Player Evaluation numbers on AI settings
Do most of you stick with the default percent's or tweak them a bit?
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I go with:
40 30 20 10 And also make sure "overall ratings based on ai evalution and not pure ratings" is enabled. That way, overalls are based on a nice mix of both ratings and recent years stats. Overalls jump when a player is coming off a great season, even if his individual ratings are not that impressive. |
Thanks for the info!
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23
32 25 20 |
15
50 25 10 |
My favorites are
0 50 25 25 & 25 25 25 25 |
Ratings Only
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50/30/15/5
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I think giving more weight to the past 2 seasons only confuses the AI during the season. It is good for the off-season and salary calculations, but if Billy Bob sucks now, who cares if he was any good 2 years ago? I'll bench his butt and I want the AI to, also.
I am currently using 25/68/5/2 I also think going all-ratings is not good for the AI. It appears that the AI evaluates stats better than it does the ratings. This is especially true if you play in an environment that does not produce stats the same as current MLB. For instance, if you play in an era when Home Runs are more scarce, the AI will over-value the Power rating. |
I'm using:
10 60 20 10 |
It seems most folks like the low ratings weight, and tier down from current to two years ago.
This is quite helpful for a noob like me. Thanks! |
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I really don't think these settings do all that much.. unless you use extreme numbers one way or the other... pure speculation on my part.
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One qs with mostly stats ratings, Atlanta has ss Simmons in aaa all year. More ratings he is called up the next day and is never demoted. The trick is finding the right balance of ratings and stats. Like quest I agree that 2 years ago are mostly useless for ai. Now I go with 30 60 8 2 |
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They are very much useful for the AI. Like you said its about balance. Everyone has their uses. Some may want AI to be perfect in their decisions while others may want realism and watching the AI DFA a player who was an all star 1-2 years ago because he had a bad couple months is not that realistic especially if the said player is still young.. |
I'm in my 6th year as GM of the Twins, using 60/25/10/5, but very tempted to try 50/33/13/4
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I haven't seen anything crazy using 50/30/15/5 so maybe they are doing their thing. ;) |
using stats to some extent will make decisions a little more life-like. GMs will have a chance to be fooled by randomness(stats) instead of using the concrete ratings, which determine actual probability of success within the game. this assumes 'normal' scouting accuracy or better. i have no experience with lesser accurate scouting in regards to these settings.
if you resim 2015 over many times (50+), and then repeat that process while keeping all settings, players, coaches, the year(2015) the same except for Scouting/AI Eval options, you will see that 100% accurate or normal accuracy for ratings and no stats ai eval results in elevated league-wide offensive numbers when compared to 100% stats evaluation. the proof is in the pudding. this is based on empirical evidence, not personal preference or emotional attachment to one settings or another. i am not suggesting you use any particular method, but understanding how it influences the ai might help you decide how you want to play the game and how you want it to work. stats are a derivative of ratings and numerous other factors in the game, including luck. so, if you use stats for evaluation, they do not paint as clear a picture - this is incontrevertable fact. they are mucked up by many factors outside of the player's actual ability. whether or not you prefer that element in the game is a matter of opinion. lowering scouting below 'normal' and having really poor scouts/scouting budgets may make what i said false. i have never tested this setting in that environment. so, there is possibly a break-even point where stats will start to become a better indicator of future sucess as scouting gets less and less accurate/reliable. |
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Having a healthy chunk of stats in the AI evaluation helps compensate for the shortcoming of the ratings evaluation routines. It let's the AI see for itself that the fella it thought would do well as starting pitcher really is worthless. |
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