Challenge 03-Aug 2026

Description: Since 1930, the FIFA World Cup matches have delivered record-breaking television audiences across the globe, proving football's unique ability to unite millions of fans. But of course, with such an audience, many questions and debates spark up as well. The answer to every debate you’ve ever had with a friend about the history of football is hidden somewhere in the data. Hence, you want to use historic FIFA World Cup data to build an interactive composite view that allows you to explore the history for yourself and find the answers. 

For this challenge, you will be using the Fjelstul World Cup Database which is a comprehensive database containing 27 .csv files about the FIFA World Cup that covers all men's and women's tournaments. The goal of this challenge is to build an interactive composite view using KNIME's View and Widget nodes. 

A great place to begin your exploration is with the tournament-standings.csv and award-winners.csv files. But don't feel restricted. You are free to use any of the datasets available in the GitHub repository. Whether you choose to combine datasets to tell a story of football history or focus on a very specific statistical question, the choice is yours. Here are some questions to get you thinking:

• Which nation holds the record for the most titles?

• Has any nation ever won back-to-back titles? Who and when? 

• Who are considered the tournament's top players and in which years?

• Who won the Golden Boot in the 2022 Men's World Cup?

• How has the total number of goals per match changed over the decades? 

Let your creativity flow!

Load Group 1 World Cup Data

This metanode pulls together a first group of World Cup reference datasets from the database, including information about tournaments, confederations, awards, players, and managers. Conceptually, it creates several ready-to-use tables that turn separate source files into cleaner lookup and analysis data for later joins, filtering, and interactive exploration.

Prepare Award and Team Reference Data

This block loads and combines a small group of related World Cup tables centered on teams, players, tournaments, and awards. The result is a richer table where IDs such as team_id, player_id, and award_id are turned into more useful context, making the data easier to analyze in later steps.

Combine Match Event Data

This block brings together several event-level World Cup tables such as substitutions, bookings, goals, and penalty kicks using shared IDs like tournament, match, team, and player. Conceptually, it condenses separate records about what happened during matches into a single, wider table so those events can be compared and analyzed together more easily.

Prepare Squad and Appointment Data

This block loads a related set of reference tables about squads, qualified teams, manager appointments, and referee appointments from the database and combines them into a richer table. Conceptually, it adds context around who was involved in each tournament by linking team, manager, and referee information so the data is easier to explore later.

Combine Match and Participant Data

This block brings together several related World Cup tables using shared IDs such as player, team, match, tournament, opponent, and referee. The goal is to turn separate pieces of information into one richer analysis table, so match-level and participant-level details can be explored together more easily.