@kheeva @Thalatta Implementing some kind of rating decay or reset seems quite appropriate to me. There are players who have had the same rating without playing a single 1v1 rated game for many years . Perhaps instead of getting tangled up in intricate calculations, “seasons” could be implemented. Basically, with each new release, all ratings would be reset and everyone would start over. It’s a fairly common mechanism. 

Ok, I think I get what you are trying to write here. You think I have never seen a solution like yours, that I've only seen the solutions I’ve mentioned, and that that’s not an argument to dismiss your solution. Well, you are wrong, I have seen solutions like yours, that’s why I say they are poorly implemented, because they show a lack of understanding on how an Elo ranking works, and the solutions I proposed solve that. The issue is, the rating is related to the winning probability, although this depends on the scale chosen. In chess (maybe 0 A.D. is the same), being ranked 400 over someone means the odds to win are 10:1, while being ranked 800 over someone is not two times better, but ten times better, the odds being 100:1. That’s why, when wanting to implement a decay, if every week you subtract different numbers from different players, you break the rating differences, and the corresponding probabilities stop making any sense. Your “we can stop here. also can decrease maximum 300 elo and make not lower 1200 that way” phrase just destroys the meaning of the Elo ratings. I mentioned the zero-sum game representation because there’s a mapping between that and the probabilities, which you mess up with the subtraction, as they are related to relative differences. The only way I see to solve this issue with your method is to subtract a given number from everyone every time, but one also has to avoid negative Elo rankings, so this number has to be obtained as a fraction of the lowest Elo rating in the ranking, which could eventually return smaller and smaller numbers with time, defeating the purpose of the decay. Thus, subtraction is a bad solution. If, on the other hand, you implement the decay as I said, reducing the influence of older games equally for everyone, the probabilities are affected correspondingly, the decay behaves always the same, and Elo ratings behave normally. Is this with “solid idea”? Or is there something still unclear?

@Outis @Thalatta I made this PDF of all the diffirent cav units/actors in the game... its quite interesting.  Take han for example for the cs and champ spearcav the portriats seems to show a shield but none of the actors do.... in some cases actors start without a shield and then add one as they rank up.  I am not a huge fan of this, unless it is REALLY historically accurate.  If in rare cases some civ had a handful of Jav cav that use shields, but most didnt i would rather just give them all Jav cav that don't have shields. CWA - Cavalry units by civ.pdf

Those are perfect! i can do them.  @Genava55 are they CC licensed ? if that so i can use the exact same black textures that match the face painting to bake them faster. Otherwise i just draw them i can draw but i already have the first electronic laboratory test next week. 

Theres something wrong when baking woman's normal map's like they are more sensitive than male low poly shape for rendering.