I'm not great at poker, but I did play a decent amount and I know a lot of my strategy involves probing for other people's weaknesses and shifting my strategy mid game to throw people off.

I feel like a lot of trained ML models have a lot laughable weaknesses, but perhaps they've been trained on every game they're well prepared for any tomfoolery.

The bot is trained to play Game Theory Optimal, aka it's playing to be breakeven at worst, which is why I believe it would be hard for a human to beat it. It's not playing perfectly, but the edges it's giving up is so marginal to perfect play that a human is going to lose simply by making a mistake at some point, even if a human were to use a solver to completely optimize their strategy.