Create NBA shot charts using data scrapped from stats.nba.com and R package ggplot2.

Stattleship R Wrapper

Scraper for NBA data

How does playing in the Olympic Games impact a player's following NBA season?

Uses Random Forest to predict NBA players' positions based solely on their in-game statistics.

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

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

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.

Using KMeans clustering and a decision tree classifer to select players who maximize a team's strengths in fantasy nba h2h category leagues.

R package to interact with NBA api

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

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.

An app to visually explore the density (and other related factors) of the schedule for NBA teams.

Bayesian Regression Analyses from scratch - NBA data example

NBA Player HUD RShiny Application

Build an R Package that can construct an NBA Shiny App

R wrapper functions for the MySportsFeeds Sports Data API

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

Complete Project on Extraction, Management, Prediction, and Profitability Analysis of NBA Games. Fully based on R.

Clustering NBA players and teams through Model-Based methods