Premier League Stats Dashboard

An end-to-end football analytics project: scrape player stats from FBref, then explore them in an interactive Streamlit dashboard.

What it does

Step	File	Description
Scrape	scraper.py	Pulls 2025-26 PL player stats from FBref via soccerdata. Downloads to CSV; subsequent runs read from cache.
Explore	dashboard.py	Streamlit app with sidebar filters (club, position, min 90s) and three tabs: Overview, Shooting, Discipline.

Quick start

# 1. Install dependencies
pip install soccerdata streamlit plotly

# 2. Download the data (only needed once; results are cached)
python scraper.py

# 3. Launch the dashboard
streamlit run dashboard.py

Then open http://localhost:8501.

Dashboard tabs

Overview — G+A leaderboard, Goals vs Assists scatter, full sortable table
Shooting — Shot volume vs goals, conversion rate (G/Sh) leaders, shooting table
Discipline — Yellow card leaders, Fouls vs Interceptions scatter, cards-per-90 table

Data

Stats come from FBref (Sports Reference) via the soccerdata library, which handles rate-limiting and on-disk caching automatically. Three stat categories are currently scraped:

File	Contents
pl_standard.csv	Appearances, goals, assists, cards
pl_shooting.csv	Shots, shots on target, conversion rates
pl_misc.csv	Fouls, interceptions, tackles, crosses

Extending the data: soccerdata also supports keeper and playing_time. For passing, GCA, defense, and possession stats, see the Playwright-based scraper preserved in the git history, or the R package worldfootballR.

Project structure

Football-data/
├── scraper.py       # data collection
├── dashboard.py     # Streamlit app
├── pl_standard.csv
├── pl_shooting.csv
├── pl_misc.csv
└── README.md