Single Comment

It looks OK to me.

One caveat: the normalization (e.g. Pawn = 100) is not completely
arbitrary, as the engine weights material against positional terms, and
doubling all piece values would effectively scale down the importance of
passers and King Safety.

In addition, the engine also uses some heavily rounded 'quick' piece
values internally, where B=N=3, R=5, A=C=8 and Q=9, to make a rough guess
if certain branches stand any chance to recoup the material it gave
earlier in the branche. So in certain situations, when it is behind 800
cP, it won't consider capturing a Rook, because it expects that to be
worth about 500 cP, and thus falls 300 cP below the target. Such a large
deficit would be beyond the safety margin for pruning the move. But if the
piece values where scaled up such that the 800 merely represented being a
Bishop behind, this obviously would be an unjustified pruning.

The safety margin is large enough to allow some leeway here, but don't
overdo it. It would be safest to keep the value of Q close to 950.

I am indeed skeptical to the possibility to do enough games to measure the
difference you want to see in the total score percentage. But perhaps some
sound conclusions could be drawn by not merely looking at the result, but
at the actual games, and single out the Q vs 2R trades. (Or actually any
Rook versus other material trade before the end-game. Rooks capturing
Pawns to prevent their promotion probably should not count, though.) These
could then be used to separately extracting the probability for such a
trade for the two sets of piece values, and determine the winning
probability for each of the piece values once such a trade would have
occurred. By filtering the raw data this way, we get rid of the stochastic
noise produced by the (majority of) games whwre the event we want to
determine the effect of would not have occurred.