The glaring incongruity for me arose from the details on Tesla.
"For example, on the driver-side small overlap test, Tesla had one model with a relevant score and it scored Acceptable (below Good, but above Poor and Marginal) "
Note the words "above poor." But in the bullet points danluu uses a different scale that doesn't match this prose, and slots Tesla into "poor."
I'm sensing an agenda. But I'd rather keep an open mind, and look at the raw data myself.
The other odd thing is that the article mentions both 2012 and 2018 data, but doesn't provide a specific link to the data that was used. What raw data was used?
A clue lies in the other prose about Tesla in the article, which refers to a 2017 article about Tesla's pushing back. (The points about this being predictable as a PR move seem valid. However what's more interesting is the timeline.) 2017 is prior to 2018. Which points to the data being relied on here being the 2012 data, not the 2018 data.
The problem with using very old data is that the cars have evolved significantly since 2012. I mean, 2012 was the very first production year for Model 2. We're talking almost a hand crafted (though semi robotic) assembly line back at that point. And yet the article talks about this as though the data represents Tesla in general. We are eight years along into the future now — almost a decade — with that many years of improvements and two (correction, three) new models, if you don't even count the vast updates to the Model S. This should be disclosed in a way that is glaringly clear, not glossed over or minimized.
In short, I would take everything here with a grain of salt. The research question, though, seems like a very good one. I would look forward to hearing an update where the data is provided, the sources are examined, the funding for the lab tests is disclosed, and current car models are covered.