Quote:
Originally Posted by justafan
Actually, not using a spreadsheet, I'm just writing a little league browser. I'm not sure if it will turn in to anything, just needed something to try out some new controls with. It's nowhere near done, but this is how far along I am...
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i meant to hammer out the actual equation they use, which you could incorporate into what you are working on as intended. it's possible with a spreadsheet...run a "multiple regression" or somethign liek that? use a short list of players and their ratings with overal being what they 'predict.' (you won't need many because we know the ratings actually add up to the overall in a very consistent manner)
i would think the weights would all add up to 1 or you can use them to figure out each ratings weight relative to each other (use as ratios, that add upto 1) - rounding could cause some amount of inaccuracy.
use editor values (1-200) and 20-80 scales for overall/potential with 100% scouting accuracy, since that overall isn't in the editor - this will minimize the effect of rounding, even if you prefer to use a different scale when playing the game. avoid players with >200 ratings in the sample data you give to the spreadsheet. >max may be handled differently, not sure. maybe it's ignored, maybe it's still in proportion.. either way remove it to learn the weights for normal ratings, then test that equation with someone with >max rating(s).
you'll know immediately if it doesn't predict the overall correctly. and if it does, it works for those guys, too. (obviously test the data-mined algorythm for overall on a normal player from outside the sample data set, too).