Overview
FBref Table Scraper is a developer tool and mini web app that lets users detect, preview, and export football statistics tables from FBref pages in a few clicks. It streamlines scouting, analysis, and content creation by turning messy HTML tables into clean, downloadable data.

Key Features

• Auto-detect tables on any FBref page (matches, shooting, passing, possession, etc.).
• Preview before export with sortable columns and pagination.
• Multi-table selection to grab several datasets in one run.
• Filters by season, competition, club, or player (when present on page).
• One-click CSV download per table (tidy headers, UTF-8).
• Error handling & feedback (loading spinners, toast messages).
• Rate-limit friendly requests with retries and graceful fallbacks.

Tech Stack

• Backend: FastAPI (Python), Requests/HTTPX, lxml/BeautifulSoup for parsing
• Frontend: Bootstrap (or Tailwind), vanilla JS/AJAX for async table detection
• Data: Pandas for cleanup/normalization, CSV export
• Auth (optional): Simple login to gate the scraper UI
• Deployment: Docker-ready; works on Render/VPS

How It Works (Flow)

1. Step 1 – Detect: Paste an FBref URL → the app scans and lists all tables found.
2. Step 2 – Select: Choose specific tables → instant in-app preview.
3. Step 3 – Export: Download clean CSVs (or copy to clipboard) for analysis.

Why It’s Useful

• Saves analysts, creators, and students hours of manual copying.
• Produces analysis-ready datasets for Excel, Python notebooks, or BI tools.
• Ideal for scouting reports, match previews, and historical trend analysis.

My Contributions

• Implemented robust HTML parsing & schema normalization.
• Built a responsive UI with live previews and multi-table export.
• Added validation (url.startswith("https://fbref.com/")) and clear error messages.
• Packaged for easy deployment with environment-based configuration.

Outcome
Reduced data collection time by 80%+, enabling quick turnarounds for content and analysis while ensuring reproducible, clean datasets.