What are the standards for algorithmically forecasting metagame evolution under certain conditions of TCG design?
It is likely that making this kind of prediction to any useful degree of accuracy is beyond the current state of the art in computing.

First, consider that forecasting the future metagame that uses unreleased cards is essentially equivalent to "forecasting" the current metagame using the current card pool. This actually helps, because that means that you can validate your methodology against every current and past metagame.

So, the task is now to create a simulation that takes the existing card pool, and produces the current metagame. In order to do that, you need to understand and reproduce the reasons that the metagame exists as it currently does. There may be a variety of reasons that a deck may be stronger or weaker in a metagame, including raw deck strength, how easy the deck is to pilot, and how flexibly it can handle different matchups. There are also additional reasons that a deck may appear more or less in a metagame, including card availability, card prices, people's existing decks and collections, and how well it matches popular deck-building heuristics.

In order to understand the strength of any single deck, you would need to be able to pilot it at a pro level to evaluate how it would perform in real top-level tournaments. To my knowledge, there are currently no programs that can play trading card games that well. The cutting edge of research into making computers play games better than humans is probably AlphaGo, and that task is probably simpler because it plays deterministic games on a single pre-defined board.

If you do somehow manage to produce a program that can accurately simulate how any particular matchup would play out, you would need to figure out what matchups are worth testing and evolve that into a stable metagame. This may require independently reconstructing modern deckbuilding strategy, while also allowing for potential rogue decks that exist outside of that strategy. This is the point where you may need to account for the factors like card availability and price. Price is also heavily dependent on metagame popularity, so that would also need to be simulated and fed back into the main simulation. This is also where you would need to evaluate whether a human could and would actually pilot that deck effectively.

Let's say you do manage to put all of that together into a working prediction machine. There are still some potential pitfalls to be aware of. You may miss a rogue deck that is outside of your search space that completely breaks things. Your players may fail to think of a specific deck that features heavily in your simulated metagame, unbalancing the rest of the metagame. You may mispredict whether players would actually be willing or able to use a deck in tournaments, again potentially unbalancing the metagame.