The NCAA conducts 90 championships annually across three divisions and over twenty sports. To enhance and celebrate the student-athletes’ experience, as well as offset the cost of the championships, the NCAA actively markets and sells tickets to the events. As part of the marketing efforts, the NCAA maintains a list of past and potential customers. Is it possible to use the information the NCAA has on customers, along with external data, to predict whether or not a customer will purchase a ticket? And if so, will the ticket be purchased on the primary or secondary market? Students will utilize datasets of Division I Women’s Basketball customer data coupled with target labels for creating their predictive models. Included in the dataset is a wealth of information about the customer, but students are encouraged to integrate external data to improve the predictive power of their models.