NBA Shot Chart ShinyR App

For my data science class, my partner, Alex Mandel, and I created this project to explore how NBA players shot charts. We were interested in seeing how well the top 25 NBA players perform. We look at different areas of the court and can see where they made the shot from and in different quarters or for an entire season. We downloaded and cropped our court images from Sports Illustrated . We downloaded our player data from NBA Savant and downloaded the NBA schedule from Kaggle . Finally, we scraped the NBA abbreviations from Wikipedia which helped us match a lot of our data. The app is hosted here.

Moving forward, I would like to analyze the data that we compiled and create a machine learning model that can predict what a player's shot chart will be on a particular night. I have read about existing projects that have been particular successful with these kind of predictions with deep neural nets.

-- Link to Github --
-- Link to App --

About Me

I am a computer science and cognitive science double major at Swarthmore College graduating in the Spring of 2020.
In addition, I am also fascinated by psychology, neuroscience, and nutrition. In my free time, I like to play baksetball and workout, cook, make/listen to music, and go chasing sunsets. I play many instruments, but mainly the piano and GuZheng. My favorite classical pieces include Grades etudes de Paganini by Franz Liszt, all three of Rachmaninioff's Piano Concertos, and Chopin Scherzo No.3 in C Sharp Minor, Op.39.

In computer science, I am passionate about parallel and distributed systems and machine learning applications. In cognitive science, I am fascinated by the microbiome of the gut, the psychology of language, as well as physiological psychology.

On a journey to quench my thirst for knowledge