The accuracy of AI predictions for the outcome of a single match typically ranges between 50% and 60%. This is better than random guessing (33%), but still far from being "guaranteed to win."

Article author, source: 0x9999in1, ME News



TL;DR

• The 2026 World Cup kicks off on June 11, featuring the first-ever 48 teams, 104 matches, and spanning 16 cities across the United States, Canada, and Mexico, with the final on July 19 in New York. The scale has doubled, and so have the variables.
• Octopus Paul's "legendary" status was essentially a game of probability: choosing correctly between two options in a single match seven times in a row has only a 1/128 chance. He won through luck, not intelligence.
• This year, the supercomputer takes the baton. Opta has ranked Spain as the top favorite, with a 16.1% chance of winning—note that even the biggest favorite has less than a 20% chance.
• The accuracy of AI predictions for the outcome of a single match typically ranges between 50% and 60%. This is better than random guessing (33%), but still far from being "guaranteed to win."
• My take: AI is a useful "odds magnifier," not a "crystal ball." It can help you calculate whether the odds are worth it, but it can't help you avoid upsets.
• What has truly changed is not football, but the way we view uncertainty.

First, let’s talk about the octopus: that legendary cephalopod—what exactly makes it divine?

First, bring back that octopus.

In 2010, South Africa. An octopus named Paul, living at the Oberhausen Aquarium in Germany, would "predict" the winner by choosing which of two boxes—each marked with a national flag and containing a mussel—he ate from first.

The result? In that World Cup, Paul predicted all six of Germany’s matches correctly. Adding his correct prediction for Spain in the final, he got all eight matches right. Over his entire career, he made 12 correct predictions and 2 incorrect ones, for an accuracy rate of 85.7%.

The numbers are impressive. But take three seconds to calm down and ask: Is this really a "prediction"?

No. This is a coin flip.

A football match, simplified to "win or not win," is a binary choice. Getting one right has a probability of 1/2; getting two right in a row, 1/4; getting seven right in a row, 1/128. The BBC once calculated this. What does 1/128 mean? It’s not high, but it’s certainly not miraculous. With so many aquariums, so many animals, and so many "prophets" worldwide, it’s inevitable that one would guess correctly by chance. We remember Paul, but forget all the others who got it wrong early on and never even left a name.

This is survivorship bias. The media needs a myth, and Paul just happened to be in the spotlight.

I in no way mean to belittle the octopus. It brought endless joy to the summer of 2010, even received death threats, and was even "protected" by German authorities. It passed away shortly after retiring—a mascot of an era.

But let’s be honest: what Paul represents is that endearing human tendency toward superstition when facing uncertainty. We want answers so badly—so desperately—that we’re willing to believe in an octopus.

Sixteen years have passed. This year, we’ve upgraded to a more respectable "prophet."

2026: This World Cup is already "different"

Why is this year special?

Because it has been rewritten at its core.

This is the first World Cup in history with 48 teams competing. The number of matches has surged from 64 to 104. Spanning three countries—the United States, Canada, and Mexico—and 16 cities, the tournament runs from June 11 to July 19, lasting a total of 39 days. The final will be held in the New York metropolitan area.

Doubling in scale means the soil for lesser-known projects has become even richer.

This year’s roster features a host of newcomers: Cape Verde, Curaçao, Jordan, and Uzbekistan—four teams making their World Cup debut. Cape Verde, an island nation in the Atlantic with a population of fewer than 600,000, has qualified for the World Cup. Curaçao, a Caribbean territory smaller than many people’s hometowns, is here too.

These stories were once fantasy in the past; now they are written in black and white on the schedule.

The format is also more complicated. The 48 teams are divided into 12 groups, with the top two from each group plus the eight best third-place teams advancing to form a 32-team knockout stage. The fact that third-place teams can still qualify gives weaker teams a chance to "survive even after a loss." The number of possible combinations the algorithm must calculate has increased by an order of magnitude.

Too many variables. Too much randomness.

So the question arises: In a more chaotic system, is prediction harder, or more valuable?

This is exactly where AI comes in.

AI Takes the Baton: The Answer Provided by the Supercomputer

This year, the cold, impersonal computing power has taken over Octopus's role.

The most representative example is Opta’s supercomputer, which inputs team strength ratings, recent form, and matchup dynamics into its model, then simulates the entire World Cup tens of thousands of times to count the frequency of each possible outcome.

Who is the top favorite? Spain, with a 16.1% chance of winning.

Keep an eye on this number: 16.1%.

This is the highest value among the 48 teams. In other words, even the team most favored by the algorithm has less than a 20% chance of winning the title. The model also states that Spain is the only team with a probability over 50% of advancing to the quarterfinals (52.1%), a 39.0% chance of reaching the semifinals, and a 25.6% chance of making it to the final. It sounds strong, right? But read it the other way: it has more than an 80% chance of not winning the championship.

