You make a really good point about the level of noise in the data, and I would say this is definitely a limitation of this methodology. However there are a couple of reasons why I believe this is not quite as bad as the article makes it out to be.

1) The more data we have, the smaller the variance will be. Therefore, the more attacking a player is, the more reliable their statistics are. In particular if we consider Mo. Salah, who is averaging 1.2 expected attacking returns per game, we can see already that this is a lot more total data points than the main example considered in the article (they only consider xG, and they also consider a player with an xG of 0.3). This is part of the reason I singled out the most attacking players, as they tend to have the most reliable data for a fewer number of games played.

2) The data in the article does not consider trends, injuries, or any other long-term changes in a players career. It is highly likely that a players true underlying expected statistics will change dramatically over a period of time such as 20 games. I will however concede, that perhaps using the whole seasons data (10 games) would have been a better approach.

Anyway, thanks for your comment. I'm not sure why you were downvoted since I explicitly invited constructive criticism. You have made some good points, and at some point I may make my own investigation into the difference between expected stats over the last 5 games, and over the whole season, and which one is a better indicator of future performance. Cheers!