Build and analyze DFS stacks with correlation and ceiling projections
Stack Ceiling = Base Projection + 1.28 × √(Σ Var + 2 × Corr × Cov)Configure your correlated player stack
3-player stack evaluation
Stack Projection
50.0 pts
Stack Ceiling
64.6 pts
Stack Floor
35.4 pts
Variance Boost
+64.0%
Common DFS stacking scenarios
TL;DR summary
Stacking groups correlated players to maximize upside. The classic NFL stack is QB + 2 WR from the same team (~35% correlation each). Stacks increase both ceiling and floor variance - essential for GPPs but risky for cash. Target teams with high implied totals (27+ points) for optimal stack environments.
Important things to know
Common stacking questions
The optimal GPP stack is typically QB + 2 WR from the same team, optionally with a bring-back WR from the opposing team. This creates double correlation: same-team correlation plus game stack correlation from high-total environments.
3-4 players for NFL GPPs (QB + 2-3 pass catchers). NHL benefits from full 3-player line stacks. MLB stacks work best with 4-5 hitters. More players = higher variance, better for large-field GPPs.
Cash games favor independent player selection over stacks. Low implied totals (under 24 for NFL) make stacks less effective. Avoid stacking when primary stack pieces are heavily owned - you need differentiation.
A bring-back is rostering a player from the opposing team in your stack. It creates a game stack that benefits from high-scoring games regardless of which team dominates. QB + WR from Team A, then WR from Team B = game stack correlation.
Look for high Vegas totals (52+ combined for NFL), pass-funnel defenses, indoor games, and competitive game scripts where neither team will run out the clock. Weather, pace of play, and defensive weaknesses all factor in.