I need a robust yet easy-to-maintain web scraper that pulls player statistics from four different sports sites—a blend of official league pages, sports news outlets, and a couple of well-known fan forums. All scraped data should flow into a single database and surface through a lightweight web dashboard where I can search by player, season, and team, compare numbers side by side, and export results to CSV. My ideal flow looks like this: enter or schedule the URLs, run or auto-run the scraper, watch progress logs, and then immediately view fresh stats inside the dashboard—no command-line work once everything is deployed. If any source changes its HTML, the scraper should fail gracefully and flag the issue in the UI so I can react quickly. Tech stack is flexible; Python with BeautifulSoup / Scrapy on the back end and a simple Flask or Node/Express interface would be perfect, but I’m open to alternatives if they shorten development time or improve stability. Clean, well-commented code and clear setup docs are essential because I’ll be hosting the solution on my own VPS. Acceptance criteria • A working scraper module for each of the four designated sites, returning consistent player-level stat objects. • A responsive dashboard that lists, filters, compares, and exports data. • Cron-friendly scheduling plus a manual “Run now” button. • Error handling with descriptive logs surfaced in the dashboard. • Deployment guide that lets me recreate the environment from scratch.