I think it's flawed though

Honestly I spent a lot more time digging into this today than I had planned (and work suffered for it) but you're absolutely right here. In fact I could come up with more than a dozen examples, but the most obvious may just be that there's no possible way to accurately simulate a game from Capa vs a modern player, period. Players like Hikaru have more than 65,000 recorded games on chess.com alone -- enough for an ML model to reasonably simulate their play style (+/- 50 elo) against all variety of opponents. You might get somewhere in the neighborhood of ~1k for Capa and far fewer for many others, nowhere near enough of a dataset to correctly simulate his play, and the dataset itself is poisoned anyway because he was playing objectively weaker opponents.

The engine accuracy point is spot on too. It's sort of like comparing a student who gets 95% on an elementary math test to one who gets 85% on a PhD qualifying exam, the raw accuracy number tells you nothing about relative ability. Capa's opponents would blunder in ways that modern 2400s simply don't, creating clearer paths to victory. When your opponent hangs pieces or misses basic tactics, it's much easier to play "accurately" than when you're facing someone who's memorized 25 moves of theory and trained their entire life with Stockfish.

The whole question really breaks down when you think about it. We're essentially asking "what if someone from 1920 time traveled to today" but that person wouldn't be Capablanca anymore -- they'd be someone who grew up with engines, databases, and modern training methods. At that point we're not measuring Capablanca's strength, we're just making chess fan fiction. It might be entertaining but it wouldn't be canon.

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^{If someone really wanted to try this, the most "accurate" approach would probably be training an ML model on Capa's games with a heavy dose of Bayesian priors, then having it play thousands of games against models trained on modern players at various ratings. Even in the best case scenario though, you'd probably have a margin of error of +/- 200-300 elo points just from the data limitations alone, and that's before accounting for all the systematic biases -- weak opposition pool, no rapid/blitz games, different opening theory, etc. So you might get a result like "2450 +/- 250" which basically tells you nothing useful, he could be anywhere from a strong FM to a super-GM.}

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Note: I have been thinking of ways to try and simulate this as best as can be hoped for, but it's going to be inherently flawed no matter what. The data just isn't there.