Statistical and Machine Learning
Faculty and Student Research Collaborations
Machine Learning for Fantasy Sports Betting
A student-led project, led by Penn State Statistics graduate student Isaac Wright, together with undergraduate students Mallet James, Jeffrey Lunger, and Kyle Kroboth, and advised by Associate Teaching Professor of Statistics Dr. Andrew Wiesner, have developed a software that uses Machine Learning (ML) applied to daily fantasy sports betting. With the fantasy sports industry projected to grow to $48 billion by 2027, it is not hard to imagine that ML tools and software could provide a value-added service by operators. “As a group who enjoys both playing fantasy sports and machine learning, it felt natural to build a project around our dual interest,” says Isaac. Thus, the idea of building consistent winning fantasy sports lineups for the Major League Baseball through a data-driven approach was born.
This student-led project has already yielded concrete results. The group created a website for people interested to follow their results and progress, and they also plan to release an interactive web app where people can play around with building their own fantasy sports lineups using the group’s algorithms. The project, however, was not without challenges. After a few weeks since the start of the project, Penn State shifted to remote learning and because of adapting to the working environment and life during COVID, the project was put on pause for several months. After restarting, the project was scaled back from building software for the MLB and NFL to building only the MLB software.
According to Isaac, the most rewarding aspect of the project was watching everyone come together and give time to the project, driven by their passion for sports and data science. “The true beauty of such projects,” writes Dr. Wiesner, “is that the success falls solely on the self-motivation of those involved. There is no money, no credit, just the willingness to learn and improve their analytical skills.” As for the future, the team has big plans; they have talked of building a company around the proprietary software or writing a paper and making everything available through the blog. Either way, they are excited to see what they can do.