Jfjelstul Worldcup Data-sqlite Online

This report provides a comprehensive analysis of the , a public dataset available on Kaggle. Created by user Jordan Fjelstul, this database offers a clean, well-structured, and comprehensive relational database of FIFA World Cup historical data. It covers tournaments from 1930 to 2014 (with later versions potentially extending to 2022) and includes granular data regarding matches, players, teams, and tournament hosting.

JFjelstul World Cup data-sqlite Code:

In addition to analyzing team performance, we can also work with match-level data. For example, to find the matches with the highest attendance, we can use the following query: jfjelstul worldcup data-sqlite

SELECT trn.year, trn.host_country, COUNT(m.match_id) AS total_matches, SUM(m.extra_time) AS extra_time_games, SUM(m.penalty_shootout) AS penalty_shootouts, ROUND((SUM(m.extra_time) * 100.0 / COUNT(m.match_id)), 2) AS pct_drawn_regulation FROM matches m JOIN tournaments trn ON m.tournament_id = trn.tournament_id GROUP BY trn.tournament_id ORDER BY trn.year DESC; Use code with caution. 3. Team Dominance Matrix This report provides a comprehensive analysis of the

If you ran or saw a specific report (e.g., “most cards in a final”, “teams that never lost a group match but were eliminated”, “win percentage by confederation”), I can help reconstruct the SQL query or explain the schema. Otherwise, could you paste a snippet or describe what finding caught your eye? JFjelstul World Cup data-sqlite Code: In addition to