I built a free 2026 World Cup prediction tool as a fun side project.
The soccer part was fun, but the AI part ended up being more interesting.
I tested four different prediction views:
My own methodology
A tournament-read model based on current form, roster age and fitness, squad depth, style matchups, counterattack danger, fatigue, climate, penalties, manager decisions, and bracket path.
Betting odds only
A market-based view.
ChatGPT independent forecast
I did not give it my methodology or preferred winner. I simply asked it to build the best prediction it could using its own logic.
Gemini logic forecast
This one was the most interesting. Gemini asked me who I was rooting for before making its prediction. Then, in my testing, it chose that team to win. When I changed the team I said I was rooting for, Gemini changed the winner to that team too.
That stood out to me.
Not because it is evil or anything dramatic like that. But it is a good reminder that AI can lean toward making the user happy. If you feed it a bias, it may hand that bias back to you with better wording and more confidence.
The biggest lesson from the project was simple:
Good input in, good output out. Garbage in, garbage out.
AI is powerful, but it still needs human judgment. It can organize thinking, compare logic, test assumptions, and help build something useful. But it still depends on the person using it to understand the situation, challenge weak assumptions, and know when an answer sounds right but may not actually be right.
The tool is a standalone HTML file. It is not a live data feed. It does not automatically update injuries, suspensions, weather, lineups, or odds movement. Users can enter live group-stage scores manually, but anything else has to be adjusted by the user.
I’m curious how others think about this:
When an AI asks for your preference before giving a forecast, is that helpful context, or does it risk steering the answer toward pleasing the user?
Also happy to drop a link for download if anyone wants it.
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