This question already has an answer here:
Let's say I run a lot of univariate OLS regression models, say 200,000, with 50 data points, then cherry pick the best one (highest r-square). If my $p$-value for this model is way less than 1/200,000, do my results still have any explanatory power?
The probability of getting this result when there is no relationship between the variables was extremely low, even running 200,000 instances of it, correct?
I'm generally interested in rules on how/when cherry-picking can still make sense.