Its not specifically related to Freeman. Autocorrelation tends to happen when you are looking at data over a period of time. How and to what degree autocorrelation biases results is hard to know. It could be large or small, and it could affect YAC more than Air yards or vice versa.

In thinking about this, there are some other issues too, namely uneven variances within the composition. So for instance, you took a composite of 100 qbs and looked at their year to year changes in Air Yards. A simple linear regression will assume that the relationship between the two years is more or less the same across all data points. For instance, if we were to look at how much income is correlated with experience, we would expect that this relationship is the same across all individuals. However, that assumption probably doesn’t hold, since males typically make more than women, whites make more than blacks, etc etc. Similarly, some qbs in some systems may have more consistent Air yards than others for a variety of reasons, but OLS will treat this composition the same.

I’ll just want to add, I like this article a lot and the things I note aren’t meant to invalidate the results at all. I think I was just being a bit nit picky.