This is something I did several years ago and I think originally I just mentioned it on the SABR list.
Here is an example of how the error rate can affect things. The
error rate is 1 - fielding pct. The regression below shows runs per game
as a function of OBP & SLG for each season of the NL from 1920-2012
(I used the whole league instead of teams)
R/G = 22.77*OBP + 6.7*OBP - 5.68
Now what if we add in the error rate. The regression becomes
R/G = 15.75*OBP + 9.7*SLG + 15.69*ERATE - 4.94
The relative value of OBP & SLG changed quite a bit. But this is for a whole league. The ERATE applies to the whole league.
have used the ERATE and applied it to teams. That assumes that the rate
of errors made against each team is the same. Not totally realistic,
but that is what I have. Sof it the ERATE was .02 one year in a league,
every team got that rate.
I did all teams from 1920-1998. Here are the two regressions
R/G = 19.89*OBP + 9.79*SLG - 5.95
R/G = 17.63*OBP + 10.7*SLG + 13.51*ERATE - 5.87
So again the relative values of OBP & SLG change