MSCI446 Term Project: Every June, the basketball world tunes into the NBA Draft, an annual event hosted by the National Basketball Association (NBA) in which the league’s teams draft players from a pool of young and promising talent. Using the NBA Draft to select the “right” players is an essential skill amongst all successful NBA teams, and is deservingly so a very difficult skill to master. It allows successful teams to invest in their future and poor-performing teams to rebuild. It is known that an athlete’s background and career prior to playing professionally are the greatest determinants of their future careers in the game. A team’s performance every season is heavily dependent on this influx of new talent as well, placing pressure on the league to ensure that the best talent from all corners of the world are being recruited. As such, we present a multiple linear regression model to predict player standings within draft classes. Additionally, we have implemented a clustering algorithm to identify the skills that make up the top players in the league today, as well as identify where efforts should be focused to garner further international interest in the sport.