First off, I haven't had the chance to analyze the data but this reply smacked me upside my head.
This, IMHO, is a significant overreaction to one guy's subjective impressions. You're talking about changing your mindset from believing a science that has reliably predicted preference (to more than a flip-of-a-coin degree) to no longer believing it because one person's subjective opinion didn't align a few times? I always listen first, take notes and then look at the data. In nearly every case I have found points in the data that explained why I heard what I heard. And in cases where I haven't I either don't know what to look for or I heard something that wasn't there. I feel strongly about that.
** Flame suit on... ** I hate to be
that guy but have you considered that Amir simply isn't the trained listener it's assumed he is? No disrespect, and lord knows I don't need a scolding and paragraphs on Amir's listening sessions with Harman listed as reference, but let's be real here: you are throwing out the baby with the bathwater by taking Amir's personal subjective reaction in a sighted test over some people's near-lifetime of work to quantify preference based on measurements. The only people I would trust explicitly when it comes to subjective feedback are the people who made the music; decided what it was going to sound like going out the door and hopefully had a very neutral set of speakers they mixed them on. I appreciate reading others' takes as more of a recreation but certainly none that I would put
significant stock in; especially if they can't help me correlate it to data. **... Flame suit off **
I am not saying it can all be bottled up in to a single set of charts *for every speaker* because there may very well be cases that kind of step outside the norm (the Philharmonic BMR is an example with its wide horizontal dispersion impacting the predicted in-room response). But I just think you're taking a leap that is too far without trying to look in to the reasons. There may be other data points that explain the differences. And maybe this data isn't as good as it may seem at first glance. Or there simply may be the human factor, which no one (myself included) is impervious of.