Charges of voter fraud in the last election began the day after the election. Many examples have been cited. Thousands of affidavits have been given. A number of cases were filed with the courts. Some of the claims have been debunked. Others remain to be proven or disproven. Most Americans don’t have the time to follow all of the evidence, and many don’t know exactly what to make of it. All they know is that Joe Biden was inaugurated as the President of the United States, so the election is settled for all intents and purposes.

I was one of those Americans that followed the claims of fraud quite closely early on, but time is precious, and eventually life has to go on. I don’t get paid to follow the news. I resolved that there seemed to be clear evidences of localized fraud, but the number of votes affected by those clear examples did not appear to be enough to change the outcome of the election. I have always been open to the possibility that the fraud was sufficient to have changed the outcome of the election, but was not willing to say the election was stolen unless and until it could be demonstrated by the evidence. I have no tolerance for conspiracy theories or speculation. Evidence must win the day.

When Mike Lindell came out with his documentary, Absolute Proof, I watched it with an open mind, thinking that he just might have evidence for widespread election fraud sufficient to change the outcome of the election. However, I was disappointed with his case. Many of the claims were not accompanied by sufficient evidence to support them. Some of the claims were debunked by critics. Evidence was presented for localized fraud. While some of these seemed convincing, even if they were true, it only proved localized, small-level fraud – not the kind you need to steal an election. His smoking gun that purported to provide evidence of widespread, systematic fraud turned out to be a Nerf gun. Long on claims, short on proof. Absolute Proof failed to deliver as promised. If that was the best they had, then perhaps the evidence for a stolen election just didn’t exist. I remained open to the idea, but tended to think that the election results were legit despite small, localized fraud here and there.

Recently, however, I was alerted to the fact that Mike Lindell is producing more documentaries. Supposedly, these will provide some of the evidence that was lacking in Absolute Proof. While his second major documentary is yet to be released, he did release an hour-long video containing an interview with Dr. Douglas Frank. He is a physicist who was asked to investigate a claim regarding election fraud in a local election. This led him to some significant findings that he and Mike Lindell discuss in the video titled Scientific Proof.

I have watched the video three times, trying to carefully digest the argument and evidence. While I am open to anyone who can debunk his claims, his data, or his analysis, if those turn out to be legit, then what he presents is, I believe, a smoking gun that there was widespread election fraud sufficient to have changed the outcome of the election. While I would highly suggest you watch the interview yourself, I will attempt to summarize Dr. Frank’s argument here to the best of my ability.

Dr. Frank’s Argument

Dr. Frank began his investigation by comparing population numbers to voter registrations by age for every county in Ohio, Pennsylvania, and Colorado. Typically, only ~80% of eligible voters are registered to vote; however, he found that in many cases, ~95% of the population was registered to vote. In some cases, there were more registrations than eligible residents. For example, registration numbers exceeded eligible residents in 26 Colorado counties. This was the first red flag.

A second red flag was raised when he layered in the data for ballots cast in the last election. The number of ballots cast by age corresponded very closely to the number of registrations by age. It’s as if someone had two pencil’s glued together and drew both lines at the same time. Every increase in registrations has a corresponding increase in ballots. When registrations increase, so do ballots. When registrations decrease, so do ballots. Consider Hamilton County, Ohio as an example:

As you can see, the gap between registrations and ballots can be larger or smaller depending on age, but both lines follow the exact same pattern. If this data reflected organic human activity, we would not expect the pattern between the two lines to be nearly identical. Such a parallel pattern between the number of registrations and the number of votes is not natural, and is a fairly clear signal of fraud.

The third red flag was even more revealing than the first two. The percentage of registered voters who voted in the election is the same for each age category in every county in the state. So, for example, if 95% of registered voters, age 65, show as having voted in one county in Ohio, you’ll find that ~95% of registered voters, age 65, show as having voted in every Ohio county. If 87% of registered voters, age 52, show as having voted in one county in Ohio, you’ll find that ~87% of registered voters, age 52, voted in every Ohio county. It would be next to impossible for the percentages in one county to be exactly duplicated in another county, yet alone in every county of the state! This is utterly impossible. This can only be explained by intelligent manipulation of the data; i.e. fraud.

Not only do we find the same percentage of registered voters of a certain age casting the same percentage of votes in every county of the state, but every county has the same percentage of voters compared to registered voters. In Ohio, for example, 86% of registered voters cast a ballot in every county. Again, that is next to impossible, statistically speaking, when there are 88 different counties in Ohio.

The fact that the percentage of voters-to-registered voters was essentially the same for each age bracket for every county in a state allowed Dr. Frank to predict the number of ballots that were “cast” in each county before ever looking at the ballot data for those counties. After examining 14 counties in Ohio, he averaged the voting percentages for each age, and then applied those percentages to the other 74 Ohio counties to predict how many ballots would be cast by age for each county. He found that his predictions matched the ballot data exactly or almost exactly in every single county. This level of predictive power is not possible unless the number of votes was manipulated for each county to match a specific pattern. This is a smoking gun for fraud. It proves that the voting machines didn’t just manipulate votes in some polling places, but across entire states.

