I Built an AI to Bet on Tennis. Then It Started Making Money — and I Stopped Trusting It.
What 263 real-world signals, an 11.3% return, and one brutal drawdown taught me about the difference between building a machine and believing one.
1. When the Machine Started Making Money
For years, I had assumed that the difficult part would be building a machine-learning system capable of finding an edge in a betting market. It took a profitable live experiment to make me realize that I had underestimated the harder problem: deciding what evidence would justify believing that the edge was real.
On March 26, 2026, I started putting my tennis model through the test I had been postponing for a long time. Instead of running another historical simulation, I began recording the bets I actually placed while matches were being played. The system had to make its decision first. Reality was allowed to answer afterward.
Five months later, I had 263 ATP betting signals in the ledger. Of those,...
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