The problem in these cases tends to be that there is no evidence. So you take as complex a form or BT as possible, then put in numbers that 'sound reasonable',

The problem in these cases tends to be that there is no evidence. So you take as complex a form or BT as possible, then put in numbers that 'sound reasonable', end up with a conclusion that supports your prior beliefs and claim it is mathematically correct, because BT has been proven, don't you know! The problem with your point about BT 'should assign a high probability' is that when you're reasoning about messy real world situations, lacking objective, quantitative data, it isn't clear how you go about generating probabilities for most kinds of evidence. It is no coincidence that the cited examples tend to be somewhat frequentist. When you start having probabilities like "the probability the disciples would have lied about seeing Jesus" you're doomed already. Not to mention the fact that BT assumes you can exclude the middle, which runs up against problems of definition in real situations: what exactly does "Jesus didn't exist" mean? You can hide a lot of rabbits in that hat. But anyway, this is getting way off the track for the OP, sorry for the derailing. tl;dr - it is hard to model the real world in mathematical models of epistemology.