CFB Optimizer

The tool ingests player projections, salaries, and roster constraints to construct optimal college football fantasy lineups. It targets fantasy players, analysts, and roster managers who evaluate slates across multiple sites and seek repeatable, data-driven decisions before deadlines. Data quality and freshness are essential for reliable results.

Conceptually, the engine assigns a value to each candidate based on projected points, volatility, matchup context, and exposure preferences, then solves a constrained optimization problem to maximize total expected points while respecting salary caps, position requirements, and contest-type constraints. It uses a MILP formulation with discrete selections and linear constraints; tie-breakers can favor sleepers, correlation, or diversification.

Who benefits: casual players aiming for stronger lineups, professional analysts running backtests, and researchers evaluating strategies across slates, sites, and formats. The tool's unique value is a transparent, reproducible workflow that can scale to large pools, incorporate scenario comparisons, enforce complex rules, and deliver consistent exports for further analytics.

Core features include salary-aware optimization, flexible position grouping, constraint controls (caps, stacking rules, exposure limits), scenario comparison dashboards, and export options for CSV/JSON. Use cases cover cash games, tournaments, and slate analysis across college football DFS. The design emphasizes reproducibility and batch processing for iterative experimentation.