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Lige på podcast artwork

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Lige på

Hosted by TV 2 Fyn · news · DA

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About this Podcast:

I Lige på går vi tæt på et menneske i en aktuel historie, som udspringer af din hverdag, og som du gerne vil være klogere på. Produceret af TV 2 Fyn.

Pitch Analysis

Required Pod Score for this podcast. PitchCentric checks your profile against host openness, topical fit, and audience signals before you generate a pitch.

Contact path

Verified email

Booking probability

33%

Guest openness

Selective

Verified email on file
80/100
Required Score

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Questions about Lige på

What is Lige på about?

I Lige på går vi tæt på et menneske i en aktuel historie, som udspringer af din hverdag, og som du gerne vil være klogere på. Produceret af TV 2 Fyn.

What has Lige på covered recently?

Recent episodes include "Lukket vej i Odense deler borgerne - Karsten mener, at gaden har fået nyt liv" (30 October 2026, 29 minutes), "Ann-Sofie skammer sig over manglende sex - Nicolaj kalder det noget pis" (28 October 2026, 28 minutes), and "Han er sprunget ud, men homofobien sidder stadig i ham selv" (26 October 2026, 28 minutes).

How often does Lige på publish?

Lige på publishes roughly a few times a week, with episodes averaging 29 minutes across 70 episodes.

How hard is it to get booked on Lige på?

Booking probability for Lige på is 33%, and the host is rated Selective on guests. Lige på requires a Pod Score of 80 or higher. Lige på's contact route on record: verified email.

About the host

Lige på is a news podcast with 70 episodes published.

Verified host email: ████████@████.comSign in to unlock →

Recent episodes

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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Recent guests

Recent guests on Lige på. Study who booked and why before you pitch.

D

Davide Giacalone

N

Noah Lykke Knudsen

Odense Pride

Best industries to pitch Lige på for

Based on semantic analysis of episode topics and host coverage, this podcast is a strong guest fit for executives in:

newsstrong

Industry fit is computed by PitchCentric using vector embeddings of the podcast's episode catalog.

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