  Shafer (2021) offers a betting perspective on statistical testing which may
be useful for foundational debates, given that disputes over such testing
continue to be intense. To be helpful for researchers, however, this
perspective will need more elaboration using real examples in which (a) the
betting score has a justification and interpretation in terms of study goals
that distinguishes it from the uncountable mathematical possibilities, and (b)
the assumptions in the sampling model are uncertain. On justification, Shafer
says 'No one has made a convincing case for any particular choice' of a score
derived from a P-value and then states that 'the choice is fundamentally
arbitrary'. Yet some (but not most) scores can be motivated by study goals
(e.g., information measurement; decision making). The one I have seen
repeatedly in information statistics and data mining is the surprisal, logworth
or S-value s = -log(p), where the log base determines the scale. The present
comment explains the rationale for this choice.
