# Correlations in Fantasy Football

Last updated: July 27th, 2020

## Correlation: fantasy points between players in the same NFL game are related

In a real life NFL game, fantasy points are related.

An easy example: a QB throws a touchdown to his WR1, and they both get points.

Correlation is just the tendency to move together. If you knew NOTHING about
a GB game, but saw Aaron Rodgers put up 500 yards and four touchdowns, you'd
expect Davante Adams to have also had a better game than average, right?

It's not for sure (maybe Davante got hurt early or Rodgers threw all his TDs
to other guys), but it

tends

to happen.

#### Correlation is measured from -1 to 1

The correlation between two pieces of data (Rodgers points, Davante Adams
points) is usually measured on a scale from -1 to 1, where 1 means the two
move perfectly together, -1 means the two move perfectly in opposite
directions, and 0 means they aren't correlated at all.

The QB-WR1 relationship is one of the strongest in a football, at about 0.40.
The only one stronger is the

negative

correlation between a QB and the DST
they're facing, which is about -0.60.

#### All players in a game are correlated to varying degrees

The QB-WR1 correlation is easy to understand. A more subtle example: QBs
facing each other in the same game are positively correlated at about 0.20.

Sometimes

(not always, otherwise the correlation would be higher), teams
will get in a shoot out, and both QBs have to air it out to keep up. Other
times, the weather will be awful, and no one can pass the ball downfield.

While any correlation is a single number between two pieces of information, we
can look at

simultaneous

correlations using a matrix, like this:

To see the correlation between any two positions, just look at ROW and COLUMN
of the position you're interested in.

For example, to check the correlation between a WR1 and the opposing QB, we
look at the WR1 row and follow it over till we see the OPP QB column. It's
0.09, which is small, but not completely independent.

#### Correlations + Distributions

The Fantasy Math model works by (1) taking thousands of draws of randomly
generated data following the correlation rules above, then (2) feeding it
those draws through the modeled

probability distributions

.

The result let's you factor in correlations when calculating win probabilities
or making who do I start decisions. You just look at all the thousands of
(correlated) simulations, and see how often you win or start whoever maximizes
your chances.

#### How Correlations Impact Your Matchup

Imagine you have a close call — say Tyler Lockett vs Stefon Diggs — and your
opponent is starting Russell Wilson.

The fact Wilson and Lockett's points are positively correlated might affect
your optimal decision. Precisely HOW it affects your decision depends on the
rest of your matchup:

•

if you're heavily favored, the correlation might mean you should start Lockett as a hedge against Wilson blowing up

•

if you're the underdog, maybe you need Wilson to underperform AND Diggs do really well to have any chance at all, which means Diggs maximizes your probability of winning

That's a simple scenario, but it can easiliy get more complicated. For
example, maybe you're heavily favored (so correlations suggest Lockett), but
you actually have Diggs as slightly better. Is an opportunity to hedge against
Wilson worth starting someone with a lower expected points?

And what about any other correlations in your matchup?

The model takes all this into account. You don't have to think about it or
weigh the trade offs subjectively, it's all factored in.

#### Model Out Soon

The full Fantasy Math model that lets you keep track of correlations across
your entire matchup will be out soon. Enter your email below to hear when it's
ready.

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