Thread by @shylockh

Evidence Suggesting Voter Fraud in Milwaukee – a thread.

I’ve been looking at the vote counts in Milwaukee, and there’s suspicious patterns in the data that need explaining. Proving fraud is difficult, but a lot of irregularities point in that direction. First, the tl;dr.
(1/N)

1. Democrat votes started increasing massively relative to Republicans after Tuesday night counts. This can’t be accounted for by explanations like heavily Democratic wards reporting later. When we look at the changes *within wards*, 96.6% of them favored the Democrats.
(2/N)

2. Democrats also improved massively against third party candidates, but Republicans and third party candidates are similar to each other. Since there’s little incentive to manipulate third party counts, the big change is in Democrat votes, not in Republican ones.
(3/N)

3. In down ballot races, Democrat increases within each ward were larger where the Democrat candidate was initially behind in the overall race on Tuesday night – i.e. relatively more Democrat votes appeared in races where they were more likely to alter the outcome.
(4/N)

4.This result is easy to explain by fraud, but is more complicated under other explanations like Democrats mostly voting by mail. Most theories predict all Democrat candidates should benefit equally within a ward, not that more votes come in exactly where they’re needed.
(5/N)

Ward-level vote counts are from the Milwaukee County Clerk at 7pm Thursday night (county.milwaukee.gov/EN/County-Cler…) and the archived version from the count as it stood on election night (web.archive.org/web/2020110404… ).
(6/N)

This idea came from @toad_spotted. I’m considering Presidential, Congress, State Senate and Assembly races. One way to look at the effect is to compare the percentage increase in votes for Republican Candidates vs Democrat candidates within each ward after election night.
(7/N)

E.g. Suppose the Democrat candidate votes went up 200% from initial count to Thursday night. How much did Republican votes go up? If the distribution of votes before and after is the same, the percentage gains for each group should be similar, regardless of who was ahead.
(8/N)

This is different from candidate totals in the state changing as different reports come in from other parts of the city. Rather, we’re testing whether the *same ward* should continue to find the same distribution of votes before and after Tuesday night.
(9/N)

If the distribution is the same before and after, roughly half the time the Republicans would get unlucky in early votes and later improve their position (regardless of if they ultimately win or lose). Around half the time, Democrats should increase their votes by more.
(10/N)

Instead, the Democrat candidate vote increases relative to the Republican candidate a crazy fraction of the time. The variable is % increase in Democrat votes for that ward (i.e. % change from Tuesday night to Thursday night), minus % increase in Republican vote.
(11/N)

So a value above zero means that Democrat totals went up more than Republicans in that ward/race. A value of 500 means that the Democrats went up 500% in excess of the republicans (e.g. D votes grew 600%, R votes grew 100%).
(12/N)

Here’s a graph of the histogram. You see an enormously right skewed distribution –tons of large gains for Democrats, very few gains for Republicans. Not only do Democrats very often increase more than Republicans, but when they do, it’s often by a colossal amount.

(13/N)

Out of the 1217 ward/race combinations with non-missing early votes for both parties, 1037 saw relative increases for the Democrats, 37 saw relative increases for Republicans, and 143 were ties. Excluding the ties, the D “win” fraction here is 96.6%. A remarkable feat!
(14/N)

Depending on how you assign ties, if this were a 50/50 coin (i.e. D and R were equally likely to gain relative to the other), the probability or p-value for this is between 10^-147 and a number Excel just lists as “0”.
(15/N)

So, this proves incontrovertibly that *something* about the count skews crazily towards the Democrats after 2am Wednesday. But it doesn’t prove what it is. Maybe they counted different types of ballots or something, but only starting at 4am.
(16/N)

However, there’s one thing we *can* test – from which party’s votes is the weirdness coming from? We can answer things by looking at vote changes for other candidates – third party races, write-in candidates etc.
(17/N)

We can be virtually certain that nobody is bothering to manipulate the vote totals for fringe, no-hope write-in candidates. These form a great placebo group – what might you expect the changes to look like for a group where nobody is manipulating the totals?
(18/N)

Let’s do the same graph, but compare each party with “Miscellaneous”. Because the Misc count is small, I aggregate it together, restricting to cases with at least 5 Misc votes in that ward by 2am Wednesday (otherwise if there’s only 1 vote, the minimum increase is 100%).
(19/N)

What are we predicting to find? Well, if it’s the Democrat total that’s being inflated, Democrats should also be increasing relative to Miscellaneous. If Republicans are just being counted as normal, then their changes should look similar to the Miscellaneous Group.
(20/N)

That’s basically what we find. In Democrats vs Miscellaneous, the picture is even more crazily skewed than before. Democrats improve relative to Misc. in 520 ward/race observations. They tie 89 times, and Misc. improves in relative terms just 3 times. That’s not a typo.
(21/N)

This corresponds to p-values between 10^-73 and 10^-177. The fraction of Democratic “wins” here (520/523), excluding ties, is a ludicrous 99.4%.
(22/N)

So how do Republicans compare with Miscellaneous? While they’re not exactly the same, they’re far closer to each other than either is to the Democrats. Other than a few outliers (as Misc. has very few votes in total), the distribution is fairly symmetric around zero.

