Web Scraping Sports Data
Intermediate
10 min read
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Nov 28, 2025
Web Scraping for Sports Analytics
While many sports data sources offer APIs, sometimes web scraping is necessary to gather data. This tutorial covers ethical scraping practices and common techniques.
When to Scrape vs Use APIs
| Use API When | Scrape When |
|---|---|
| Official API exists | No API available |
| Need real-time data | Historical data only |
| High volume requests | One-time data collection |
| Production applications | Research/analysis |
Ethical Scraping Guidelines
- Check robots.txt: Respect site's crawling rules
- Rate limiting: Wait between requests (1-2 seconds minimum)
- User-Agent: Identify your scraper honestly
- Terms of Service: Review site's legal policies
- Data usage: Only use for permitted purposes
Common Tools
- BeautifulSoup: Parse HTML, extract data
- Selenium: Handle JavaScript-rendered content
- Requests: Make HTTP requests
- rvest (R): R package for web scraping
Key Takeaways
- Always prefer official APIs when available
- Be respectful of server resources
- Handle errors gracefully with retries
- Cache data to avoid redundant requests
- Consider using sports data packages first (pybaseball, baseballr)
Discussion
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