Visualization and analysis of NBA player tracking data

NBA API Documentation

Visualizations to better understand NBA shooting tendencies and efficiency and classification models to predict shot outcomes

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

An R Shiny app to help make betting decisions for FanDuel player props

NBAShotTracker is a data visualization tool to track player shot performance.

Displaying team performance against player rotations during NBA games

stats.nba.com library :basketball:

Interactive exploration of NBA roster turnover

本项目综合运用d3、echarts来完成可视化工作，实现了对nba两场比赛的可视化数据分析，包括球员运动轨迹、个人数据、传球次数以及得分位置等多种可交互式图表。通过可视化方法，我们能够进一步深入分析球队的具体情况，便于制定更佳的战术。

An implementation of six degrees of separation for mutual NBA teammates.

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

Analysis of NBA player stats and salaries of the 2016-17 for the 17-18 season

Find basketball players with similar shot charts

visualization course project

A working workbook looking at physical demands of plays in NBA using SportVU legacy data.

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

Visualize the NBA Playoffs

Web application to see latest NBA news and stats

Project folder for all my Jupyter Notebooks and NBA data.

A Front-End project to show the hot shooting points of NBA players to help analysis.

NBA player shot selection dashboard

NBA scoreboard web scraping using Python's selenium and Bucks 10 first games analysis

A NBA player data explorer web app in Python using the Streamlit library

Source plugin for pulling NBA data into Gatsby 🏀

对NBA常规赛（2016-2017）中平均得分TOP30的球星的做了热图和雷达图的可视化分析

NBA Shots visualization

3D visualization of basketball shots using plotly and NBA shot chart data

Visualizing NBA margins of victory for 2016-2017

Estimating player value based on Win Share and Salary data