Empirical evidence and historical data leads to an inescapable conclusion about the 2020 election. Here are nine categories of suspicious anomalies in Biden’s victory.

Eleven months after the 2020 American presidential election, the official results remain so incongruous, they merit an empirical exegesis.

The political establishment’s narrative is that Biden won an unexpectedly close race, and the outcome requires no further examination. Yet, Biden’s victory is so statistically suspicious, so riddled with ahistorical outcomes, that a detailed data examination is necessary to reassure Americans the official result was, in fact, the actual result.

Official tallies record 161.3 million votes cast in 2020. Donald Trump got 75 million of those votes, 12.1 million above his 2016 total, and the most votes ever received by an incumbent president. Joe Biden received 81.2 million votes, the most votes for anyone who has sought the presidency.

Biden received 306 Electoral College (EC) votes to Trump’s 232. The individual vote totals behind that victory show an amazingly slim margin of victory for Biden. He won Arizona (11 EC votes), Georgia (16 EC votes), and Wisconsin (10 EC votes) by a combined 43,809 votes, which made the difference between victory and an Electoral College tie.

Now, let’s consider nine categories of suspicious anomalies that led to Biden’s squeaker of a victory.

I. Census Bureau Data

In 2020, the Census Bureau found 5 million fewer voters than the number of ballots counted. This is the largest gap recorded since these post-election surveys began in 1964. These 5 million excess ballots account for most of Biden’s national popular vote lead. To cite one state-level example, the Census Bureau found 4.8 million voters in Georgia, but Georgia reported 5 million counted ballots.

The Census Bureau’s validated voter survey is a very thorough and comprehensive piece of post-election data analysis. Historically, it has been far more accurate than exit polling and other post-election surveys and studies, as Robert Barnes, a leading political analyst, and successful political prognosticator, explained in early May on his “What Are the Odds?” podcast.

The nationwide excess of counted ballots over registered voters in 2020 is extremely unusual. Census data usually finds a very small differential between the number of people they identify as having voted in the previous presidential election and the official total number of ballots counted in that election. In 2016, Census voting data matched almost precisely the number of ballots counted.

Historically, when Census data has differed from the official ballot count, it has tended to overestimate, rather than underestimate, the number of voters. The opposite was the case in the 2020 election.

Most revealingly, the Census data shows the turnout surge was almost exclusively among White blue-collar voters, an overwhelmingly pro-Trump cohort. Yet, somehow, the surge favored Biden in the end.

Turnout in 2020 was 6.7 percentage points higher than in 2016. The Census data on overall turnout, and turnout among specific demographic groups, closely aligns with the macro- and micro-turnout predictions made respectively by Barnes and Richard Baris, the preeminent pollster and managing director of Big Data Poll, and polling data at my firm, Democracy Institute, which forecast a Trump win.

II. Predictive Metrics

During any presidential campaign, a number of leading indicators foretell the election outcome. The mainstream media focuses almost exclusively upon approved media and academic polling, which historically has a mixed record. Unlike the independent polling conducted in 2016 and 2020 by Baris, Robert Cahaly, Rasmussen, Susquehanna, and the Democracy Institute, respectively, the mainstream pollsters sponsored by the major television networks and news organizations performed terribly in 2016 by predicting a Clinton win, and even worse in 2020, predicting a Biden landslide.

 

“The 2020 polls featured polling error of an unusual magnitude,” a report by the American Association for Public Opinion Research concluded. “It was the highest in 40 years for the national popular vote and the highest in at least 20 years for state-level estimates of the vote in presidential, senatorial, and gubernatorial contests.” The average error in the polls just two weeks before the 2020 election was 4.5 percentage points nationally and 5.1 percentage points in state-level polls.

In a normal election, when the big polls err, non-polling metrics do not. These include party registration trends; the number of votes the candidates received during their party’s primary election; voter enthusiasm levels; the number of (especially small) donors; social media followings; broadcast and digital media ratings; online searches; the number of candidate lawn signs; campaign merchandise sales; and the number of individuals betting on each candidate.

Every non-polling metric forecast Trump’s reelection, and these non-polling metrics have historically had a 100 percent record in indicating who will be president—until 2020. Consider: for Trump to have legitimately lost the election, the mainstream polls needed to be correct, which they were not. Furthermore, for Trump to lose, not only did one or more of these non-polling metrics have to be wrong for the first time ever, but every one of them had to be wrong, and all at the very same time.

This is not, strictly speaking, impossible, but it is extremely unlikely.

III. Voter Registration

Historically, the registration-by-party trend is a very reliable predictor of the election outcome. New and crossover registrations are the best proxy for both voting intention and actual voting behavior. In 2020, Republicans achieved massive registration gains vis-à-vis the Democrats across almost all competitive states. Notably, in 2020 voter registrations in the swing states of Michigan, Pennsylvania, and Wisconsin—won by Trump four years earlier—each trended toward more Republicans registering, foreshadowing an even more favorable electoral environment for Trump than in 2016.

The higher Republican registrations were the continuation of what happened in 2016. In Pennsylvania, for example, 2016 registrations had trended toward the Republicans in 60 of 67 counties. Unsurprisingly, when those newly registered voters cast their ballots, 62 of those 67 counties trended toward Trump, explaining his statewide victory over Hillary Clinton.

But strangely, the same trend didn’t produce the same result in 2020. Statewide registration trended 3 percent to the Republicans between the two presidential elections, with Republicans registering 242,000 net new voters, compared to just 12,000 for the Democrats. This gave the Republicans a massive 21-to-1 registration advantage over the Democrats in Pennsylvania between 2016 and 2020.

Hence, last year saw 60 of 67 Pennsylvania counties trend toward the Republicans in registrations, foretelling a larger Trump win statewide than in 2016, as historically Pennsylvania along with the swing states of Florida and North Carolina has always trended towards the party that made overall registration gains.

However, when the ballots were cast, only 20 of those 67 counties trended toward Trump—which is the opposite of what one would expect. The official results reported Biden winning Pennsylvania with 50.01 percent of the recorded votes…..

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Continue reading this article at Chronicles Magazine.