with as much film as I can, paying attention to the schemes being played, the WRs getting open and what big plays are on the way. Additionally, I utilize various game stacking methods and research individual matchup history between both payers and coaches. Lastly, I formulate and use my own exclusive mathematical statistic called "Z-Score".

As the analyst that will be covering all things GPP at 4for4 this year, the following will outline my weekly process that will coincide with 4for4's already award-winning projections and DFS tools and reports. In addition to a weekly comprehensive GPP article, I will be joining TJ Hernandez on Sunday mornings at 11 am ET/8 am PT on 4for4's subscriber-only discord for a live show giving 4for4 DFS subscribers our final thoughts on the week's GPPS.

More DFS Strategy: Intro to NFL DFS | 10 Tips for New DFS Players | Cash Game Strategy | DFS Playbook: Positional Strategy Guides

4for4 Projections and Z-Score

If you read my GPP articles this year, you will see me discuss Z-Scores. The Z-Score is a statistical measurement of a score's relationship to the mean in a group of scores. In non-math terms, it displays how much better something is than the average—in DFS, I base that average on positional groups. Here's a simple example: say the average QB score in a week is 15 fantasy points and the standard deviation among all quarterbacks is 5 points—if Patrick Mahomes scores 30 points, his Z-Score would be 3.0 (three standard deviations above the average)—that gives you a significant advantage at the QB position.

The way I use Z-Score before the week is based on 4for4's weekly projections to see where the edge will be at each position. An example of a players' Z-Score that worked in my favor was Week 13 of 2020. Darren Waller—a player priced near the top at his position—had a projection that generated a 3.2 Z-Score. At QB Aaron Rodgers had a 1.7 Z-Score, WR Davante Adams had a 2.4 Z-Score, and RB Dalvin Cook had a 2.6 Z-Score, all players priced up at their respective positions. In more straightforward terms, Waller was projected to outscore the TE2 significantly more than the top players at the other positions. That advantage was going to make up for missing out on potential blow-ups from Rodgers, Adams or Cooks since other players at their positions were projected relatively close.

Z-Score is especially useful when deciding which position to pay up for, but your projection system must be accurate, which is where 4for4 comes in.

Identifying Game Stacks

Game stacking involves taking up to five players from the same game. Vegas over/unders are a tool that tells you where the high point totals will be. However, they don't tell you who scores points, so I want to focus on the general approach to finding good plays once we pinpoint high game totals.

First off, identify which offenses in the same game can take advantage of the opposing team's defense. For example, a sneak preview on a likely popular game stack for Week 1 of 2021 is the Arizona Cardinals vs. the Tennessee Titans. There is a 51-point total on paper, and both offenses should take advantage through the air based on the current cornerback depth charts on both sides. The points are likely to be scored in the passing games.

The second thing I like to look at is to compare the pricing of these game stacks vs. other popular ones. For example, if you went with a four-player run-it-back game stack on DraftKings, for the same cumulative salary you could have either Ryan Tannehill/Derrick Henry/A.J. Brown/DeAndre Hopkins or Patrick Mahomes/Clyde Edwards-Helaire/Travis Kelce/Nick Chubb—same cumulative salaries but likely very different ownership.

Lastly, the game stack has to tell a story and make sense. Continuing with this Titans example, if your idea is that the Titans get up early and ride Derrick Henry, then playing Kyler Murray, Chase Edmonds, DeAndre Hopkins, and running-it-back with Derrick Henry makes the most sense.

Game stacking isn't a perfect science, but it can lead to hugely profitable weeks.

Week-to-Week Trends

Weekly trends present advantages in daily fantasy football. Advantages vary from injuries to certain key players, recognizing potential mismatches, or seeing steady increases of opportunity for a certain player rising toward a potential breakout. For example, DK Metcalf struggled against Patrick Peterson in the Week 7 matchup with the Arizona Cardinals. Then, Metcalf proceeded to put up two monstrous performances against the 49ers and the Bills. And in Week 10, his matchup drew Jalen Ramsey, another big, fast, and physical corner—this caused Metcalf another disappointing performance. As a result, going into 2021, I will not be playing Metcalf against the similar makeup of the corners that match him well.

The Atlanta Falcons firing of Dan Quinn led to a very different Falcons defense last year. Through the first portion of the season, the Falcons were awful verse running backs and tight ends in DFS. Then they fired Dan Quinn and made Raheem Morris interim defensive coordinator. This action resulted in a significant change in how they played, leading to huge improvements against tight ends and running backs.

Opportunity drives running back production. Cam Akers is the perfect example of what more opportunities can do for you during the season. He was a must-play in late-season DFS contests last season until he got priced appropriately. Another example of this was Gabriel Davis—with the weeks that John Brown missed, Brown started to see his snaps increase and become a part of an excellent offense. His price didn't dictate it for a few weeks, and in those weeks, you could get some excellent value for a min-priced wide receiver.

Daily fantasy football is all about adapting and zeroing in on the week at hand.

The Bottom Line

• Z-Score will be featured heavily in this year's analysis, especially when deciding which positions to pay up for. Players with the largest expected gap in production between themselves and other players at their positions are those that we should allocate salary to.
• Identifying game stacks starts with over/unders but more needs to be considered such as where the points in those games are likely to come from, if there are similarly-priced stacks with probable gaps in ownership, and if stacks follow a logical game flow narrative.
• Follow weekly trends and be adaptive—changes in coaching, playing opportunity, or positional matchups should be part of weekly DFS research.
• Other notes: Don't worry about leaving salary on the table and learn to narrow you player pool—don't try to cover all of your bases.
• Have fun!