The point of all the data is to give coaches more objective information. To use your example: The data says run the ball. The stud defensive tackle has just s

The point of all the data is to give coaches more objective information. To use your example: The data says run the ball. The stud defensive tackle has just started playing really well. Here's the beauty of the way this data can be presented: While there is a way to present it as "expected points," you can also present it as "likelihood of a given result." In this case, the positive outcomes for the offense are a first down (or score, which would also be a first down). If the data says you will pick up a first down 51% of the time and you know the Broncos tackle has recently begun playing well, you adjust down for it, and likely decide not to run (and no analytics guy will fault you for it). If the data says you'll pick up a first down 85% of the time, you need a better reason to justify not going for it (is this new tackle the greatest of all time? Or just an upgrade on what they had?). Data is not best used as a replacement for a coach. It is best used to give a coach the likelihood of a given event occurring, and then let the coaches knowledge of matchups, injuries, and personnel issues adjust that likelihood up or down.