NBA-Analytics

Author: Chris Young

Project Description

This project was created as part of an assignment for IS 542. NBA-Analytics is my own version of ESPN or NBA.com where fans can come and see statistics and team/player performance for the current season. In future versions, users will also be able to view live scores for NBA games as they are played.

Data

Data for this project was obtained from a Python package called sportsreference. This package scrapes data from Basketball-Reference, a site that tracks advanced statistics for sports, particularly the NBA. This package can be called by running the following commands:

• pip install sportsreference
• from sportsreference.nba.teams import Teams
• utah = Teams('UTA')
• Then team attributes, like a dataframe of statistics can then be accessed by utah.dataframe

API

To access this data from my React project, I created a python script that would go and collect stats from each team, game, and player available from the package. I then utilized an EC2 instance to execute this script daily (a cron job), and rewrite JSON files that I could access at a server endpoint on the EC2 instance. I pulled these JSON files into my application through axios

Architecture

This project required:

• AWS EC2 t3.micro instance
• Python script/cron job running on server
• JSON data transformation/manipulation
• React application
• React context
• React-router-dom
• React-bootstrap
• React-chartjs-2
• React-select
• Deployment via BYU subdomain

Features

This project includes the following features:

1. Dashboards for each team showing a line chart trend of games played and points scored by the home/opposing teams. Team dashboards also include cards showing PPG, APG, RPG, and TPG (turnovers per game). Finally, this dashboard also shows team shooting percentages in a donut, react-chartjs-2 chart.
2. A select page that selects players and displays a player dashboard. The select component allows for filtering on both teams and playing positions in the event that a user may be forgetting the name of a player.
3. Player dashboards show variance between a player's current season and career statistics. It shows variance on three-point, two-point, free-throw, field goal, and true shooting percentages.
4. In future versions, selecting a team's game date will display a new version of the team dashboard specified for that specific game.
5. Future versions will also include the capability of getting live data for NBA games.

Application

View my application live by visiting nba.chryoung.org