WNBA Analytics Dashboard

April, 2024

Introduction

With the 2024 WNBA regular season around the corner, I wanted to set up some analytics dashboards while practicing my web scraping and Shiny app development, and I adapted the app I built for the UChicago Basketball Teams based on 2023 WNBA data.

Check out the site here or scroll to see how I built it!

Team Rankings

  • Traditional + advanced stat averages
  • Box score, play-by-play data scraped manually from Basketball-Reference
    • Advanced stats calculated from team averages
    • Average possession length calculated from play-by-play

Player Rankings

  • Traditional stat averages
  • Box score data scraped manually from Basketball-Reference

Assist Rankings

  • Most frequent assist pairings across the league (table)
  • Most frequent assist pairings filtered by team (chart)
 
  • Play-by-play data scraped manually from Basketball-Reference

Rotation Charts

  • Substitution patterns filtered by team
 
  • Play-by-play data scraped manually from Basketball-Reference *

* This data can be particularly tedious, leading to occasional inaccuracies – e.g. a player checking into the game who’s already in the game, leading to a 4-man or 6-man lineup. My current workaround is to ignore substitutions that result in invalid lineup sizes (anything other than 5 players), but this still results in inaccuracies.

Single-Game View

  • Traditional + advanced stat comparison
  • Lead tracker
  • Rotation chart by team
  • Box score, play-by-play data scraped manually from Basketball-Reference

Team Logs

  • Traditional stat log, ordered by date
  • Margin of victory chart, ordered by date, margin, or team
  • Rolling average chart of multiple stats
 
  • Box score data scraped manually from Basketball-Reference

Player Logs

  • Traditional stat log, ordered by date
 
  • Box score data scraped manually from Basketball-Reference