The database is a collection of containing over 1.58 million data points . It is designed for both professional sports analysts and data science students, offering a "tidy" data format that makes it easy to merge and reshape for various research goals. It covers: 22 Men's World Cup tournaments (1930–2022). 8 Women's World Cup tournaments (1991–2019).
(recommended)
SELECT DISTINCT winner AS country FROM fjelstul_world_cup_database UNION SELECT DISTINCT runner_up AS country FROM fjelstul_world_cup_database UNION SELECT DISTINCT third_place AS country FROM fjelstul_world_cup_database; fjelstul world cup database csv
Information on tournaments, confederations, teams, players, managers, referees, stadiums, and matches.
import pandas as pd
The official source for the database is the jfjelstul/worldcup GitHub repository . Inside the repository, you can find a dedicated data-csv/ folder containing all 27 datasets as individual CSV files.
These tables normalize player data.
The Fjelstul World Cup Database is more than just a spreadsheet of scores; it is a meticulously crafted tool for historical preservation and statistical analysis. By normalizing messy historical data into a tidy, relational format, it bridges the gap between football history and modern data science. For anyone looking to perform serious analysis on "The Beautiful Game," the Fjelstul CSV collection remains the definitive starting point.
SELECT AVG(goals_scored / matches_played) AS avg_goals_per_match FROM fjelstul_world_cup_database; The database is a collection of containing over 1