Jfjelstul - Worldcup Data-csv Appearances

Using the appearances table, you must calculate time_played = (substitute_out - substitute_in) for each row. For players who played the full 90 (or 120), the logic is different.

SELECT player_name, team, SUM(minutes_played) as total_minutes FROM appearances WHERE tournament = '2022' GROUP BY player_id ORDER BY total_minutes DESC Goalkeepers and center-backs from finalists dominate. In 2022, Emiliano Martínez (Argentina) or Hugo Lloris (France) would top the list with ~690+ minutes. But the real magic is historical: In 2014, Manuel Neuer played every single minute of Germany’s run, including the final. 3. The Tactical Insight: Substitution Dynamics Over Time 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. jfjelstul worldcup data-csv appearances

Calculate the average minute of the first substitution per decade. Using the appearances table, you must calculate time_played

In the ecosystem of sports data science, few repositories are as meticulously maintained or as democratically accessible as Joshua Fjelstul’s jfjelstul/worldcup database. While the goals.csv file gets the glory and the matches.csv file provides the narrative spine, there is one table that captures the raw, human cost of the World Cup: appearances.csv . In 2022, Emiliano Martínez (Argentina) or Hugo Lloris

For the analyst, this file is a playground of temporal logic. For the fan, it is a reminder that every minute on that pitch is a dataset of one. Load the CSV. Run the join. Ask who really worked the hardest. The answer is waiting in the rows of appearances.csv .