FIFA Influence monitor 2025 Infographic

193 member associations — players, influence, islands & oil states
Players per 1,000 population
Overview
Players vs. Influence
Island States
Oil States & World Cups
All Countries
Notes
Very high (>10 / 1,000) High (5–10) Medium (2–5) Low (0.5–2) Very low (<0.5) Oil state Island state
Registered players by confederation
Players by confederation
Top 25 countries by influence score
Influence scores
Oil state Island state High influence (≥5) Other
Island states: players vs. influence (bubble size = population)
Island states
Island states by confederation
By confederation
World Cup hosting 1930–2034
Traditional football nation Oil / petro state North America Emerging / other Future host
Oil states: influence vs. players per 1,000 population
Oil states analysis
Country ↕ Conf. Players ↕ Per 1,000 ↕ Influence ↕ Type

About this dashboard

This dashboard visualises the distribution of power within FIFA across its 193 member associations. It combines three dimensions: the footballing footprint of each country (registered players), its formal decision-making weight (influence score), and its geopolitical character (oil state or island state).

World map panel

The choropleth map colours each country by registered players per 1,000 population using a five-tier blue scale. Red dots mark oil states; amber dots mark island states. Hover over any country for a tooltip. Use the search bar to locate any country and display its exact player count, influence score, confederation and classification.

Overview panel

The bar chart shows total registered players per confederation. UEFA and AFC together account for more than 70% of all registered players globally, with UEFA alone registering over 32 million. The horizontal bar chart ranks the top 25 countries by influence score. Switzerland (score 151) sits alone at the top due to FIFA’s headquarters location and the nationality of the current president; Sweden (44) and Italy (39) follow.

Players vs. influence panel

The scatter plot exposes the central paradox of FIFA governance: influence scores are largely decoupled from player bases. Bahrain (score 31, 3,796 registered players) outranks Brazil (score 5, 2.5 million players). Paraguay (score 26, 130,000 players) outranks China (score 1, 26 million players). The X-axis can be toggled between absolute player count, total population, and players per 1,000 population.

Island states panel

The 21 island states identified in this dataset hold disproportionate influence relative to their footballing weight. Vanuatu (population 327,000) holds an influence score of 21. American Samoa (population 55,197) holds a score of 6. Each of the 211 FIFA member associations casts one equal vote in Congress, making small island states structurally valuable in presidential elections and statutory votes. The FIFA Forward programme distributes near-equal operational grants to all 211 associations, creating financial dependency regardless of association size.

Oil states and World Cup panel

The timeline shows all 25 World Cups from Uruguay 1930 to Saudi Arabia 2034. The shift from traditional football nations to oil and petro states as hosts is visible from 2018 onwards: Russia (2018), Qatar (2022), and Saudi Arabia (2034). The United States — itself a significant oil producer — co-hosts in 2026 and hosted in 1994. The bar chart shows that oil states often combine high influence scores with low player penetration rates, most strikingly in Bahrain (score 31, 0.26 per 1,000) and Qatar (score 9, 0.92 per 1,000).

Influence score methodology

The influence score is derived from the source dataset (Moedersheet_FIFA.xlsx) and reflects structural power within the FIFA governance architecture. A baseline score of 1 applies to all ordinary FIFA Congress members. Higher scores reflect additional positions held: FIFA Council membership, confederation presidency, Bureau of the Council membership, committee chairmanships, and the FIFA presidency itself (score 151 for Switzerland, reflecting Infantino). The score does not capture informal influence, patronage networks, or voting bloc coordination.

Data sources