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80match
banddamusement.com
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1 co-citations5 shared tech0 shared categoryentertainment
80match
ferreraentertainment.com
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1 co-citations5 shared tech0 shared categoryentertainment
80match
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79match
makennagallagher.com
Makenna Gallagher - Makenna Gallagher
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76match
greghoovermusic.com
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74match
joepalmucci.com
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74match
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1 co-citations4 shared tech0 shared categorytelevision
74match
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1 co-citations4 shared tech0 shared categoryclassical-music
74match
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1 co-citations4 shared tech0 shared categorymovies
74match
ccjazzband.com
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1 co-citations4 shared tech0 shared categoryjazz
74match
djjayjay.com
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1 co-citations4 shared tech0 shared categorydance-and-electronic-music
74match
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1 co-citations4 shared tech0 shared categoryclassical-music
74match
georgetownquintet.com
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74match
geraintowen.com
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1 co-citations4 shared tech0 shared categoryclassical-music
71match
gufidelis.com
Gu Fidelis - Home
1 co-citations4 shared tech1 shared categorysongwriters-folk
70match
jacobanayamusic.com
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1 co-citations4 shared tech0 shared categorymusic
70match
3milesawayband.com
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1 co-citations4 shared tech0 shared categorymusic
67match
cedarwingmusic.com
CEDARWING - Home
1 co-citations5 shared tech0 shared categorymusic

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.