So, here's a couple links that describe what to do with outliers in mathematical analyses and why.
https://www.statology.org/remove-outliers/
https://humansofdata.atlan.com/2018/...liers-dataset/
Neither article is very long, if that's a concern.
In short, the removal of outlier datapoints/sets of data is a normal, traditional operation. I didn't make it up, nor did I make up the rules by which I remove such data.
Those rules/guidelines are well-established, and those links above describe some of the circumstances that such removals would be considered appropriate. Removing the highest/lowest values is just one method; it is acceptable to remove just one datapoint as well, so I was wrong about that part; I've always removed the lowest/highest values, as far as I can remember. And, this is basic, fundamental stuff, so if you took prob/stats, you had to learn these operations.
The funny thing about the whole argument, is that everyone does this in their everyday lives in their heads as a matter of course. Probably on an everyday basis. So it's kind of strange that no one seems to get it.
I have no remembrance of being able to arbitrarily add fictious numbers to an analysis, but I tried to google it. So far I haven't come across an article that says you can.
As for the WRs performance on Sunday, well, I already offered a quickie opinion earlier in this thread, so no need to repeat that.
Patrick did not have to run for the first time this season, and only took two sacks, so that's positive, and may indicate improvement by the WRs.
He did apparently take 9 QB hits, but I'm not sure where that falls compared to the other 4 games this season, so I can't offer an opinion about that part of it. It sounds a bit high, but he didn't look like he was getting smacked around out there, so I'll reserve my opinion on the subject in favor of someone who actually looked at those numbers this season.
We'll see how things are trending in a few weeks, but this game was at least a better performance than the previous one in more than one respect.