Mathematical EV
Where is the Edge?
Most things look noisy from the outside.
Poker hands. Shuffling machines. Chess positions. Statistical models. Human decisions made under pressure.
Noise is not the same as randomness. Underneath the mess there is usually a structure. Sometimes it is mathematical. Sometimes it is mechanical. Sometimes it sits inside an assumption everyone stopped questioning years ago.
Poker gave me the habit of looking for structure beneath noisy outcomes, and data science gave me better tools for testing whether it was really there.
MathematicalEV is where I put the questions I cannot leave alone.
A shuffling machine everyone treats as random, so I built one.
A chess idea about tension that exposed a leak in my poker game.
A model that works beautifully until the wrong question reveals what it never understood.
A poker tournament where the real objective was hidden behind the prize pool.
Right now, most of my attention is on the One2Six continuous shuffler. I wanted to know what process was producing the cards, what information survived that process and whether any of it could become an edge visible from the table.
I am drawn to mechanisms, uncomfortable questions and the point where a clean explanation stops being true.
The point is to strip away the noise and find what is producing it.
mollitia exitium est