DFS Simulator

Team Sports DFS Simulator

Team-sport DFS is the shape most players learn first: fill a positional roster under a salary cap, stack correlated players from the same game, price against a large field. NBA, NFL, MLB, NHL, WNBA, and the college + international variants all follow this template with sport-specific scoring on top. Correlated Monte Carlo simulation is where the format shines — a stack's ceiling is not the sum of its parts, and pricing the joint distribution honestly is what separates cash from GPP construction.

Why simulate team sports

Every team-sport DFS build reduces to three decisions: which players clear the salary-cap efficiency floor, which correlated groupings stack together for shared game-script upside, and how to spread portfolio exposure across enough distinct build patterns to span the winning universes without concentrating variance. The specific weights differ by sport (NFL rewards QB-WR pairs; MLB rewards 4- and 5-batter team stacks; NBA rewards game-total pace-up plays) but the framework is the same, which is why the same simulator engine powers every team-sport slate with per-sport correlation matrices and per-site scoring configs.

Every team sports we cover

11 sports in this category — per-sport pages cover scoring, strategy, and site-specific configuration.

Frequently asked questions

Which team sports have the biggest DFS contest catalogues?

NFL Sundays, NBA nightly slates, and MLB main slates — in that order by prize-pool volume. NHL, WNBA, and CFB run smaller but sharper fields. The four US majors together account for over 90% of team-sport DFS entry volume.

How do team-sport DFS rosters differ across DK, FD, and Yahoo?

Positional slots vary slightly (DK's UTIL flex vs FD's G/F/UTIL in NBA; DK's 10-player MLB roster vs FD's 9), salary caps differ ($50k on DK vs $60k on FD), and stacking rules cap max-per-team differently. The simulator's per-site config handles all three so a projection loaded once works across every site.

Why is stacking so central to team-sport DFS?

Because scoring events are shared between correlated players — a QB's touchdown is his receiver's touchdown; a hitter's run is his teammates' RBI. The joint distribution of a stack is heavier-tailed than the sum of independent players, and that tail is what wins tournaments.

Which team-sport DFS blog post should I read first?

If you're new: 'NFL DFS Strategy' or 'NBA DFS Strategy' for your primary sport. Then 'MLB DFS Stacking' for the correlation math that generalizes to all team sports.

Other DFS categories

Simulate team sports

One engine, 11 sports, correlated Monte Carlo.