A ranked-choice analysis · Maine, July 2026

What the slate
was worth

Over one July weekend, 17,279 Maine Democrats chose 500 convention delegates — plus 101 alternates — from a ballot of 3,666 neighbors. Part 1 showed why that weekend, not the convention, will likely decide the Senate nomination. This piece looks more closely at the results themselves: using every published vote total from all 16 counties and the three campaigns' published slates, we can measure exactly what an endorsement was worth — and meet the handful of people who out-ran the odds.

by Philip Englund Mathieu

The model

How we built this

This analysis uses Bayesian statistics to help us understand the uncertainty around any given candidate's vote totals. At its core, Bayesian techniques help you to mathematically quantify every quantity you don't know — how much a slate was worth, how generously a county's room spread its votes, etc. Each piece of evidence narrows the range of uncertainty on our estimates of those factors. A model fit this way states assumptions up front, then uses data to find the parameters that best represent that data.

We model every candidate's vote total like this:

Breaking that down:

By stating these assumptions up front, we can use them to calculate the expected result, as well as the degree to which our observed result differed. Whatever remains for any one candidate once county, ballot position, and slate are priced in — actual votes minus the model's expectation — is fairly called their personal vote. As an added feature of Bayesian statistics, every effect arrives with an uncertainty range instead of just a point guess. See the Method section below for details, or scroll on to see it in practice.

The baseline

Penobscot County's ballot was a wall of 341 names competing for 44 delegate seats and 9 alternate spots; each of the county's 1,046 voters could mark up to 53 of them. No parties next to names, no offices, no districts. Just names.

Start with a generic candidate. Random votes - neighbors, friends, town-mates voting for every name they recognize, etc. - earns about 4-5% of ballots on a typical person, roughly 50 votes of Penobscot's 1,046.

The alphabet

But ballots ran alphabetically, and it shows: a name at the bottom of a long ballot collects up to a tenth fewer votes than the same name would at the top. Our candidate — the "S. F." on the card — files under F, high on Penobscot's ballot, so the adjustment here is about two votes. It's a bias too small to see on any one card, and unlikely to shift many votes, yet still big enough to observe. This effect could be easily mitigated by rotating or randomizing the order, but doing so would mean each person gets a different ballot, and looking up a candidate by name becomes more difficult.

The slate

Now the piece that dwarfs the others. Averaged across every county and candidate, appearing on Troy Jackson's slate was worth +31 percentage points of ballots on top of the baseline; Nirav Shah's was worth +15; Shenna Bellows's roster, just +6.

The gap is discipline, not just reach. Jackson's pages said "vote for every name on the slate and no other names," and his voters did: his slate-mates' totals move in near lockstep, while Bellows's listed names barely outran the unslated. Jackson's organization amplified his slate's power by encouraging voters to explicitly avoid voting for anyone beyond his slate.

The personal vote

Adding these three pieces up produces a predicted vote range for every candidate. The difference between that prediction and the actual count is the part no list explains, or the "personal" vote.

Here is the card we've been watching. Sean Faircloth — a sitting state representative from Bangor — was on Jackson's slate, which lifts his prediction to about 410 of Penobscot's 1,046 ballots. He drew 605, the most of any Penobscot candidate. The slate carried him to the line, but his personal vote brought him +195 beyond it.

For most candidates, the final result boiled down to whether they were or were not on the Jackson slate — but not for everyone. Let's look at some real examples to see how different archetypes fared.

Your turn

Look up a delegate card

All 3,666 candidates from the July 18–19 county meetings are here. You start with a card dealt at random — search a name, deal again, or jump to any county's top vote-getter. Chances are you know someone in the deck.

Cards show official results (Maine Democratic Party) against this model's expectations. The shaded band on the actual bar is the model's 95% expected range for a card like that one; a red tag appears only on the 5% of cards that landed outside their band — everything untagged is within ordinary spread. A card's "personal vote" is a model residual, not a judgment — for slate members, matching the prediction just means the slate was the story. Public roles are noted only for verified current state legislators.