Heavyweight

Pushkin Industries · Society & Culture

YAPP has Smart‑Skip data for 12 episodes of Heavyweight. Recent episodes average 9 minutes of ads per 50.4‑minute episode.

10.7ad minutes per hourof runtime
17.9%of runtimeis advertising
4.8ad breaksper episode, on average
12episodesmeasured by YAPP

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Recent episodes

Ad time detected in the 12 most recent episodes of Heavyweight that YAPP has processed.
Episode Published Length Ad time Breaks
#68 Songe 49:34 10:16 5
#67 Jenna 48:34 11:01 5
2026 Update: James 45:56 6:35 5
Jonathan Vs. Kalila on Smash Boom Best 44:57 9:08 6
2026 Update: Julia 45:30 10:23 3
2026 Update: Brandon 48:45 9:05 5
2026 Update: Frederick J. Brown 42:20 5:53 4
2026 Update: Christina 56:55 9:34 5
2026 Update: Skye 1:01:07 10:44 6
Jonathan Goldstein on Wild Card 52:59 9:39 5
2026 Update: Elyse 57:02 10:38 4
2026 Update: Tony 50:51 5:18 4

Ad load varies by listener. Most podcast advertising is dynamically inserted, so figures reflect ad load as observed by YAPP's processing pipeline at the time each episode was fetched, not what any individual listener hears. Methodology

Listening to Heavyweight with YAPP

Heavyweight runs 4.8 ad breaks in a typical episode, so there is a fair amount between you and what you came for. Across the episodes we have processed, that comes to about 9 minutes per episode, or 10.7 minutes for every hour of listening.

YAPP maps each episode before you play it, so you get the show and not the rest of it. Because the ads are stitched in per listener, YAPP matches what you are actually hearing rather than replaying a fixed set of timestamps.

How these numbers are measured

YAPP transcribes each episode, classifies advertising segments, and refines their boundaries using audio fingerprinting. Figures cover the 12 episodes of this show that YAPP has processed. Because most podcast ads are dynamically inserted and vary by listener, these figures reflect what our pipeline observed rather than what every listener hears. Full methodology

Boundaries for 5% of detected segments were refined by audio fingerprinting; the rest rest on transcript timing and are less precise.

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