2026 World Cup Data in One Workbook
48 teams, 1,100+ players, ~15 columns from club to xG/90; formulas rank market value and cost efficiency; every figure marked with source and verification status.
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A World Cup workbook built from a 48-team, 1,100+ player database, formula-driven rankings and conditional-formatting heat maps.
Adds a 104-match calendar sheet, filterable by date, group and host city.
Try in KimiBuild a "2026 World Cup Data Panorama Workbook": the core data sheet holds a database of roughly 1,100–1,250 players across 48 teams (about 15 columns including name, country, club, position, age, height, market value and xG/90). Use formulas to compute global market-value rank, rank within position, value for money and an overall score, and build a 48-row national-team summary with SUMIF/AVERAGEIF/INDEX-MATCH; add conditional-formatting heat color scales, a frozen header row and a filterable structure, in a low-saturation warm white palette. Tag all data with its source and data status (verified or estimated).
Adds a Golden Boot shortlist ranked by projected goals, with formulas linked to the player database.
Try in KimiBuild a "2026 World Cup Data Panorama Workbook": the core data sheet holds a database of roughly 1,100–1,250 players across 48 teams (about 15 columns including name, country, club, position, age, height, market value and xG/90). Use formulas to compute global market-value rank, rank within position, value for money and an overall score, and build a 48-row national-team summary with SUMIF/AVERAGEIF/INDEX-MATCH; add conditional-formatting heat color scales, a frozen header row and a filterable structure, in a low-saturation warm white palette. Tag all data with its source and data status (verified or estimated).
Same workbook structure, rendered in English with the same formulas and conditional formatting.
Try in KimiBuild a "2026 World Cup Data Panorama Workbook": the core data sheet holds a database of roughly 1,100–1,250 players across 48 teams (about 15 columns including name, country, club, position, age, height, market value and xG/90). Use formulas to compute global market-value rank, rank within position, value for money and an overall score, and build a 48-row national-team summary with SUMIF/AVERAGEIF/INDEX-MATCH; add conditional-formatting heat color scales, a frozen header row and a filterable structure, in a low-saturation warm white palette. Tag all data with its source and data status (verified or estimated).
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KPIs, share price, market cap, annual revenue, category and region mix, store and staff efficiency, operating margin — two worksheets in EUR million. Swap in yours.