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basically it's converting relative to modern day values... so, it won't match up to historical environment..
e.g. if the editor consistently under reports walks, you can expect it for every player's 'estimates' in the editor for that league.
easier to explain with batters, but same concepts:
i don't use modern values for HR.. i use fewer. so, when i look in an editor it over-predicts homeruns by about ~10-15%... probably disproportionately affects the high end guys more than the middle of the road guys, too. i.e. and not just due to "10%" multiplied by a larger estimated #.
for your situation to get a rough estimate without any observation:
i would compare the league totals (relative to #of teams and # of games played - not just the "totals" on their own) between the league totals you see for MLB quickstart and your historic league...
e.g. if you see 25% fewer strikeouts, you can expect fewer strikeouts than what the editor predicts... will it be 25%? probably not, but a good ballpark to start... with more experience and observation you can have better guess as to the real difference.
no guarantee the modern Stats and AI total values from a modern league are what the editor is using, either... but a good starting point, nonetheless.
use multiple players and compare eresults to prediction in editor... figure out a rough Conversion % per stat...
if you want to change ratings based on stats input into editor, factor that %-difference between prediction and results into what values you use.
if you find that the editor is 25% over-predicted for K's, make sure to reduce by 20% or in other words use 80% of that value instead (use recipricol of difference - in this case 4/5 is reciprocal of 5/4 - 5/4ths is a 25% over-prediction)
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