The point isn’t so much that R^2 is misleading - the main thing is that it doesn’t tell you what you really need to know - which is how confidently the focus is known - in terms of steps. You might use very large steps and get a very good v curve that matches a parabola well - but the expected error in the predicted focus is very large.
What I’m talking about isn’t earth shaking and it is standard procedure when fitting data to determine an underlying parameter. The fit not only gives you an answer, but it also gives uncertainties in the parameters. You can then use those uncertainties to calculate the uncertainty in what you are measuring.
If I say one focus value is 100 with R^2 of 0.9 and another is 120 with R^2 of 0.8 - what do I conclude? Compare that with one value giving 100 +/- 50 and another giving 120 +/- 5. The +/- comes directly out of the fit and carries much more info for comparing different curves and parameters.
You can do the calculation with your own data - I describe how to on the page I reference.