The book was science history rather than science, so I felt like we really didn't get the meat of why Bayesian probability was so controversial. There were plenty of examples of why people kept going back to Bayesian principles (frequently reinventing them!)--- basically because the frequentist approach couldn't answer the questions they were wanting to ask! But the difference between the two approaches was scattered throughout the history rather than really being spelled out in any way a lay reader could be expected to grasp, with some well-structured examples comparing the two approaches.
(My attempt: the frequentist approach says that probability is about the limiting behavior of infinite sequences. If you don't have one, or at least pretend to have one, then the frequentist answer is that you aren't asking a statistical question. But, if you do, then the answer you get is "objective." Bayesians say that probability is a statement of belief, which can be modified as more information comes in. But initial beliefs might be "subjective", such that the same evidence could support two different outcomes.)
The last-finished book of the year is volume 4 of _Unwritten_, "Leviathan", which has a lot of whales in it. Unless I finish "Ghost Story" tonight, which seems unlikely.