Worldcup Database Sqlite Link Download May 2026

SELECT player_name, COUNT(*) AS total_goals FROM goals JOIN players ON goals.player_id = players.player_id GROUP BY player_name ORDER BY total_goals DESC LIMIT 5; (Expected: Miroslav Klose, Ronaldo, Gerd Müller, etc.)

worldcup.db (SQLite)

Tagline: Stop scraping Wikipedia. Here’s a ready-to-use SQLite database of every World Cup match (1930–2022). worldcup database sqlite download

| Table | Sample Columns | |-------|----------------| | matches | year, home_team, away_team, home_goals, away_goals, stage, attendance | | teams | team_id, team_name, confederation (UEFA, CONMEBOL, etc.) | | players | player_name, team_id, position, caps, goals | | goals | match_id, player_id, minute, own_goal, penalty | | tournaments | year, host_country, winner, top_scorer, total_goals | Data covers 1930–2022 (all 22 tournaments, 900+ matches, 2,700+ goals). I’ve prepared a clean, version-controlled copy for you. No registration, no paywalls. SELECT player_name, COUNT(*) AS total_goals FROM goals JOIN

SELECT year, home_team, away_team, home_goals || ' - ' || away_goals AS score FROM matches WHERE stage = 'Final' ORDER BY year; I’ve prepared a clean, version-controlled copy for you

If you’ve ever tried to analyze World Cup history—from Uruguay 1930 to Qatar 2022—you know the struggle. Data is scattered across JSON files, messy CSV exports, or behind rate-limited APIs.

📦 github.com/yourusername/worldcup-sqlite (Update with real link) 📧 Contact: data@yourblog.com Final Word Stop wrestling with messy web scrapers. Grab the SQLite file, open your terminal, and start asking real questions of World Cup history.