In July 2018, Steven Cao and applied to the 2018 NBA Hackathon. We had to answer two questions:

1. Basketball Analytics: For each player in each game listed in the given data, calculate the plus/minus, defined as the team’s score differential while the player is on the court.
2. Business AnalyticsGiven viewership data for 1000 games across two NBA seasons, predict the total international viewers for 460 other games.

You can find the Github repositories for the hackathon application here:

Last year, I had used Excel VBA to run scripts on the data, not knowing there were much more efficient data science tools out there. This year, I learned how to use the pandas package to analyze the data, producing a more elegant result. Even though we were not accepted to the hackathon, it was encouraging to see how my data science skills have progressed from only a year ago.