CulturalHusbandry

This is based on their proprietary "Edison" data source which would ordinarily be impossible to access for people outside the press.

I suggest that everyone back up both of these files, bc this is an extremely important data source, and we cant risk anyone taking it down.

What we are looking at will be time series analysis and you will see that it is extremely difficult to create convincing synthetic times series data. By looking at the times series logs of the ballot counting process for the entire country, we can very easily spot fraud.

As we can see on this log-log plot, for many of the counting progress updates, we see an almost constant ratio of #Biden to #Trump. It's such a regular pattern that we can actually fit a linear regression model to it with near-perfect accuracy, barring some outliers.

How could this be possible? Is this a telltale sign of fraud? Surprisingly, as it will be shown, the answer is no! This is actually expected behavior. Also, we can use this weird pattern in the ballot counting to spot fraud!

like a deck of cards. Since the ballots are randomly mixed together during transport, spanning areas occupied by multiple voting demographics, we can expect the ratio of mail-in #Biden ballots to mail-in #Trump ballots will remain relatively constant over time...

and across different reporting updates. Lets dig a little deeper into this:

The initial reporting represents in-person voting. These vote reports have such large variation bc in-person voting happens across different geographic areas that have different political alignments.

We can see this same pattern of noisy in-person voting, followed by homogeneous mail-in reporting in almost all cases.

This slight drift from D to R mail-ins occurs again and again, and is likely due to outlying rural areas having more R votes. These outlying areas take longer to ship their ballots to the polling centers.

Now we're getting into the really good stuff. When we see mail-in ballot counting where there isn't relatively stable ratios of D and R ballots that slightly drift R, we have an anomaly! Anomalies themselves are not necessarily fraud, but they can help us spot fraud more easily.

Now let's look at some anomalies:

Around 4am there, there is a marked shift in the ratio of D to R mail-in ballots. Based on other posts in this thread, this should not happen. This is an anomaly, and while anomalies are not always fraud, often they may point to fraud.

so what happened just before 3am CST in Wisconsin? This did!https://twitter.com/mattsmith_news/status/1323914505638809601 …

Around 3am Wisconsin time, a fresh batch of 169k new absentee ballots arrived. They were supposed to stop accepting new ballots, but eh, whatever I guess.

By 4am the D to R ratio was all thrown out of whack. That is because these ballots were not sampled from the real Wisconsin voter population, and they were not randomized in the mail sorting system with the other ballots. They inherently have a different D to R signature...

than the rest of the ballots quite possibly bc additional ballots were added to the batch, either through backdating or ballot manufacturing or software tampering. This of this being kind of analogous to carbon-14 dating, but for ballot batch authenticity.

Here is Pennsylvania's vote counting history. For the first part of the vote counting process, we see the same pattern for mail-in ballots that we've seen in every other state in the country, which is relatively stable D to R ratio that gradually drifts R as more ballots...

come in from rural outlying areas. But then as counting continues, the D to R ratio in mail-in ballots inexplicably begin "increasing". Again, this should not happen, and it is observed almost nowhere else in the country, because all of the ballots are randomly shuffled...

in the mail system and should be homogeneous during counting. The only exceptions to this are other suspect states that also have anomalies. Again, this is evidence of ballot backdating, manufacturing of software tampering.