Exploring MCTS / self-play on a small 2-player abstract game — looking for insight, not hype

Hi all — I’m hoping for some perspective from people with more RL / game-AI experience than I have.

I’m working on a small, deterministic 2-player abstract strategy game (perfect information, no randomness, forced captures/removals). The ruleset is intentionally compact, and human play suggests there may be non-obvious strategic depth, but it’s hard to tell without stronger analysis.

Rather than jumping straight to a full AlphaZero-style setup, I’m interested in more modest questions first:

• How the game behaves under MCTS / self-play
• Whether early dominance or forced lines emerge
• What level of modeling is “worth it” for a game of this size

I don’t have serious compute resources, and I’m not trying to build a state-of-the-art engine — this is more about understanding whether the game is interesting from a game-theoretic / search perspective.

If anyone here has worked on:

• MCTS for small board games
• AlphaZero-style toy implementations
• Using self-play as an analysis tool rather than a product

…I’d really appreciate pointers, pitfalls, or even “don’t bother, here’s why” feedback.

Happy to share a concise rules/state description if that helps — but didn’t want to info-dump in the first post.

Thanks for reading.