Think that no way a card distrbution working into an asymmetrical model can get symmetrical results for long and at various degrees. So in some sense and in order to build a long term plan we are compelled to wager towards asymmetricity. Unrandomness enforces such asymmetricity.
Statistically speaking, it's just the number of runs (whatever intended) that confirm or not the randomness of our sample.
Since you can take for granted that live shoes aren't random produced, we are forced to evaluate the number and the probability to get asym results per every shoe dealt.
We know that card distributions can produce infinite results, yet the probability to get something is endorsed by restricting outcomes that tend to go beyond given points and we know that the best way to limit the results is by classifying them into 1, 2 and 3 situations.
Transforming into math such probabilites, we know that 1=50%, 2=25% and 3=25%.
Of course when wagering B side 1 probability is lower than 2 and, at at a lesser degree, 3>2 and the oppposite is true about P side.
Nonetheless and from a strict bet selection point of view, such asym values won't get much of a difference.
Best example is by considering my up #2, spots where we'll win first by hoping for a B single as it's lowering the general B>P propensity as itlr previous BB trigger must involve a kind of already worn-out asymmetrical force (providing BB-B gaps are close). Whether such asym math force hadn't acted yet, probability to get another B hand after a BB pattern is generally endorsed.
For the same reasons any 3 event will be followed or not by another 3 event and the general probability will be always 0.25%. Yet the actual probability is quite lowered or raised in some shoes and dependent on which random walks we choose to follow.