Researcher ORCID Identifier
0000-0002-7432-1371
Graduation Year
2022
Date of Submission
4-2022
Document Type
Campus Only Senior Thesis
Degree Name
Bachelor of Arts
Department
Economics
Reader 1
Yaron Raviv
Terms of Use & License Information
Rights Information
© 2022 Dhruv Narula
Abstract
Over the past few years, fantasy sports have become increasingly prominent, becoming a multi-billion dollar industry with future growth still expected. Millions of people from all around the world play various fantasy sports games, with one example being Fantasy Premier League (FPL). Various studies of different natures have been conducted to aid users (or ‘managers’) to perform better in FPL. This study aims to do so by creating an improved version of The Scout by forecasting future points for 364 unique players based on four position-wise linear regression models trained on one year of past data of the same players. Through the use of linear optimization, 38 weekly teams will be created with the goal of maximizing total points while adhering to various constraints, such as number of total players, number of players per position, etc. The aim is that such a study will serve as a helpful resource for FPL managers, FPL content creators, and the creators of FPL itself.
Recommended Citation
Narula, Dhruv, "Fantasy Premier League: Forecasting Future Points and Creating Optimal Weekly Teams to Outperform The Scout" (2022). CMC Senior Theses. 2969.
https://scholarship.claremont.edu/cmc_theses/2969
Data Repository Link
https://github.com/vaastav/Fantasy-Premier-League/blob/master/data/cleaned_merged_seasons.csv
This thesis is restricted to the Claremont Colleges current faculty, students, and staff.
