Sports analytics are a constantly growing field, but little work has been done to incorporate analytics to video games. This summer through my project, I wanted to see if similar tools that are used in professional sports could be applied to sports video games, specifically to predict Rocket League game outcome. I utilized a variety of statistical learning methods to investigate which statistics were most positively or negatively associated with winning, and built a random forest model that classified games as wins/losses correctly with almost 90% accuracy. Additionally, through different variable investigation I was able to begin to identify which strategies proved to be more and less effective at the professional level. My project helps to demonstrate that as the world of esports continues to constantly evolve, there is a growing potential for data-driven analysis to help strategize, coach, and change the way people think about competitive video gaming.