(CROSSROADS CLASSIC ANALYTICS CHALLENGE https://crossroadsclassicanalyticschallenge.com/)
This project aimed to predict ticket purchases and identify whether tickets would be bought on the primary or secondary market for NCAA Division I Women’s Basketball. The methodology included data exploration, feature engineering, and model building. Our final model was Gradient Boosting, which secured 8th place out of 54 teams from 4 universities. Results were visualized using Tableau to highlight key trends and the model's effectiveness in predicting ticket purchases.
A presentation file can be found here: https://github.com/YHL996/CCAC/blob/main/Multipurpose%20Presentation.pdf