Other models show slight variations in ranking; some place Portugal (6.92%), Brazil (6.82%), and Germany (5.84%) at the top, consider the Netherlands and Norway as dark horses, and view Morocco (1.93%) as Africa’s greatest hope—the team that stunned the world by reaching the semifinals four years ago.

The fact that the numbers don't match exactly speaks for itself: even machines can't reach consensus.

Even more interesting are the large models. Media outlets posed the same question—"Predict the winner of the 2026 World Cup"—simultaneously to chatbots like ChatGPT, Grok, Gemini, and Copilot. The results? Wildly divergent answers. Some predicted France, others Spain, and one, after being thanked, calmly added: "Why don’t we revisit this prediction closer to 2026? Team conditions will change a lot."

Look, even AI is feeling guilty.

It’s true. Conditions change, injuries happen, red cards are shown, and penalties miss. These are things models can only approximate with probabilities—they can’t press the confirm button for you.

How far can AI really calculate? Don’t deify it, and don’t underestimate it.

Let’s be clear: How accurate are AI predictions for football?

There is a relatively reliable answer.

Public industry evaluations and academic studies generally point to the same range: AI predictions for the outcome of a single match (win, draw, loss) typically achieve an accuracy rate between 50% and 60%. Some studies across European leagues extend this range to 55% to 70%, depending on the model and data quality.

How do you read this number?

On the positive side: soccer has three possible outcomes, so random guessing has a 33% accuracy rate. AI achieves over 50%, which is a genuine improvement—it truly extracts certain patterns from vast amounts of data.

Put negatively: a 50% to 60% success rate means you’ll get one wrong out of every two or three bets. When it comes to predictions involving real money, this is far from being "stable."

Moreover, the league and the World Cup are completely different things.

The league sample is large, the pace is steady, and the lineups are familiar—models have plenty of historical data to train on. What about the World Cup? It’s a one-off event. New lineups needing cohesion, intercontinental travel, climate and time zone shifts, in-game mentality—these “soft variables” are barely represented in databases. This year, newcomers like Cape Verde and Curaçao, with virtually no top-tier competition data, have been added. For these teams, the model is essentially guessing blind.

The bigger the competition and the newer the participants, the less confident the AI becomes. This isn't due to inadequate technology, but because the data is inherently scarce.

Even the most skilled cook cannot make a meal without ingredients. No matter how intelligent the algorithm, it cannot create something it has never seen.

So, can AI help you win predictions? My answer

After going in a circle, we return to the original question: The World Cup is coming soon—can AI assist with predictions?

Yes, but it depends on how you use it.

My position is clear: AI is an efficient "probability magnifier," not a "crystal ball."

Its greatest value isn't telling you who will win, but helping you calculate whether this odds is truly worth it.

For example, when a bookmaker sets odds for a match, those odds implicitly imply a win probability. If an AI model calculates a win probability that is significantly higher than the probability implied by the odds, a “value” opportunity arises. Betting consistently and disciplinarily on such value opportunities is theoretically more effective than relying on intuition alone. This is where AI truly adds value: it translates vague intuition into measurable, comparable numbers.

But please firmly remember three things.

First, probability is not outcome. A model stating that Spain has a 16.1% chance of winning does not mean Spain will win; it means that "if this World Cup were replayed many times, Spain would win in approximately one out of six parallel universes." But we live in only one of those universes.

Second, upsets are the soul of football, not bugs. Morocco reaching the semifinals, Cape Verde making it to the World Cup stage—these are precisely the moments models struggle most to predict, yet they are also the most inspiring. If everything could be foreseen by algorithms, this sport would have died long ago.

Third, the house always takes a cut in gambling. AI can narrow your information gap, but it can't eliminate that mathematical edge. It's fine to treat betting as entertainment, but treating it as an ATM will eventually cost you everything back.

Ultimately, what changes are the tools—from Octopus Paul to supercomputers—but human nature remains the same.

We are still the species that faces the unknown and can’t resist peeking at the answers. Sixteen years ago, we placed our hopes in a mollusk; today, we entrust them to computational power and models. It seems we’ve become more "scientific."

But at its core, what we still want is the same thing—a little bit of certainty, in a summer where no one can be sure of anything.

AI can provide probabilities, but not certainty.

But the ball must still be kicked for ninety minutes. This is what makes the World Cup the fairest and most captivating event of all.

The whistle blows, the code resets, and the story begins anew.

Reference materials

1. Opta Analyst. "Who Will Win the 2026 FIFA World Cup? Opta Supercomputer Predictions."
2. Sports Illustrated. "Supercomputer Predicts 2026 World Cup Winner."
3. FIFA. "FIFA World Cup 2026: Fixtures, groups, teams, host countries, cities, and more." March 29, 2026.
4. ESPN. "World Cup 2026: What you need to know about all 48 teams." 2026.
5. Wikipedia. "Paul the Octopus."
6. BBC News. "What are the chances Paul the octopus is right?" July 2010.
7. The Databetics. "How Accurate Are AI Football Prediction Models?"
8. AS USA. "AI picks a winner: who will win the 2026 World Cup, according to three major chatbots." 2026.