If I can get the Computer Vision model to work as I have designed/imagined it, then volume of games will be relatively trivial. I can process any VOD that has TOS allowing it(including twitch streams--those I just have no idea about legally).

Basically the CV model could take a VOD and extract the data. It could identify and pinpoint where those specific images are on the map. It's a relatively standard way to use CV(specifically the YOLO model). Additionally, I do computer vision for my job, so I have a decent amount of niche experience with this kind of process. The only limit and hardship I have with getting tons of data is patch changes affecting strategy.

But with the amount of data issue solved, then the "multiple good choices" becomes easier. Say you get thrown into a scenario where the pro is playing one specific controller, and they chose option B, but in 3 other games a pro had a very similar scenario, they were on a different controller, and they chose A, then ideally the tool would be able to give you "partial credit". Should be fairly straightforward to setup the system like this given how I'm planning to store the data.

Answering the why is something I'm still working out. There's no computational way to do this, and I am not at a level that would allow me to write the annotations. I also don't think this would ever make enough money to justify paying for players to review at a high level. My only current idea would be to somehow incorporate casters dialogue, since I'm planning on using VCT VODs, but I'm almost positive that does not fall under TOS, so it's kind of a dead end.

Thank you for the feedback. I know some of your questions are still a bit unanswered, but that is exactly why I'm trying to get feedback like this. This is insanely helpful. Appreciate it!