The problem is that metric, like any metric, is both easy to game _and_ can provide misleading information.
Measuring number of commits? Create fewer, larger commits. Measuring commit size? Pull in more third-party libraries, even where it does't make sense. Author count? Add more/less documentation and recruit or inhibit new devs depending on what your goal is.
Not to mention the number of commits/authors before and after an arbitrary point in time might conflate a successful growing project with a project in a death spiral being passed around from group to group.
It's a good idea, but in practice simple metrics like this often (but not always) devolve into prime examples of Goodhart's law.
In science, measuring things until you find a benefit is called p-hacking. Every extra test you do that splits your data along a different dimension, is another independent opportunity for "random chance" to look like positive signal.
There is no programming project in existence with enough developers working on it, that developer-productivity data derived from a change to it would not be considered "underpowered" for the sake of proving anything.
The obsession with measuring is hilarious. There are plenty of things in life (and jobs) that aren't measurable and are worth doing. Probably all of the important things are actually unmeasurable. Think about it this way, if its so easy you can measure it, it probably isn't very important in the grand scheme of things.
No metric can escape gaming when you apply it to rational actors (Campbell's Law / Goodhart's Law). Blind devotion to metrics is just as bad as no metrics at all.
I was just yesterday discussing the opportunity cost of infrastructure changes, as a new team member was bemoaning our out of date patterns...
A high impact infra change will often inconvenience dozens of people and distract from feature work... You know, the shit people actually care about... (this is analogous to how "Twitter, but written in Golang" appeals to approximately no one.)
Goodhart's law is entirely applicable to management (adding scientific in front doesn't actually mean anything). That is one of the prime areas of applicability. People change their behavior to increase a metric at the cost of decreasing other more important things.
Measure commits/authors before and after a refactor.