JustinTimeCuber
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I just had an idea about improvement. Being a mathy person, I turned it into an inequality. It states that the fastest you can get with a method is at least as fast as the best nonlucky solve that you have gotten. Of course, nonlucky is not strictly defined, but I would define it as a solve where you have to do every step, and each algorithm is at least medium long, not super easy (unless you intentionally influence it). My inequality is stated like this:
C(m) ≥ min(Nₘ)
Where: C(x) = the capability of method x (1/a where a is the best average you can get using x), m = the method that you use (more specific than just CFOP, Roux, ZZ, etc, I mean what algorithms you use and which LL cases you 2-look, 3-look, or 4-look, whether you know full CMLL, etc.), min(x) = the lowest value in the numerical set x, and Nₓ is all of your nonlucky solves using method x.
If this inequality is true, then it is definitely possible (maybe not easy) to try to get sub-13 or sub-12 with pure CFOP and no other algorithms. (I have gotten nonlucky sub-12 singles.) There are likely people who have gotten sub-12 with no extra alg sets, but I can't name any specifically..
C(m) ≥ min(Nₘ)
Where: C(x) = the capability of method x (1/a where a is the best average you can get using x), m = the method that you use (more specific than just CFOP, Roux, ZZ, etc, I mean what algorithms you use and which LL cases you 2-look, 3-look, or 4-look, whether you know full CMLL, etc.), min(x) = the lowest value in the numerical set x, and Nₓ is all of your nonlucky solves using method x.
If this inequality is true, then it is definitely possible (maybe not easy) to try to get sub-13 or sub-12 with pure CFOP and no other algorithms. (I have gotten nonlucky sub-12 singles.) There are likely people who have gotten sub-12 with no extra alg sets, but I can't name any specifically..