True Crime All The Time
Emash Digital · Society & Culture
YAPP has Smart‑Skip data for 15 episodes of True Crime All The Time. Recent episodes average 4.1 minutes of ads per 62.9‑minute episode.
Listen to the good stuff in True Crime All The Time
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Recent episodes
| Episode | Published | Length | Ad time | Breaks |
|---|---|---|---|---|
| Paula Chin | 53:40 | 1:02 | 1 | |
| Clara Rector | 58:54 | 3:32 | 3 | |
| Eric Plunkett and Benjamin Varner | 1:07:23 | 5:39 | 4 | |
| Jayne Salazar-Chavez | 56:56 | 2:29 | 2 | |
| Starr Harris | 57:53 | 6:11 | 5 | |
| Michele Carson | 58:02 | 2:34 | 3 | |
| Bob Lee | 57:49 | 1:37 | 1 | |
| Jack Irwin | 1:09:26 | 4:43 | 4 | |
| Samuel Hochstetler | 59:18 | 4:38 | 5 | |
| Denise Huber | 1:15:41 | 3:28 | 4 | |
| Cathy Sposito | 52:41 | 3:30 | 4 | |
| Shilie Turner | 1:07:10 | 4:07 | 4 | |
| David Grunwald | 1:08:27 | 4:47 | 5 | |
| Ben Renick | 1:16:49 | 8:23 | 6 | |
| Caroline Muirhead and Sandy McKellar | 1:03:14 | 5:16 | 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 True Crime All The Time with YAPP
True Crime All The Time runs 3.7 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 4.1 minutes per episode, or 3.9 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 15 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 20% of detected segments were refined by audio fingerprinting; the rest rest on transcript timing and are less precise.
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