Another issue with the approach is that the model had direct access to game data, that is simply an unfair competitive advantage in dota, and it is obvious why that advantage would be unfair in CS.

It is certainly possible, but i won't be impressed by anything "playing CS" that isn't running a vision model on a display and moving a mouse, because that is the game. The game is not abstractly reacting to enemy positions and relocating the cursor, it's looking at a screen, seeing where the baddy is and then using this interface (the mouse) to get the cursor there as quickly as possible.

It would be like letting an AI plot its position on the field and what action its taking during a football match and then saying "Look, The AI would have scored dozens of times in this simulation, it is the greatest soccer player in the world!" No, sorry, the game actually requires you to locomote, abstractly describing your position may be fun but it's not the game

Did you read the paper? It had access to the dota 2 bot API, which is some gamestate but very far from all gamestate. It also had artifially limited reaction to something like 220ms, worse then professional gamers.

But then again, that is precisely the point. A chess bot also has access to gigabytes of perfect working memory. I don't see people complaining about that. It's perfectly valid to judge the best an AI can do vs the best a human can do. It's not really fair to take away exactly what a computer is good at from an AI and then say: "Look but the AI is now worse". Else you would also have to do it the other way around. How well could a human play dota if it only had access to the bot API. I don't think they would do well at all.