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Your home for the Sunny Morning Show with Mark McGill and Michiana's #1 favorite place to listen at work and wind down at night with Delilah!
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
32%
Guest openness
Selective
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Signup to Generate a PitchYour home for the Sunny Morning Show with Mark McGill and Michiana's favorite place to listen at work and wind down at night with Delilah!
Recent episodes include "Mark and Julie Took Calls and Texts About Actual Haunted House Things That People Experienced. Break 2" (30 October 2026, 5 minutes), "Mark and Julie Took Calls and Texts About Actual Haunted House Things That People Experienced. Break 1" (30 October 2026, 7 minutes), and "Mark and Julie Talked About The "Official" Rules Of Trick or Treating." (30 October 2026, 5 minutes).
Sunny 101.5 publishes roughly daily, with episodes averaging 5 minutes across 50 episodes.
Booking probability for Sunny 101.5 is 32%, and the host is rated Selective on guests. Sunny 101.5 requires a Pod Score of 80 or higher. Sunny 101.5's contact route on record: verified email.
Sunny 101.5 is a music podcast with 50 episodes published.
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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Sunny 101.5
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Sunny 101.5
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Sunny 101.5
News and sports headlines for October 30, 2026. See omnystudio.com/listener for privacy information.

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Sunny 101.5
News and sports headlines for October 29, 2026. See omnystudio.com/listener for privacy information.

Sunny 101.5
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Recent guests on Sunny 101.5. Study who booked and why before you pitch.
Vice Dean for Student Success at Klein College of Media and Communication; Interim AVP for Enrollment Management, Boys and Girls Clubs of Indianapolis
Corewell Health
Corewell Health
Corewell Health
Based on semantic analysis of episode topics and host coverage, this podcast is a strong guest fit for executives in:
Industry fit is computed by PitchCentric using vector embeddings of the podcast's episode catalog.
Shows with the most semantically similar episode content. Pitch one, pitch all; producers cluster.
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