Baselight

Trending FIFA

This dataset can be used to find the factors determining a FIFA player's

@kaggle.willianoliveiragibin_trending_fifa

  • 78.27 KB
  • 3000 rows
  • 11 columns
player_name

Player Name

age

Age

national_team

National Team

positions

Positions

overall

Overall

potential_overall

Potential Overall

current_club

Current Club

current_contract

Current Contract

value

Value

wage

Wage

total_stats

Total Stats

T. Almada22Argentina['CAM', 'CM', 'CF']7987Atlanta United2022 ~ 2025€39.5M€10K2050
L. Palma23Honduras['LW']6975Celtic2023 ~ 2028€2.2M€22K1794
R. Lavia19Belgium['CDM']7386Chelsea2023 ~ 2030€7M€32K1829
W. Zaïre-Emery17France['CM', 'CDM']7789Paris Saint Germain2022 ~ 2025€24M€9K2080
Gabri Veiga21Spain['CM', 'CAM']7889Al Ahli Jeddah2023 ~ 2026€31.5M€28K1944
J. Bellingham17England['CAM', 'CM']6482Sunderland2023 ~ 2028€1.5M€1K1714
K. Havertz24Germany['CAM', 'RW', 'ST']8287Arsenal2023 ~ 2028€46M€110K2044
A. Vermeeren18Belgium['CDM', 'CM']7487Antwerp2022 ~ 2026€9.5M€7K1883
R. Højlund20Denmark['ST']7789Manchester United2023 ~ 2028€25.5M€77K1841
J. Bellingham20England['CAM', 'CM']8791Real Madrid2023 ~ 2029€112M€190K2265

CREATE TABLE trending_football_players_year_new (
  "player_name" VARCHAR,
  "age" BIGINT,
  "national_team" VARCHAR,
  "positions" VARCHAR,
  "overall" BIGINT,
  "potential_overall" BIGINT,
  "current_club" VARCHAR,
  "current_contract" VARCHAR,
  "value" VARCHAR,
  "wage" VARCHAR,
  "total_stats" BIGINT
);

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