Fantasy Football Analytics Projections: How to Correlate

What do we do with analytic data to support decisions made in fantasy football?

Don’t worry I won’t bore you with the analytics since i’m not a math major nor set out to be one, but will put this into simple terms as it relates to fantasy football and other sports as the info you really need is readily available in the resources below.

When you set up to win, you should constantly be testing for better
results and application of the processes you use to win in daily
fantasy sports.

When you learn how to correlate, you recognize the difference between
a correlation and just a number.

There are correlation factors in many stats of the analytic game.
Rushing attempts always correlate to rushing yards, in fact more then
any other statistic in football. Then targets correlate to receiving

Nothing really correlates in the touchdown department from year to
year or week to week, unless they have a good red zone percentage
going for them, which means the team is using the player fairly
consistently within the 20, 10, and goal line downs. A team may very
well go to a player they frequently go to at any position, especially
with the game on the line or in the playoffs.

Another correlation is with winning teams. Winning teams likely run
the ball for a while with their #1 back, especially at home, as teams
always do better winning at home. The correlation will be seen in
their up tic in rushing attempts, all correlating nicely together for
your fantasy outlook.

When correlating, you must begin with players who are obviously likely
to score points together. These include the Quarterback with his receivers, mostly the WR and TE positions.

This works in other sports as well. In fact very well in the success I have seen recently in NHL Hockey.. if you would like a breakdown of how I placed 1st in a recent tournament on fanduel, out of 7k+ players, check out my breakdown here for my NHL DFS GPP Strategy.

Here is a spreadsheet for the what the layout looks like when correlating players from opposing teams.

fantasy football analytics projections
Displaying the Correlation Matrix Spreadsheet

When using a correlation sheet, you simply follow the columns of the players you want to use so that you can see if they have a red or green or neutral correlation. You can get the sheet at or by clisking on the sheet itself. I explain some things to look for in this video:

If you notice I also show the fantasy football algorithm sheet used by draftdashboard. They have an interesting way of rankings by comparison to the latest sheet for the week for the divisional round playoffs. There is no correlation sheet on this site, however, you can go to the “browse by teams and look for the top 6 otpimal plays by team on this screen, giving you a better chance to obtain 2 players from the same team such as Rivers with Allen this week for Los Angeles.

fantasy football correlation

By the way, here is my fantasy football rankings by position post for my best plays by position.

To note: You can get rankings as well on

However, its better to get projections, reflecting the analytics as well as the human reason for coming up with practical rankings based on these projections, of which I find are best at the such as Big Marley’s Draft Kings Player Pool.

And of course the latest Research Station for the Week, as its finished as of this writing. Big Marley’s player pool should be updated tomorrow as its better to wait a day before the main slates play on the dfs sites. For Fanduel, Geek’s Player Picks are Best with his breakdown.

Any questions for comments about fantasy football or other sport analytics in general? Or even for this Divisional Playoff? Go ahead and comment below

2 thoughts on “Fantasy Football Analytics Projections: How to Correlate”

  1. I have been researching the internet for the past two days so I can choose the best positions and stuff. It has been really hard for me to decide. But this article helped me out in a very big way. It has the best positions and I am going to follow it for sure.

    Thank you for posting this.

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