DFS Correlation Calculator
Calculate stack variance and ceiling boost from player correlations
Combined Variance = Var(A) + Var(B) + 2×Correlation×StdDev(A)×StdDev(B)Correlation Analysis
Enter two players to analyze stack potential
Stack Analysis
Combined projection and variance
Stack Projection
35.0 pts
Stack Ceiling
47.6 pts
Stack Floor
22.4 pts
Ceiling Boost
+1.8 pts
Variance Comparison
Correlation Examples
Common DFS correlation scenarios
Quick Answer
TL;DR summary
Correlation measures how two players' scores move together. Positive correlation (0.2-0.5) means both benefit from the same game script - ideal for stacks. Negative correlation (-0.1 to -0.3) means one benefits when the other doesn't. Understanding correlation is essential for building GPP lineups with correlated upside.
Key Correlation Facts
Important things to know
- Correlation ranges from -1 (opposite) to +1 (identical movement)
- QB-WR same-team correlation averages 0.30-0.40
- Stacking positively correlated players increases variance
- Negative correlations are useful for fading scenarios
- Game stacks (both teams) have mild positive correlation
- Higher variance lineups perform better in large GPPs
- Cash games prefer low/no correlation for consistency
- Correlation compounds: 3-player stacks have higher combined variance
Frequently Asked Questions
Common correlation questions
What is correlation in DFS?
Correlation measures how two players' fantasy scores move together. A correlation of +0.35 means when Player A exceeds their projection, Player B likely does too. This relationship is driven by shared game script (both benefit from pass-heavy game flow).
How does correlation affect lineup variance?
Positive correlation increases lineup variance (ceiling and floor). When correlated players boom together, your lineup explodes. When they bust together, your lineup tanks. This variance is valuable in GPPs where you need to beat thousands of entries.
What are the most correlated positions in NFL?
QB-WR from the same team (~0.35 correlation), QB-TE (~0.25), and same-team passing game players. Game stacks (QB + opposing pass catchers) have ~0.20 correlation as shootouts benefit all passing game players.
Should I use correlation in cash games?
Generally no. Cash games reward consistency over upside. Independent player selections provide a more stable floor. Save correlation stacks for GPPs where you need to differentiate from the field and hit ceilings.
How do I use negative correlations?
Negative correlations create natural hedges. If you roster a DST, consider fading their opponent's RB (negative correlation). If you roster a pitcher, you're naturally fading opposing hitters. Use this for game theory plays.