World Cup 2026 Elimination "Food Chain"
Haiti is one of the earliest nations to be eliminated from the 2026 World Cup. After just two matches, they lost 0-1 to Scotland on June 14 and then lost again 0-3 to Brazil on June 20.
But if we check the archive, their World Cup journey was actually much longer than those two matches. The qualification stage started in 2024, and they had to endure at least ten matches before securing their place at the World Cup.
Before being eliminated by Scotland and Brazil in the group stage, they had actually eliminated several CONCACAF nations during the qualification stage: Saint Lucia, Barbados, Aruba, Honduras, Costa Rica, and Nicaragua.
After realizing this, I noticed that there is an implicit “food chain” among nations in the World Cup.
Nation B eliminates Nation C, then later Nation A eliminates Nation B, whether in qualification, the group stage, indirectly through mathematical elimination in the third-best group ranking, or later in the knockout rounds such as the Round of 32, Round of 16, and beyond.
I want to visualize this “food chain” as a graph.
There's plenty of data that I still need to process, and as of this writing, the World Cup is still ongoing. As a result, this dataset remains incomplete and is still a work in progress. Below is the list of (eliminated) nations that I have managed to process so far.
Anyway, what insights have I managed to notice so far?
First, there are these “isolated” subgraphs.
The pattern is obvious: two or three nations manage to push a single nation to the bottom of its group. This happened to New Zealand, Tunisia, and Turkey.
Then, I found the first “big” subgraph.
Most of it consists of Asian (AFC) nations, but there is also a small connection to South American (CONMEBOL) nations because of two events.
First, the intercontinental qualifier between Bolivia and Iraq, where Iraq eliminated Bolivia from World Cup contention with a 2-1 win.
Second, Spain (Europe - UEFA) quickly eliminated both Uruguay (South America - CONMEBOL, 1-0) and Saudi Arabia (Asia - AFC, 4-0) in the group stage. As a result, three South American nations—Venezuela, Chile, and Peru—became part of this “Asian subgraph” thanks to Uruguay losing to Spain and Bolivia losing to Iraq.
Wait... I just remembered today’s “Hatsune Miku” meme trending on X after Norway eliminated Brazil in the Round of 16.
The meme started after Brazil eliminated Japan in the Round of 32, effectively “taking over” Hatsune Miku from Japan. Now that Brazil has lost to Norway, Miku’s custodianship has passed to Norway.
Using that same logic, who is the real “king” of this large, Asian-majority subgraph?
I wondered if there was already a mathematical name for this problem: given a directed graph, define the “king” as one or more nodes that sit at the top of the food chain.
ChatGPT suggested that if indirect eliminations are taken into account, then the relevant concept is reachability or the graph’s transitive closure. Under that definition, a “king” would be a node that can reach the largest number of other nodes through directed paths.
I’m not going to implement that functionality just yet. Instead, I’ll trace it manually using this visualization.
Hmm... it seems this subgraph has multiple “kings”: Colombia, Portugal, Canada, Bosnia and Herzegovina, France, Norway, Senegal, Austria, Algeria, and Spain.
And, here’s the second big subgraph that I managed to find.
The real clash between Europe and the Americas.
Scotland managed to eliminate Haiti with a 1-0 win. Then, in retaliation (?), South America’s Brazil eliminated Scotland with a 3-0 win. Ironically, Brazil’s assault on Scotland would not have happened without Europe’s Croatia and its advanced 4D chess “remote mathematical elimination” technique. Although Croatia was in Group L and Scotland was in Group C, Croatia still managed to indirectly eliminate Scotland.
