What’s Wrong With Using Bayes Theorem to Evaluate Miracles?

In a previous post I spoke on the topic, Miracle Claims Asserted Without Relevant Objective Evidence Can Be Dismissed. Period! At the end I had some closing thoughts about Bayes Theorem and miracles. I'm highlighting it for thought below.
What’s Wrong With Using Bayes Theorem to Evaluate Miracles?
Now I want to end by talking briefly about Bayes Theorem. In his writings and talks Richard Carrier does a good job of explaining it.
It asks us to input a number which we consider the prior probability of a given hypothesis we wish to test, say of whether a crime took place. Then it asks us to input some numbers for important posterior questions like, what should we expect to find if a crime took place, compared to if it didn’t? For instance, we might expect to find a dead body, showing evidence of a struggle, as opposed to a dead body lying peacefully in bed. Then it asks us to input numbers for the relevant background factors that would increase or decrease that prior probability, like if the suspect had a motive for murdering the victim, or if the victim was suicidal, and so on. After inputting the numbers in the equation we do the calculations, and the resulting percentage is the probability that a crime took place.
Now I don’t object to using the Bayes’ Theorem when it's applied appropriately to questions for which we have prior data to determine their initial probability. But Bayes Theorem is treated by some people as the only tool in their tool chest. To people who only have a hammer, everything looks like a nail. That’s the problem. 
I have five objections to it:
1) With miracles there is no previous data to work from.
Bayes can only be useful when there is prior data to work from. We’re told every logically possible claim has a nonzero probability to it. But miracles don’t have any prior probability. A flying pig would be a miracle. So we need prior data to work from. How many pigs have ever flown of their own power? Without any previous data Bayes isn’t the proper tool to use here. All we know is that there is no objective evidence for such a thing. That’s more than enough.
There have been as many as 120 billion human beings who have lived at some time on this planet. Since there’s no reason to think any virgin birthed a god, or anyone resurrected from the grave, the odds of each of these two miracles are as low as the number of people who have ever lived on this planet. 1 out of 120 billion! Since we don’t know when the first occurrence of a virgin birthed deity or a resurrected person will be in the future, there could be an additional 120 billion people before such an event like that takes place, or more, like three times more, or never. So if you cannot input a number for the initial probability you have nothing to calculate.
It’s argued that we should be generous with our numbers when dealing with miracles, by inputting a better sounding number. But why? Why be generous if we’re seeking truth? I see no reason to do so.
2) Bayes won’t help clarify our differences.
We don’t need Bayes to know where our differences are to be found. We already know. The main difference between us is that believers value faith, blind faith, the only kind of faith there is, faith without objective evidence, while nonbelievers value sufficient objective evidence. That’s why we're nonbelievers, and that's why believers continue to believe based on ancient 2nd hand hearsay testimony about a miracle.
3) Bayes gives undue credibility to some miracle claims over others when none of them have any objective evidence for them.
I’ve written a book called Unapologetic on why responding to fundamentalist arguments in kind gives their beliefs a certain undeserved respectability.
To treat the resurrection story as if we have some objective evidence for it when we don’t, is to give it undeserved credibility over other miracles, especially the ones located in very gospel texts where we read of the resurrection. Why is no one doing a Bayesian analysis of the virgin birthed son of god? That's the point!
The only response to a claim that a pig can fly of its own power is to see one fly under test conditions. Lacking any objective data that shows pigs can fly of their own power, the proper way to deal with such a claim is to dismiss it. To go through the motions of calculating such a probability beginning with a completely made-up nonzero prior probability is foolishness, and would give people the credibility they so desperately crave for such a bizarre claim because we took it on.
4) Bayes won’t help convince anyone.
Bayes is probably worse off in terms of convincing others, for the only people who would sludge through it are far less likely to be convinced by it. Just ask to see the objective evidence, and if it’s lacking, like it is, then dismiss it.
The truth is people are using Bayes and coming to very different conclusions:
-- Vincent Torley calculated there’s about a 60-65% chance that Jesus rose up from the dead. Now after reading Michael Alter’s book, Resurrection: A Critical Inquiry, he doesn’t think historical evidence can show a miracle happened. Now it's probably down to 20-30% for him. 
-- Richard Swinburne calculated the probability of the bodily resurrection of Jesus is 97%.
-- Timothy McGrew and Lydia McGrew calculated the odds of the resurrection of Jesus to be 1 followed by 45 zeros to 1. Can anyone do better?
In Richard Carrier’s estimation Bayes leads him to think the probability that Jesus did not exist is 67%. So much the worse for his resurrection!
If  Bayes helps us then why does it produce these wide diverse results? Tools are supposed to help.
5) Imagining what might convince us is largely an exercise in futility.
Bayes asks us to imagine what might convince us of a given hypothesis. This is a reasonable request in criminal trials, and other kinds of scenarios  where actual evidence is being considered. But in order to imagine what would convince us of miracles, it would require changing the past, and that can’t be done. If I could go back in time to watch Jesus coming out of a tomb, that might work. But I can’t travel back in time. If someone recently found some convincing objective evidence dating to the days of Jesus, that might work. But I can’t imagine what kind of evidence that could be. As I’ve argued, testimonial evidence wouldn’t work, so a purported handwritten letter from the mother of Jesus is insufficient. If a cell phone is discovered and dated to the time of Jesus, which contains videos of him doing miracles, that might work. But come on, this is as unlikely as his resurrection. If Jesus, God, or Mary themselves were to appear to me, that might work. But that has never happened, even in my believing days, and there’s nothing I can do to make it happen either.
In any case, imagining what could convince us of a miracle only arises when using the hammer of Bayes on the nail of miracles. Imagining evidence that could convince us Mary gave birth to a divine son sired by a male god is a futile exercise, since we already know there’s no objective evidence for it.
One might as well imagine what would have convinced us in 1997 that Marshall Applewhite of the Heaven’s Gate suicide cult, was telling the truth that an extraterrestrial spacecraft following the comet Hale–Bopp was going to beam their souls up to it, if they would only commit suicide with him.
One might even try to imagine today what would convince us that he and his followers are now flying around the universe. Such an exercise is utter tomfoolery.
Thank you for your consideration.