# Pseudocode for Python (Pandas) avg_sub_time = df[df['substitute_out'].notnull()].groupby('year')['substitute_out'].mean()
Analyzing which countries have sent the most players to the World Cup, and conversing on how this reflects on their footballing culture and success.
The , created by Joshua C. Fjelstul, Ph.D., is one of the most comprehensive open-source datasets for FIFA World Cup history. It covers all 22 men's tournaments from 1930 to 2022 and 8 women's tournaments from 1991 to 2019, comprising over 1.58 million data points.
The chart will show massive spikes at 45' (halftime tactical changes), 60' (the classic "fresh legs" moment), and 75' (the desperation sub). Post-2020, you will see a new spike at 80' due to the five-sub rule allowing late-game management. jfjelstul worldcup data-csv appearances
In the 1980s, the average sub happened in the 75th minute. By 2022, it’s the 58th minute. This table empirically proves the tactical revolution: managers now treat the bench as a weapon, not a lifeboat.
This dataset is structured in a "long" format, where a single player appears multiple times—once for every World Cup tournament in which they participated.
appearances = pd.read_csv('https://raw.githubusercontent.com/jfjelstul/worldcup/master/data-csv/appearances.csv') goals = pd.read_csv('https://raw.githubusercontent.com/jfjelstul/worldcup/master/data-csv/goals.csv') It covers all 22 men's tournaments from 1930
The substitute_in and substitute_out columns allow you to map the evolution of tactics. Before 1970, substitutions were practically non-existent (injury only). By 2022, five substitutions were allowed.
: Tracking the rise of multi-tournament veterans like Lionel Messi or Lothar Matthäus.
The true value of appearances.csv is realized when it is joined with other files in the Jfjelstul collection using the ID columns: In the 1980s, the average sub happened in the 75th minute
The dataset has gained significant traction in the data science community and has been featured by major outlets like , The Washington Post , and DataCamp . The Fjelstul World Cup Database - GitHub
An informative article based on World Cup player appearance data could cover several areas: