Jfjelstul: Worldcup Data-sqlite

This query groups the data by winner and counts the number of titles won by each team.

| Table Name | Description | Key Attributes | | :--- | :--- | :--- | | | High-level tournament data. | year , host_country , winner , runners_up , attendance . | | teams | List of participating nations. | team_name , confederation . | | matches | The central fact table for games played. | match_id , year , stage , home_team , away_team , score . | | players | Squad information. | player_name , team , position , caps , goals . | | goals | Granular data on every goal scored. | minute , player_name , match_id , penalty , own_goal . | | penalties | Data on penalty shootouts. | winner , score_home , score_away . | | venues | Stadium information. | stadium , city , capacity . | jfjelstul worldcup data-sqlite

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. This query groups the data by winner and

The is a gold standard resource for football analytics. By structuring the data relationally, the author has saved analysts significant time in data wrangling. It serves as an ideal backend for sports visualization dashboards, an educational tool for SQL learners, and a robust dataset for historical sports research. | | teams | List of participating nations

# Visualize team performance import matplotlib.pyplot as plt team_performance.plot(kind="bar") plt.title("World Cup Titles by Team") plt.xlabel("Team") plt.ylabel("Number of Titles") plt.show()