Publication Date
2019
School
School of Engineering and Computational Sciences
Major
Computer Science
Keywords
Machine Learning, Fantasy Sports, Basketball
Disciplines
Other Computer Sciences | Theory and Algorithms
Recommended Citation
Earl, James, "Optimaztion of Fantasy Basketball Lineups via Machine Learning" (2019). Senior Honors Theses. 836.
https://digitalcommons.liberty.edu/honors/836
Abstract
Machine learning is providing a way to glean never before known insights from the data that gets recorded every day. This paper examines the application of machine learning to the novel field of Daily Fantasy Basketball. The particularities of the fantasy basketball ruleset and playstyle are discussed, and then the results of a data science case study are reviewed. The data set consists of player performance statistics as well as Fantasy Points, implied team total, DvP, and player status. The end goal is to evaluate how accurately the computer can predict a player’s fantasy performance based off a chosen feature set, selection algorithm, and probabilistic methods.
