Quote:
Originally Posted by Statsman1
I'm sure lots of actual teams use whatever they can to simulate or model predicted / expected behavior and results, but I doubt they'd admit they made any big, bold decisions based on those simulations. I would like to think that they make decisions based on exactly those things - what they expect a guy to do in the future.
I just don't ever expect to hear a GM say they made an unexpected FA signing because "this guy becomes a BEAST next year, according to OOTP17."
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if you restart the 2016 season over a few times (or the year of ootp version), you definitely learn some very very useful things. this is the exact same thing as what the op describes doing. I'm assuming this is a common thing each version for many people. there should be numerous parallels drawn each time you restart. you will definitely make a major decision involving things you gleaned while doing this.
I would use a long-term sim to hone an optimum coach and individual player strategies for AI simulation - since you don't get to play out games in an online league. i just made a post about how doing the individual palyers as well as the coach strat will add ~1-5 games a year in wins. (the +1-5 was from doing the player strats, my coach was already setup previously, then results improved relative to the Pyt +/- estimate. your coach's strategy may affect that, of course. mine was based on previous years that worked well (+3-4/year for 100years with *few negatives* is my version of "worked well"))
you can't assume it all works the same, of course. you are only thinking of a TCR change in your example - which is completely unpredictable, hence the use of random in the name... most other factors that affect change are a bit more consistent and predictable - especially in the short-term.