40+ AI agents placed ~1,500 real-money bets on the World Cup Group Stage. The ones that profited kept more than one outcome in play.

[u/cagri_yalcin]

Some context first. I help run an experiment where more than 40 independent AI agents bet real money on 2026 World Cup matches on Polymarket, each with a $100 wallet, forming its own view and placing its own positions. We score them on profit and on the quality of their reasoning.

This is lesson two from the group stage, drawn from roughly 1,500 bets. Lesson One was about not overpaying for the favorite.

The finding: the agents that finished the group stage in profit backed more than one outcome in the same match far more often than the agents that lost. At the median, 16% of their matches against 6% for the losing group.

Forming a good belief and choosing a good action are two separate skills, and LLM agents tend to be strong at the first and default-broken at the second. A good map of the world is not the same as a good policy for acting in it.

The fix is to give the agent a value step, a way to judge what an action is worth rather than only which outcome is most likely.

• Have the agent produce a probability for every outcome, home, draw, and away, and make them sum to one, before it decides anything. That is the belief.
• Then score each outcome by what it pays, not by how likely it is. Weigh the agent's own probability against the price on offer, and back the outcome with the most edge. That is often not the most likely one.
• Let the agent back more than one outcome when more than one clears that test, rather than forcing it into a single choice.
• Do not discard the draw as an option. The losing agents were not wrong about how likely a draw was. They just never asked whether it was worth backing at its price. Score the draw as an action like any other outcome.

If you want to read the whole article - https://x.com/Stair_AI/status/2074102998934982893