In this Major Qualifying Project (MQP), we partnered with the online sports betting company DraftKings to develop a process that assisted in setting odds for live propositional bets. With a focus on baseball, and more specifically the outcome of an at-bat, the goal of our project was to predict the likelihood of an at-bat outcome before assigning odds for that event. Working with data retrieved from the MLB API, our finalized dataset contained 16 features with over 80 thousand rows of data. Utilizing this dataset and machine learning models such as a Random Forest Classifier (RFC), K Nearest Neighbors (KNN), and Decision Tree Classifier (DTC) we were able to run various tests on model accuracy, which were used as the foundation for generating actual odds for each play.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Pandit, Kaustubh Vivek
• Yan, River
• Ardhaldjian, Ardavasd

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-042722-184548
• 64646

Keyword

• Data Analytics
• Baseball
• DraftKings
• Machine Learning
• Live Propositional Bets

Advisor

• Brown, Donald R.
• Paffenroth, Randy Clinton

Year

• 2022

Sponsor

• Brandon Ward (DraftKings)

Date created

• 2022-04-27

Resource type

• Major Qualifying Project

Major

• Data Science
• Computer Science

Rights statement

• In Copyright