(23/N)

Republicans improve relative to Miscellaneous 179 times, Misc. improves 251 times, and there are 74 ties. The p-value you get depends greatly on how you allocate the ties. Give them to M, and it’s 10^-11. Give them to R, and it’s 0.55, almost exactly chance (253 vs 251).
(24/N)

Excluding ties, the R “win” percentage is 41.6%. So under some measures, they look slightly worse, but this is affected by questions of rounding and the small vote totals for M. What’s incontrovertible is that D looks wildly, wildly different from either of them.
(25/N)

This is exactly what we’d predict if votes before look like votes after, which for R vs M, they do. This is also inconsistent with the driver being something Trump did, like telling all his supporters to vote in-person.
(26/N)

If so, why do changes in Miscellaneous votes look about the same? The important difference after Tuesday night, whatever you think it is, is coming on the Democrat side.
(27/N)

Could there be other reasons than fraud why ballots might be different before and after? If the ordering is random and drawn from the same pool, no. But if wards count different types in a different order (votes cast at 9am vs 4pm, in-person vs mail-in), then possibly.
(28/N)

Whatever is changing vote distributions before and after, it’s overwhelmingly impacting Democrats, not Republicans. If you think it’s about in-person vs postal voting, Republicans must be similar to Miscellaneous in this respect. This is possible, but not at all obvious.
(29/N)

There’s another more important aspect. If Democrat increases are partly fraud, we would expect that increases should be larger *when the fraud is more likely to impact the race*. We have lots of down-ballot races like State Assembly Representatives we can test here.
(30/N)

Sometimes the Democrat is way up after early counting, so improving the margin doesn’t matter. But if the Democrat is down early on, adding votes is much more important. I’m assuming fraudsters would like to win as many races as possible with the least amount of fraud
(31/N)

The comparison is now between two different races at the same ward. A Democrat voter comes to the ballot box or mailbox, and sees a number of races. For some, like President, it’s going to be a close call. For others, it might be a heavy favorite for the Democrat.
(32/N)

The voter is a Democrat, so presumably he’s inclined to vote Democrat for both. We can compare within a given ward which of the two races showed bigger improvement for the Democrats in that particular ward after Tuesday night.
(33/N)

Indeed, the increase in Democrats relative to Republicans is significantly higher when the Democrat is doing worse overall in early counting. Within each ward, late votes break more heavily to Democrat in exactly those races where they are likely to affect the result.

(34/N)

How big is the effect? There were 8 races where Republicans were ahead on Wednesday morning. By Thursday night, half had flipped to Democrats. By contrast, there were 19 races where the Democrat was ahead, and not a single one flipped Republican.
(35/N)

It’s not that the races flipped because heavy Democrat wards started reporting in. More votes started coming in for Democrats relative to the ratio for that exact ward the previous night. The votes also skewed more for races that Democrats looked like they might lose.
(36/N)

This is surprisingly hard to explain with common explanations for why Democrats pulled ahead overall. E.g. mail-in ballots are counted late, and these are more heavily Democrat. In general, this doesn’t explain why some races later skew Democrat more than others.
(37/N)

The key is that for each voter, voting by mail is common to all races. A single voter can’t vote for some races by mail, and others in person. So if the overall D skew is a mail ballot effect, most versions of this predict that all races should be equally affected.
(38/N)

Consider a simple example where everyone votes straight ticket. More Democrats vote by mail, and these are counted late. This would predict overall Democrat improvement, but it should be the same for all races, regardless of whether the Democrat is ahead or behind.
(39/N)

More ballots come in Democratic, they each vote for every Democrat, so all Democrats increase in the same percentage terms. This isn’t what we find. In the data, within a ward, the important races go up more than the unimportant races.
(40/N)

The prediction that all races should be equally affected holds for many variations. Does the answer change if every Democrat voter has a 90% chance of voting for each Democrat candidate, if this attitude is the same those who vote in-person vs by mail? No.
(41/N)

The answer also doesn’t change if Democrat voters generally vote less for shoo-in candidates, but vote more in tight races. If holds equally for Democrats who vote by mail vs in person, there should be no difference across races in how much they break towards Dems.
(42/N)

You need something complicated to explain it. Dem voters vote less for Dem candidates if they know they’re know are going to win anyway, AND this instinct is somehow larger in Dem mail-in voters than Dem in-person voters, AND Dems vote more by mail overall.
(43/N)

If this sounds confusing, that’s kind of the point. We’re a long way from just Dems voting more by mail. It’s not impossible, and we can’t rule it out. But if it’s about mail-in ballots, there must be some difference *within Dem voters* between mail vs in person.
(44/N)

Races swung more towards Dems exactly where the Dems were down on Wednesday early morning. To explain this with mail-in ballots needs a very complicated story. To explain it with fraud needs a very simple story – you commit fraud more where the fraud matters more.
(45/N)

This is why the evidence suggests fraud to me, but your mileage may vary. I’ve tried to stick to the facts, as I don’t have any special ability to interpret the numbers above. Whatever is going on is crying out for explanation, and the simple alternatives don’t do it.
(46/N)

A final question to ponder. What should our null hypothesis be? When we say “there’s no evidence of fraud”, we’re claiming “no fraud” as the null hypothesis. To me, the system of vote counting is so broken that this is very difficult to justify.

https://twitter.com/shylockh/status/1324190811043581952?s=20

(47/N)

I find the possibility of voter fraud entirely plausible, and that belief has nothing to do which party you think is doing it. At a minimum, I feel strongly that this possibility needs to be investigated more seriously than it is, given the evidence above.
/fin
(48/N)

One postscript that people have asked about - why Milwaukee? Why not analyze everywhere else too? I picked Milwaukee after initial strange reports of ballots being found at 4am. But it took about 48 hours of work and writing to put together just this much.

Do you still believe that most voter fraud will be caught in time before it decides the election? Really?

Most people assume that there must be thousands of highly paid people working on this problem right now. I suspect the answer is more like ten, and I personally know about seven of them.

At least for doing this kind of analysis, not for the broad voter fraud question. But a similar issue applies, I suspect.