WR And RB Receivers Who Could Outperform Projections In Week 1
At the heart of being a successful NFL Daily Fantasy player, is having access to a strong set of projections. However, no matter how much computational power or thought going into them, DFS projections are not an exact science. There will be weeks they are spot on and others that are way off. A better way to approach projections is what we call a range of outcomes. Without even thinking about it, many DFS players use this concept when they use player and team averages to help them set their lineups.
For example, in 2020 Tom Brady averaged 289.6 passing yards per game. With this data point, it would not be unreasonable to assume that Brady will throw for between 260 and 320 yards in week 1. “After all, models and projections are just based on averages anyway”. Experienced DFS players count on their opponents to stick to this surface-level thinking as they dig deeper into what the data says.
When choosing a player for a fantasy lineup, we do so in the belief that they will have a “good game”. However, this term means different things for different players. And, each player has shown a historical likelihood to have a “good game”.
This is what we attempt to quantify when talking about a player’s range of outcomes. Using Tyreke Hill as an example, here’s a simple way to think about this concept.
Statistically, what does a bad, average, and good performance look like for Hill?
Statistically, how likely is Hill going to have a bad, average or good performance?
Only when we have this data are we able to get a sense of what we refer to as a player’s “floor” and “ceiling”. In the perfect world, a lineup would be filled with individuals with both high floors and ceilings. In reality, the great equalizer known as the salary cap forces us to make sacrifices.
High Upside Revisited
The traditional way of thinking about high upside players is they are essentially lottery tickets. Most likely, they will disappoint but if everything comes together, they could be the reason we win the contest. And, they came cheap! A common way this plays out is selecting a wide receiver who doesn’t get a lot of targets but has had a few long TD receptions. But, before rounding out a roster with someone who first this mold, it is better to first rethink the concept of upside.
As opposed to equating upside with finding 1 cheap player, a better strategy is to build an entire lineup with players who have the best chances of having a “good game”. And, whose “good games” are actually needle-moving fantasy performances.
Identifying Upside Walkthrough
The table below shows, leaders in fantasy scoring potential in strong statistical games. This is relative to their own performances. In other words, if Derrick Henry were to have a good game, we could expect it to be around 25 FPTS. This was good for the top spot in 2020
Note- Fantasy points and projections in this data are only related to rushing statistics.
Where the data gets interesting is when you look at how often games in this range of outcomes actually took place. According to the data, we can expect these players to put up a fantasy score in this vicinity around 25% of the time.
|Player||Fantasy Score||Great Game Percentage|
Add on each player’s DFS salary to the equation and you are now able to see how much a player’s upside is going to cost.
|Player||Fantasy Score||Great Game Percentage||Salary|
Now, with an actual number assigned to a good performance, how likely it is to happen, and the player’s cost, we are better equipped to bring in our additional research and make a winning pick.
RB Upside Cheat Sheet
The process I use for identifying upside candidates is to use a combination of top-end performances and likelihood. I immediately rule out any players whose projections are more than 25% away from what is considered a good performance. This means this player would have to significantly outperform their projections in order to come close to having a good game.
Week 1 RB To Avoid
Jonathan Taylor – My projections show Taylor only putting up getting 10-12 carries for 50 yards in week 1. In 2020 a good game by Taylor meant only 12 FPTS. This is a classic example of limited upside.
Aaron Jones- Jones was a touchdown machine last season but Jones would have to outperform his projections by 39% to put up a good game.
James Conner- In 2020, a top-end performance from Conner meant around 11 FPTS. Given that it is unclear who will receive the majority of the carries in Arizona, it is best to stay away from the Cardinal backfield altogether.
RB’S Who Ranked: Good Game Frequency
A common strategy in DFS cash games is to target players with higher floors. The players from the following table were able to put up strong individual performance over 25% of their games.
|Player||Fantasy Score||Rushes||Yards||TD||Great Game Percentage||Salary||Points Projected||% Increase For Good Game|
James Robinson- Robison projects to provide a good mix of top-end scoring upside, a nearly 29% track record of strong performances all for the price of $5900.
Alvin Kamara – Despite the big price tag, the Saints will find ways to feature Kamara as much as possible. Look for Kamara to put up a huge game against the Packers.