I jokingly call it a “4D chess” move because the chain of events is so complicated to calculate. Just take a look at this:
“Scotland needed Ghana to defeat Croatia by a large enough margin to keep Scotland’s goal difference and ranking among the best third-placed teams alive. Instead, Croatia’s 2–1 victory meant Scotland could no longer finish in the top eight third-placed teams. Before the final Group L matches, Scotland’s qualification scenario required all three of the following: Ghana to beat Croatia by three or more goals; either Uzbekistan to draw with DR Congo or win by fewer than four goals; and either Austria to beat Algeria by at least two goals or Algeria to beat Austria by at least four goals. Instead, Ghana lost 2–1 to Croatia, ending Scotland’s hopes immediately. Even if the other two conditions had been met, that result alone was enough to eliminate Scotland.”
I heard that a similar system has been used before, although not in the World Cup, and that some teams failed to qualify because they miscalculated the scoreline they needed. Something like, “We thought a draw was enough, so we parked the bus for the entire match, but it turned out it wasn’t!” I haven’t verified this story yet, though. An online friend told me about it. If it’s true, it’s quite funny.
Meanwhile, Europe’s Croatia also eliminated Central America’s Panama with a 1-0 win.
So, Europe eliminated North America, then South America eliminated Europe, with help from another European team. That same European team also eliminated a Central American nation.
Because of this clash, there were plenty of collateral damages.
In Europe: Faroe Islands, Gibraltar, Ireland, Denmark, Belarus, Greece, and Scotland (blame Czechia and Scotland for all of this).
In the Americas: Belize, El Salvador, Guyana, Guatemala, Montserrat, Suriname, Nicaragua, Costa Rica, Honduras, Barbados, Aruba, Saint Lucia, Jamaica, Bermuda, and Trinidad and Tobago (blame Curaçao, Haiti, and Panama for all of this).
Hmm... Interesting. I could probably make a map of this.
Anyway, what about that Asian-majority subgraph from earlier?
The Asian regions affected by collateral damage are Turkmenistan, Hong Kong, Kyrgyzstan, the UAE, Afghanistan, India, North Korea, the Philippines, Vietnam, Kuwait, Palestine, Oman, Pakistan, Tajikistan, Bahrain, China, and Indonesia (blame Uzbekistan, Qatar, Iraq, Jordan, and Saudi Arabia for all of this).
The American region affected by collateral damage consists of Venezuela, Chile, Peru, and Bolivia (blame Uruguay).
Alright. Let’s make that map.
First, I downloaded the “World Administrative Boundaries - Countries and Territories” shapefile from public.opendatasoft.com, then opened it in QGIS by dragging and dropping the .shp file into the project.
Next, I right-clicked the world-administrative-boundaries layer, selected Toggle Editing, and opened the attribute table.
Then I clicked the New Field icon to create a new field called aff, which stores each nation’s current subgraph. This field will later be used as the coloring guide.
With the attribute table still open, I pressed Ctrl+F and searched for the target country by its English name, then clicked Zoom to Features. After that, I selected the Identify Features tool from the toolbar, clicked the country’s territory on the map, right-clicked the aff field, selected Edit Feature Form, and assigned the appropriate label.
Finally, I double-clicked the world-administrative-boundaries layer and opened the Symbology tab. I changed the renderer to Categorized, set the value field to aff, and clicked Classify. From there, every nation’s subgraph was displayed with a uniform color based on its aff value.
Yep, making this map is surprisingly hard.
The Asian regions affected by collateral damage are Turkmenistan, Hong Kong, Kyrgyzstan, the UAE, Afghanistan, India, North Korea, the Philippines, Vietnam, Kuwait, Palestine, Oman, Pakistan, Tajikistan, Bahrain, China, and Indonesia (blame Uzbekistan, Qatar, Iraq, Jordan, and Saudi Arabia for all of this).
Faroe Islands, Gibraltar, Ireland, Denmark, Belarus, Greece, Scotland, Georgia, Bulgaria, and Kosovo (blame Czechia, Turkey and Scotland for all of this).
Belize, El Salvador, Guyana, Guatemala, Montserrat, Suriname, Nicaragua, Costa Rica, Honduras, Barbados, Aruba, Saint Lucia, Jamaica, Bermuda, and Trinidad and Tobago (blame Curaçao, Haiti, and Panama for all of this).
