An R package to quickly obtain clean and tidy men's basketball play by play data.
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Updated
May 7, 2024 - R
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.
R package to interact with NBA api
Code for the article "Adjusting for Scorekeeper Bias in NBA Box Scores" published in DMKD and presented at Sloan.
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
Data Analysis and Visualizations on the Basketball Dataset using R Programming
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
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
Unsupervised learning Project - NBA players clustering
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