Brawl Stars is a real-time battle-royale-style mobile game that is enjoyed by millions around the globe. Recent match history is available through the Brawl Stars API. The objective of my project was to build a recommender system to provide players insights about how to maximize their likelihood of winning a match. Population win rates serve as the foundation for the recommendations, but where individual history is available, adjusted Wald confidence intervals are used to test whether individual win rates are statistically significantly different from the population win rates. The results of this analysis are then used to further enhance the recommendation to the player. Three different recommendation algorithms were created, each containing a different mix of population data and individual data. Once tested, these were built into a Flask web application. Through this interface, players anywhere can query the database to receive personalized character recommendations. The web application can be found here: https://brawl-stars-bvsfa.ondigitalocean.app/, but it may migrate to a different domain after June 2021.