One of the most important concepts that advanced daily fantasy sports players use with team selection is correlation.

By definition, correlation refers to the relationship between two variables. In DFS, this can apply to a number of different factors such as team matchups, positional changes, game strategies, weather and, most commonly, between players.

When selecting your DFS lineups, you always want to think about which players will be most suited to whatever variables are offered. This is where correlation comes in.

The most common situation for correlation in DFS is finding players that are most likely to perform well together. For example, in the NFL there is a strong correlation between a quarterback and his wide receiver. If the quarterback has a good game, it is likely that his wide receiver will also have a good game. Or if you’re looking at the AFL and find a team that likes to share the ball in their backline, then you could play multiple defenders from the same team in the hope they will play kick-to-kick with each other and stack up the points. If one has a good game, then there’s a positive correlation that the other will also go well. This might also be dependent upon whether the opposition like to press forward or shift their defence back.

Another example might be the structural changes when a player is out injured or returning to a lineup. Correlation can be either positive or negative between the players as their role changes. In basketball, it might be the difference between a starting role and extra minutes for higher fantasy scoring, or being shunted to a backup role on the bench and limited minutes.

By understanding correlation, DFS players can also avoid making the mistake of including players who are likely to perform poorly together. For example, you may not want to include a quarterback and a defence from the same team in the same lineup. If the quarterback has a good game, the defence is unlikely to score many points.

In addition to helping DFS players make better selections, correlation can also help to manage risk. Selecting players who are highly correlated can be a bit of an all-or-nothing strategy. That’s not a bad thing in big tournaments, but sometimes you may want to reduce your risk by diversifying your lineup and including players who are not as strongly correlated. For example, if you load up on two forwards from the same AFL team and their team loses badly, then it’s likely your selections will both perform poorly.

You can make use of our Data Tools here on Daily Fantasy Rankings to look at the historical stats and analyse the correlation between players in the most popular sports.

Correlation is a critical tool for DFS players. By understanding the relationship between different players, you can make better decisions about which players to include in lineups to either maximise your chances of winning or manage your risk. While it may seem complicated at first, it’s important to start to think about these factors and learn to use correlation to your advantage to increase your chances of success.


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