Optimizing Daily Fantasy Baseball Lineups: A Linear Programming Approach for Enhanced Accuracy

TL;DR

This paper develops a linear programming-based lineup optimizer for daily fantasy baseball, aiming to improve the accuracy of lineup selection and assist participants in winning more often.

Contribution

It introduces a novel linear programming approach to optimize daily fantasy baseball lineups, enhancing the accuracy of current strategies.

Findings

Linear programming improves lineup accuracy

Python implementation enables efficient optimization

Potential for increased winning probabilities

Abstract

Daily fantasy baseball has shortened the life cycle of an entire fantasy season into a single day. As of today, it has become familiar with more than 10 million people around the world who participate in online fantasy. As daily fantasy continues to grow, the importance of selecting a winning lineup becomes more valuable. The purpose of this paper is to determine how accurate FanDuel current daily fantasy strategy of optimizing daily lineups are and utilize python and linear programming to build a lineup optimizer for daily fantasy sports with the goal of proposing a more accurate model to assist daily fantasy participants select a winning lineup.