NBA Daily Fantasy Sports EDA and Player Modelling with R

NBA Quote Generator

Node application using D3 to Analyze Data from the NBA

Using machine learning libraries to analyze NBA data

2017 Example NBA basketball website using nba_py for people to learn how to use NBA Stats Python API.

Nba Watson

predicting next season's statlines

#rstats R project for experimenting with machine learning using NBA data (circa 2016)

Only NBA tweets from ESPN Stats & Info https://assafmo.github.io/nba-espn-stats-and-info

CMSC 320 (Introduction to Data Science) Final Tutorial Project (UMD Fall 2018)

NBA

A data science and machine learning project that attempts to predict the ideal player attributes for a top NBA Draft pick using supervised learning and a linear regression model, built using the NBA Data API, Python, NumPy, Pandas, and Sci-Kit Learn.

NBA Player of the Week Visualizations using ggplot

Website application that consolidates real-time stats and social media updates for various sports teams.

NBA Player of the Week & Salary Prediction using Scikit-learn

Simulating the rest of the 2019-2020 NBA season

Calculating Regularized Adjusted Plus-Minus (RAPM) with R

Web app that leverages Flask backend to pull wealth of data on NBA players in clutch circumstances directly from NBA.com and visualizes it in a comprehensible manner, allowing users to settle the age-old argument: who's more clutch?

Who had the hardest/easiest NBA season?