> curious how “an AI can do it” yields much difference in terms of result for the casual watcher

An AI can do it in volume, and therefore cheaper. I don't think a human could do everything I said in real time - maybe with a lot of training and custom software.

A human could transcribe the scoreboard, but the article still thinks that's an interesting application of cutting-edge machine vision.

Humans can do _most_ of what you said in real time, both providers using bespoke software and club analysts using off the shelf stuff like Sportscode. For full positional data on every player, every frame then yes, computer vision is doing most of the work but the quality isn't always great. Providers with in-stadium multi-camera systems provide great data, but you don't necessarily have access to the size of dataset you'd want for recruitment, and so lower-quality broadcast tracking exists (with all the problems you can imagine like missing players, occlusions, crazy camerawork etc). Most clubs also have wearables for their own analysis. Almost every fully automated broadcast tracking solution has hit a wall (sometimes on the first day of a season) in terms of quality that is often only solved by human QA, or by just discarding some games, so this is far from a completely solved problem. Fun domain to work in, but lots of horrible edge cases.