The precise probabilist can respond to the weight/balance distinction argument by pointing to the property of resiliency (Skyrms 2011) or stability (Leitgeb 2014). The idea is that probabilities determined by the weight of evidence change less in response to new evidence than do probabilities determined by balance of evidence alone. That is, if you’ve seen a hundred tosses of the coin, seeing it land heads doesn’t affect your belief much, while if you’ve not seen any tosses of the coin, seeing it land heads has a bigger effect on your beliefs. Thus, the distinction is represented in the precise probabilistic framework in the conditional probabilities. The distinction, though, is one that cannot rationalise the preference for betting on the fair coin. One could develop a resiliency-weighted expected value and claim that this is what you should maximise, but this would be as much of a departure from orthodox probabilism as IP is. If someone were to develop such a theory, then its merits could be weighed against the merits of IP type models.