In the age of big data, the field of sports analytics is becoming increasingly transdisciplinary, combining domain specific knowledge from sports management with the statistical and computational tools of data science. Golf is a sport that generates massive amounts of data with no shortage of opportunity for analysis. As statistics becomes more integrated into professional sports, having an analytical edge gives both athletes and teams a competitive advantage. In fact, many PGA Tour champions have credited their success to analysts that give insights on how to succeed at upcoming tournaments. The goal of the project is to use machine learning to predict the performance of professional golfers. This end-to-end machine learning project involves web scraping, data manipulation, exploratory data analysis, model training, model optimization, model evaluation and predictive modelling.