City of the Rails

iHeartPodcasts · Society & Culture

YAPP has Smart‑Skip data for 10 episodes of City of the Rails. Recent episodes average 7 minutes of ads per 54‑minute episode.

7.8ad minutes per hourof runtime
13%of runtimeis advertising
4.5ad breaksper episode, on average
10episodesmeasured by YAPP

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Recent episodes

Ad time detected in the 10 most recent episodes of City of the Rails that YAPP has processed.
Episode Published Length Ad time Breaks
Living By The Tracks — E10 1:08:36 7:50 5
Fire in New Orleans — E9 56:55 7:16 4
All The Livelong Day — E8 59:01 6:50 5
Cops & Robbers — E7 1:01:09 8:13 5
The Comfort Offensive — E6 57:30 7:23 4
Tramp Town, USA — E5 46:04 7:11 5
Riding the Dragon — E4 46:35 7:45 5
The Fiercest Females On Earth — E3 50:07 6:01 4
The Yard — E2 47:58 5:35 4
I've Gone and Made a Fool of Everyone — E1 45:54 6:10 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 City of the Rails with YAPP

City of the Rails runs 4.5 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 7 minutes per episode, or 7.8 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 10 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 2% of detected segments were refined by audio fingerprinting; the rest rest on transcript timing and are less precise.

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