Nevada’s Election Shadows Part 3: Edward Solomon’s Shocking Discovery, Identical Vote Ratios in Every Nevada Precinct? The Data Doesn’t Lie

Building on that DOJ scrutiny from last installment, let’s shift to a guy who’s become a hero in conservative circles for calling out what looks like outright election rigging. Edward Solomon isn’t some wild-eyed theorist, he’s a mathematician who’s crunched numbers from multiple states, including Nevada, and what he found in our 2020 and 2024 data will make your blood boil. Solomon has never been disproven, and his $80,000 challenge to anyone who can prove him wrong remains undefeated.

Here’s the story: Solomon analyzed mail-in and early voting totals in Washoe and Clark counties, our two biggest vote hubs. In precinct after precinct, he spotted identical vote ratios for candidates, down to the decimal. For instance, in Washoe’s 2020 data, basically all precincts showed Biden getting exactly 58.3% of mail-ins while Trump got 39.7%, repeating like a broken record. Solomon detailed this in affidavits for cases like Joey Gilbert’s 2022 gubernatorial challenge, where he testified about an “illegal formula” skewing results. Court docs from that hearing confirm his formula: Leaving out election-day votes, the ratio of mail-ins plus early votes often hit the same percentages across unrelated precincts.

Why’s this suspicious? Random human voting shouldn’t produce cookie-cutter math like that. Solomon argues it points to algorithmic tampering, where software flips votes to hit predetermined ratios. In Clark County, with over 1,000 precincts, he found similar patterns in 2020, where ratios matched in ways probability says are impossible without intervention. Even so-called fact-checkers like FactCheck.org acknowledge Solomon’s Georgia analysis raised questions, and Nevada’s parallels are undeniable per public election datasets.

Let’s break it down simply for the average Joe. Imagine you’re at a casino in Reno, and every slot machine pays out the exact same jackpot pattern, 3 cherries, then a lemon, repeating across the floor. You’d yell foul, right? That’s Solomon’s point: Votes should vary like people do, but here they’re synced like machines. For example, in a small town precinct with 100 voters, you’d expect Biden to get 55 in one, 60 in another. But if it’s 58 every time? Something’s forcing it.

This isn’t abstract, it fueled lawsuits and GOP pushes for audits. If true, it explains why races feel “off” to so many of us. Remember the 2020 presidential race? Nevada’s six electoral votes went to Biden by just 33,596 votes, less than 3%. If even a fraction of Solomon’s claims hold, it could’ve swung things. The problem is clear: Hidden algorithms erode trust. Solutions? Many say ditch machines for paper ballots, hand-counted at precincts, with voter ID to ensure transparency.

But Solomon didn’t stop there, he’s exposed even more layers of potential fraud, like see-saw patterns where vote shares reflect across invisible lines. Stick around for Part 4, where we explore those other bombshells from Solomon’s research, like phantom voters, batch flips, and the STUV framework. It’s building toward how we fix this mess, and you need these details to see the full picture, including how federal probes could enforce paper-only voting.

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