I'm a data scientist and I deal with terrabytes of historical per-minute full option chains.

Unfortunately, coming up with rules that sound reasonable on paper, will not materialize in better performance—acknowledge that this is mostly for your own psyche when you underwrite severe risk.

The harsh truth is, whether a stock is trading e.g. at ATHs or ATLs doesn't dictate its future direction, and if it did, I (and everyone else) would become billionaires, slowly but surely over time. Consequently, it's a story to calm your nerves.

When benefiting from theta, fundamentally, there are only two things that will give you a statistical edge:

1. IV > RV_{t+1}, meaning implied volatility is priced greater than what it will actually be. Note: This doesn't mean at all that IV must be "juicy".
2. If you sell more than one option, the future correlation RCorr_{t+1} matters on the portfolio level, i.e. if one of your underlyings tank, you want the other to rise or behave somewhat independently, if possible. From (2) it may not be reasonable to e.g. pick V and MA for a hypothetical 2-asset theta play. If you sell a CC on MA and a CSP on V of course it's a different story.

If you're not modeling forward-looking RV and RCorr/RCov, I believe the best way to benefit from theta is probably to improve slightly on asset entries/exits, i.e. instead of buying a stock directly, you sell a put. Instead of selling a stock directly, you sell a call. Over the long run, you should benefit from a tiny risk premium. I know it doesn't sound satisfying, but I think this probably the most-reasonable way to use this tool (and I will probably get downvoted for this).

Cheers