DFS Dashboard provides actual probability information so users can make pragmatic decisions for DFS lineups and sports betting. 

I have created an AI algorithm that creates simulations of 1,000 outcomes and determines all of the lineups that provide a a greater than 20% chance to finish in the top 20% of a GPP contest.

The following dataset represents a simulation-driven approach to DraftKings Showdown lineup construction, built entirely from DFS Dashboard projections and evaluated through 1,000 player-level Monte Carlo simulations. Each lineup is anchored by one of three high-impact captains—Christian McCaffrey, Jonathan Taylor, or Brock Purdy—and is required to meet strict salary constraints while demonstrating probabilistic strength. Rather than relying on raw projections alone, lineups are judged by how often they finish in key percentile bands (Top 1%, 5%, 10%, and 20%) relative to the full lineup pool. Only lineups that finish in the Top 20% in more than 20% of simulations are retained, ensuring that every entry in the file has both ceiling access and distributional consistency.

From a strategic perspective, the data highlights the trade-off between upside and stability across captain archetypes. Running back captains such as McCaffrey and Taylor tend to produce higher first-place equity, showing stronger Top 1% outcomes when game scripts break correctly, while quarterback captains like Purdy generate a larger volume of lineups that repeatedly land in the Top 10–20% range. By pairing detailed salary allocations with finish-rate metrics, this dataset allows players to move beyond “best projection” thinking and instead build portfolios intentionally—balancing risk, correlation, and payout structure. In short, these lineups are not just valid; they are empirically vetted for how tournaments are actually won.