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Muhamad Kautsar
Muhamad Kautsar

Posted on • Originally published at Medium

I Asked My AI Agent to Predict Every World Cup 2026 Match. Here's What Happened.

The tournament started June 11. I had an AI agent running on my personal server. The obvious next step was obvious.

So I did it. I fed my AI agent — AkiraAI, which I built myself and runs 24/7 on my own server — live World Cup 2026 data and told it to predict every single group stage match. All 104 of them.

Some results were embarrassing. Some were eerily accurate. And one prediction genuinely made me stop and stare at my screen.

Here's the honest breakdown.


First, Why I Built My Own AI Agent in the First Place

AkiraAI isn't a wrapper around ChatGPT. It's a full agent I designed and deployed — web search, document generation, reminder systems, code management, the whole thing — running on a VPS I personally manage.

I built it because I got tired of switching between 12 different tools to get work done. One agent that actually does things, not just talks about them.

So when World Cup 2026 kicked off with 48 teams and 104 matches — the biggest tournament in FIFA history — it felt wrong not to put AkiraAI to work on it.


What I Actually Fed It

No, I didn't just ask "who wins the World Cup?" That gives you a generic answer every time.

Instead, I gave it:

  • Current FIFA rankings per team
  • Each team's qualifying form (last 10 matches)
  • Key injury reports as of June 11
  • Head-to-head records for each group stage matchup
  • Travel distance between matches (rest time matters more than people think)
  • Historical World Cup group stage patterns

Then I asked it to predict scorelines — not just win/draw/loss — for every group stage match.


The Results Were... Interesting

Where it was eerily accurate:

Iran vs. New Zealand. AkiraAI predicted a draw, 1-1. The real result: a tense draw with New Zealand's Elijah Just scoring twice and Iran equalizing through Mohammad Mohebbi. Not exactly 1-1, but the draw call with both teams scoring? Spot on.

Saudi Arabia in Group H. AkiraAI flagged them as an "upset candidate" based on their 2022 World Cup data where they beat Argentina. Sure enough, Abdulelah Al-Amri scored their first goal of the tournament against Uruguay.

Where it was completely wrong:

It underestimated Sweden badly. Viktor Gyokeres and Alexander Isak are in form that no historical dataset fully captures right now. AkiraAI had Sweden winning narrowly. They struck five. Five.

Haiti giving Italy a fright? It didn't see that coming at all. Neither did I, honestly.


The Part That Made Me Stop

After running all predictions, I asked AkiraAI a follow-up: "What's the single biggest variable you can't account for?"

Its answer: "Individual brilliance in high-pressure moments."

It explained that every model — no matter how much data you feed it — essentially averages out human performance. But World Cups aren't won by averages. They're won by a Messi at his peak, a Gyokeres who's unstoppable right now, a goalkeeper who has the game of his life.

That hit different. Because it's not just true for football. It's true for everything.

AI is extraordinarily good at seeing patterns. It's still terrible at predicting when someone breaks them.


What This Actually Taught Me About AI

Running this experiment for a week clarified something I'd been vague about:

AI prediction tools are confidence machines, not oracle machines.

They give you a probability with authority. That authority feels like certainty if you're not careful. Squawka's AI predictor, OddsFlow, ChatGPT bracket predictions — all of them produce clean, confident numbers. But football doesn't care about clean numbers.

The best way to use AI for this? Not as a predictor. As a filter.

Use it to quickly eliminate the 70% of matches that are genuinely predictable (heavy favorites vs. minnows). Then spend your actual thinking time on the 30% of matches where the model uncertainty is highest — those are the games that'll define the tournament.


Is Spain Actually Winning This?

ChatGPT says Spain. Most AI models say Spain. AkiraAI also leans Spain based on FIFA rankings, recent form, and their qualifying dominance.

Personally? I'm not so sure. France and Brazil are lurking. England has a realistic path. Argentina are the reigning champions and Lamine Yamal is 18 years old playing like he's been here before.

I'll let AkiraAI keep tracking as the knockout rounds approach. I'll share updates as results come in and predictions get tested against reality.


The Bottom Line

I built an AI agent. I pointed it at the World Cup. Here's what I actually learned:

AI is a brilliant analyst. It's a mediocre prophet.

The data it surfaced — travel schedules, rest patterns, head-to-head records — genuinely made me understand some matches better than I would have without it. But every time a Sweden striker is on fire, or Haiti pushes Italy to the edge, the model shrugs.

That gap between "pattern recognition" and "human unpredictability" is where football lives. It's also where the best AI research is happening right now.

I'll keep running the predictions. And I'll keep being wrong in interesting ways.

Follow along if you want to see how this plays out — I'll post updates as the knockout stage hits.


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