I guess in practice it’d be the tiniest shred of plausible deniability. If your prior is that alice@example.com almost surely didn’t enter the contest (p=1%) but her hash is in the table (which happens by chance with p=1/1000) then you Bayesian-update to a 91% chance that she did in fact enter the contest. If you think she had even a 10% chance on priors then her hash being in the table makes you 99% sure it’s her.
I guess in practice it’d be the tiniest shred of plausible deniability. If your prior is that alice@example.com almost surely didn’t enter the contest (p=1%) but her hash is in the table (which happens by chance with p=1/1000) then you Bayesian-update to a 91% chance that she did in fact enter the contest. If you think she had even a 10% chance on priors then her hash being in the table makes you 99% sure it’s her.