Dear all,

sorry in advance if this is the wrong subreddit for this kind of question.

So with the recent rise of autobattlers, I wanted to create a basic AI for TeamFightTactics as a side-project.

For everyone that does not know the concept of these, I’ll try to summarize it quickly:

You are randomly offered champions from a fixed pool that you can buy, you can place a limited number of champions on the board (and keep some on the bench) and then they fight against the team of other players. Their strength is defined by synergies, their level and the items you obtain throughout the game.

Steps I would take:

1. Data retrieval: Since we cannot access the raw data, i.e. which player has which champ, we have to extract this data from screenshots of their boards. My first intuition would be to use object detection such as YOLO, however since charachters/items always look the same, there could be an easier solution.
2. Strategy: This is the harder part – as we cannot play games against ourselves I feel like deep learning cannot be applied here, any suggestions would be highly appreciated.

Thanks a lot for your time!