•Utilized a variety of prediction strategies to determine the number of yards a rusher gains in an NFL play based off initial play characteristics and player positions
•Main strategy built around native algorithms for Pursuit Vectors and realistic physics simulations in Python
•Merged original data from NFL with Madden skill data to enhance realism of simulations
•Combined simulation predictions with Machine Learning based methods such as KNN Regression to strengthen overall model
•Worked in tandem with fellow Senior Undergraduate Researcher and Machine Learning Professor