Possible relationship between zero and changes of state in the sequence

yep

I’m not saying 30,000 spins prove anything just because there are a lot of them. My point is that I identified certain relationships early on, and as the sample kept growing, those same relationships continued to appear. That’s what I’m trying to measure properly now.

For me, the important question is not whether the sample got bigger, but whether the same structures keep returning as more data is added. If they do, then the reasonable next step is to quantify them and test how far they actually hold.

Calculo que el material acumulado ronda los 30.000 giros. Lo que realmente me llamó la atención fue la regularidad con la que ciertos comportamientos y relaciones volvieron a presentarse bajo condiciones similares. Tengo bastante material y varias relaciones que considero especialmente llamativas; precisamente por eso he seguido investigándolo durante tanto tiempo. Ahora estoy organizando todo para poder analizarlo de una forma más clara, estructurada y cuantificable. No lo planteo como una regla cerrada ni como una predicción automática, pero sí creo que hay elementos suficientemente consistentes como para que merezcan un análisis serio y más profundo.

Sorry, my previous comment was accidentally posted in Spanish. Here it is again in English:

I estimate that the accumulated material is around 30,000 spins. What really caught my attention was the regularity with which certain behaviors and relationships kept appearing under similar conditions. I have a considerable amount of material and several relationships that I find particularly striking, which is precisely why I have continued investigating this for so long. I am now organizing everything so I can analyze it in a clearer, more structured, and quantifiable way. I am not presenting it as a fixed rule or as an automatic prediction, but I do believe there are elements consistent enough to deserve serious and deeper analysis.

I understand your point. I’m not saying that zero causes what happens next or that it changes the probability of the next spin. What I’m looking at is something different: whether zero tends to appear at certain points within a sequence, and whether certain structures repeatedly show up around it.

Since zero falls outside red/black, odd/even, and high/low, I’m treating it as a different kind of reference point. I already have several records where certain formations repeat before or after zero appears, so I’m interested in seeing whether anyone else has noticed something similar.

I’m not claiming it is a rule. I’m comparing the data to see whether that relationship actually holds up.

Fair question. I should clarify one thing first: I’m not claiming that zero is a transition marker, nor that zero causes a change in the sequence. That would be a much stronger claim than what I’m actually investigating.

By “state,” I mean the combination of several observable conditions within a given stretch of the sequence, rather than any single pattern by itself. For example, the relative balance or imbalance of certain categories, the presence and length of particular runs or repetitions, and how several of those conditions occur together at that point.

What I’m interested in is comparing the configuration that exists before a zero with the one that develops afterward, and then asking whether similar changes occur just as often around ordinary non-zero reference points.

If the same type of change appears with similar frequency around other reference points, then zero has no special significance in that respect. If a consistent difference remains after applying the same criteria to both, then that difference would be worth studying more closely.

So at this stage, zero is a reference point in the analysis, not a presumed cause or confirmed transition marker.

The sample isn’t based on one notebook or a handful of isolated sessions. I’ve been collecting material from different tables, sessions, screenshots, videos and result histories over time, then comparing the same variables across those records. There are several recurring relationships that stood out enough for me to keep documenting them. I’m now organizing the full dataset so I can measure how often those conditions actually repeat and how stable they are across different samples.

understand what you mean, but I should clarify that I’m not starting from zero on this. I already have a fair amount of observations and recorded cases behind the idea.

I’m not trying to use zero to predict when it will land. What I’ve been doing is comparing the structure around it: how several conditions behave before and after, and whether certain relationships appear repeatedly under similar circumstances.

At this point, what I’m mainly looking for is independent material that can help me compare, challenge, or refine what I already have.

So if anyone has tracked something similar, or has data, methods, examples, or even a different interpretation that could be compared with mine, I’d be very interested to see it.