Well, we know that the the “Cell” armor that the forward fuel tanks should have aren’t thick enough, so it should be increased to ~63mm overall.
So with the current mechanics it’s actually underperforming in terms of “Overmatch” and even then won’t be unless they are modeled with a single variable thickness volumetric plate, due to the way stacking plates currently (doesn’t) properly interact with the overmatch mechanic.
Depends on how exactly things are modeled and how specific tip & impact angle combinations are implemented, and if bending is taken into account (e.g. simplified modeling could be based off Euler's critical load - Wikipedia as a more refined limit impact energy limit).
You say statistics, and the proceed to quote characteristics. Then don’t actually properly compare them either, the colors are also not all too useful, since well it doesn’t put any sort off attention to relative capabilities;
For example;
The combination of the poor turret and KE ammo the M1 provides the worst possible “Effective range delta” for the M1 vs all referenced counterparts (and alternately the potential impact of the addition of M833 or M900(A1) would have on the match ups), which defeats the fact that the UFP causes “Auto-bounce” since you aren’t going to be shooting at it in preference to the LFP / Turret (ring) if you have the choice, most of the time.
As an example.
M1 (M774 / M833 / M900A1) vs T-80B (3BM42), as per your table; N/B - 10% performance reduction to penetration of the shells to account for greatest possible RNG reduction.
(0m / 0m / 2000m++) / 2000m+ ( 800m ( vs right side of turret)) Which is very obviously Negative or, slightly positive w/ M900A1.
So isn’t in the M1’s favor.
Do you have actual Statistical modeling that shows the M1 out performing it’s counterparts, and which dataset is it based off?
It’s more than a feeling at this point.
I’m working on producing a CDF for various tanks to actually pull (understandable, and relatively useful) non heuristic data from samples, that can at least to some degree take a look at actual relative performance (of the surveyed players), I’ll see if I can get it hooked up to Statshark / Thunder skill / WT Dataproject datasets at some point.