This pattern isn’t confined to Ohio. Dr. Frank checked the data for Pennsylvania and Colorado as well and found the same thing. The fraud was statewide. While other states have yet to be assessed, if the first three states Dr. Frank chose to examine all showed evidence of systematic voting fraud, chances are, many other states will as well.

So what exactly was the fraud, then? The voting machines were operating according to an algorithm that converts a pre-determined percentage of registrations into fake ballots. So, for example, the algorithm might be set so that 92% of registered voters 45 years of age will cast a ballot. If only 72% of voters age 45 actually cast a ballot, the system will create 20% more ballots/votes. These are phantom ballots/votes from phantom voters. This algorithm has a recognizable shape to it. Mathematicians call it a 6th order polynomial. You only need 6 numbers to make it work. The algorithm is the same for every county in a state, but differs from state to state.

To test his theory about phantom voters/votes, Dr. Frank utilized the county registration databases that are available to the public in every state. These databases tell you the voting history of each person and their address. A lot of people showed as having only voted one time, specifically in this last election. He predicted that 30% of the “voters” were phantom voters; i.e. people who did not vote, but the voting machine created a ballot/vote for them anyway. He chose a small county in PA to knock on doors and see if the person whom the system says voted actually lives there, and actually cast a vote. His team knocked on 1600 doors and found that 32% of those households did not contain the supposed voter or the supposed voter did not vote (very close to his prediction of 30%). That means 1/3 of the votes in that particular county were fraudulent. Given the fact that this fraud is being driven by an algorithm that is consistent across the state, it’s likely that this percentage of fraud would be found in other counties as well.

You might be wondering where these phantom voters come from. Often, they are people who have died or moved out of the county. If those registration rolls are not cleaned out, hackers have more phantom voters to work with. Or, they are people who are registered to vote but do not cast a ballot in the election.

There is one final red flag that should be mentioned. As you examine the registration and ballots cast data, you’ll notice a series of stair-step bumps on the chart for those age 70+. This phenomenon is present in every county. Look at the chart from Hamilton County, Ohio again:

Here is Stark County, Ohio, where we observe the same pattern:

Here is Ashland County, OH:

What can explain this? Dr. Frank had been teaching on differential calculus just prior to the election, and used the 2010 census data as an illustration. He recognized these bumps from the 2010 census data he had been teaching from. Here is an example of the census data from a county in Pennsylvania, highlighting the bumps.

When he shifted the 2010 census data 10 years and accounted for mortality, he found that this matched up almost perfectly with the registration data he was seeing from the machines, including the bumps:

Those who inserted the algorithms to commit voter fraud had to make assumptions about the population so that they didn’t create more registrations than there were people, so they used the 2010 census data to make their population assumptions, shifting that census data 10 years and reducing the populations slightly to account for mortality. That’s why the population and registration info is so closely correlated, and why the number of registrations for those age 70+ display the same bumps in every county. Unfortunately, this is not a perfect system because it can’t account precisely for migration and death. That’s why the number of registrations (and sometimes even votes) exceeded the current population in these counties. Broomsfield County, CO is illustrative of this tendency:

While Mike Lindell claims to have other soon-to-be-released data showing the precise actors who committed the fraud, when they committed the fraud, and where they committed it, I think this data alone is enough to demonstrate widespread voter fraud involving voting machines.

A Stolen Election?

Was this enough to change the outcome of the election? That answer depends on which states were affected, how many fake votes were created in each state, and who those fake votes were for.

Regarding the first question, as I already noted, which states were affected is yet to be determined. We know that at least three states were, and one of those states was a swing state that went to Biden (PA). Given the fact that the first three states Dr. Frank chose to examine all evidenced systematic fraud, we should expect that many other states will yield the same evidence.

Regarding the second question, this can only be answered by the first question. However, for the states we know there was fraud in, as many as 1/3 of the ballots could be fraudulent. While Dr. Frank did not say how he arrived at his estimation, he said that absent the fraud in Ohio, Trump would have won by 16-17% rather than 8%. This amount of fraud would have easily allowed Trump to win Arizona, Georgia, and Michigan, and thus the election.

Regarding the third and final question, who the fake ballots were cast for was not identified in the presentation, however, given Dr. Frank’s assessment of Ohio, given the oddity of states like Arizona and Georgia voting Democrat, and given the fact that Joe Biden won so handily without even campaigning or generating much excitement for his candidacy, I’m betting that most (if not all) of the fraudulent votes were for Joe Biden. If so, then he did not win the election, and is not the legitimate President of the United States of America. Whether or not this evidence will be presented in a court of law, and whether or not it will hold up to scrutiny is yet to be seen.

Let me conclude by once again noting that someone may be able to demonstrate a flaw in Dr. Frank’s data or analysis. So far, however, I am unaware of anyone who even attempts to do so. If his analysis holds up, it is deserving of our consideration.