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57match
electthebeard.com
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1 co-citations4 shared tech2 shared categoryelections
52match
kylekopko.com
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0 co-citations4 shared tech2 shared categorypolitics
52match
electarikan.com
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52match
electleehelton.com
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50match
electnataliehiggins.com
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0 co-citations4 shared tech2 shared categorypolitics
46match
jenkrimm.com
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1 co-citations4 shared tech1 shared categorypolitics
46match
kellykoenig.com
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1 co-citations4 shared tech1 shared categorypolitics
46match
kenhelm.com
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1 co-citations4 shared tech1 shared categorypolitics
45match
electbobboyer.com
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44match
electtazeen.com
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1 co-citations4 shared tech2 shared categoryelections
44match
jackwebbermbv.com
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1 co-citations4 shared tech2 shared categoryelections
43match
electhicks.com
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1 co-citations4 shared tech1 shared categorypolitics
43match
elijahstanfield.com
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43match
fenfowler.com
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43match
finlayson4treasurer.com
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1 co-citations4 shared tech2 shared categoryelections
42match
electionforall.com
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2 co-citations4 shared tech2 shared categorypolitics
42match
ballabon.com
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42match
coopermaine.com
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How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.