An R package to quickly obtain clean and tidy men's basketball play by play data.

Stattleship R Wrapper

R wrapper functions for the MySportsFeeds Sports Data API

Scraper for NBA data

A conceptual dashboard to visualize Expected Possession Value (EPV) in the NBA.

Code for the article "Adjusting for Scorekeeper Bias in NBA Box Scores" published in DMKD and presented at Sloan.

R package to interact with NBA api

Predict the best lineup combination for each NBA team based on player clusters and and historical 5-man lineup performance.

Classification on the Kobe Bryant Shot Selection dataset (https://www.kaggle.com/c/kobe-bryant-shot-selection/data) using Decision Trees

Build an R Package that can construct an NBA Shiny App

Predicting NBA salaries using machine learning through R. Clustering players based on stats to determine player type in an increasingly position-less era of basketball.

A R Script to read Play by Play data and turn it into Offensive and Defensive Ratings

NBA Player HUD RShiny Application

Data Analysis and Visualizations on the Basketball Dataset using R Programming

Unsupervised learning Project - NBA players clustering

Use R and python to build a dashboard to analyse NBA data

R | Collection of analyses & visualisations done on various NBA datasets

With the NBA bubble in Orlando, which teams are being spared the most/least from traveling to opponent arenas?

Project dealing with NBA salaries and contracts, researching the best way to allocate salary. See Final Paper and Presentation, R Shiny App and website below for results.

my dabbling in R and data analysis, predicting All-Star potential for players in the 2017 draft