[NoOne]

approach it in an objective way... this is ootp video game, so i am only talking in reference to it, not RL baseball. and, only Batting Average - example should be easy to extrapolate and apply to other things.

What's relevant in the game?

Contact is made up of BABIP, Avoid K's and Power in OotP.

We have access to stats that directly and objectively relate to these ratings


understand statistical environment not changing much is also key: the league environment as defined by a static set of well-callibrated LTM/LT and related Stats and AI settings, plus PCMs that created the players when LTMs are callibrated with auto-calc (-if). in these situations, ratings = probability of results and remain consistently defined.. even if LTMs change a small bit (auto-calc, for example), as long as the totals and other stats and ai settings are unchanged, it will be in the near vicinity, nonetheless.

So,

BABIP stat = BABIP rating
K/AB = Avoid K's
HR/AB = Power

with a large enough sample, these things will tell you fairly accurately what the ratings are. With a little experience and objective observation you can easily translate this into an expected BA for your league's statistical environement. (ignoring that ratings can change constantly, of course... have to consider that, too... if not stats-only, scouting reports help greatly)

because these 3 stats resolve earlier much earlier than 1000AB (a confident BA sample size), you can also deduce whether a small sample BA will increase or decrease over time, assuming consistent ratings/talent. with ratings on, what i said above about easily tanslating is the same thing.

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I've never cared to deduce the equation for Contact, and each league is a bit different for results... i.e. different league totals will require a different expected BA results for the exact same ratings (not contact, the three that make it). example: higher HR league total means power will have a greater influence on BA, than a lower HR league total.

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the key anything similar is that it should be a rate and directly or partially tied into the factor at hand -> BA in this case (in ootp this means the individual basic ratings you find in editor, not necessarily the profile - e.g. you don't see overall defense or overall/potential etc, contact is broken up even if displayed added together)

competition obviously plays a role, too.. big part of why you need to consider sample sizes of these values (it's part of what needs to be resolved with time/opportunity)... stop thinking of it as per season... samples of data should be from when they are similarly rated, or you believe them to be if you play stats-only.

physics don't change seaon to season, people do. the slack off, the work harder, whatever... in the game this is slow changes over time based on personality and aging etc etc.. so, applying this is more sophisticated than explaining it... it's all relative though! you accept what the information is - good, bad, ugly and work with what you have.. knowing when it is a more of a guess is useful information, too.

Also, not all resulting stats we have access to so neatly and cleanly relates to the ratings... but, there's always a way to make sense of it. and, relative to this stuff there is empirically a "best" way to do it... simply about playing odds and nothing else.