A
A leaderboard for podcast *episodes*
Hacker NewsA leaderboard for podcast *episodes*
Inspired by Matt Turck's tweet from a couple weeks ago: "A HackerNews style leaderboard, but for best podcast episodes for the tech crowd on any given week" https://twitter.com/mattturck/status/1749071475821183374 As IMDb does for movies, there ought to be a list of the top 1,000 podcast episodes of all time — filterable by category. This is my attempt to build that.
Share cardActual performance
2points
2comments
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsMay not resonate with HN audience · Strong signals: 000 · Missing: https docs, excited, just released49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting31%31% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
Th
The Instavest Leaderboard40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The Instavest Leaderboard
Hacker News6
ScoreLeader36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Scoreboard & Leaderboard App
Product Hunt+6We
Well Made podcast45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Well Made podcast
Hacker News2Fi
Find your next favourite podcast29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Find your next favourite podcast
Hacker News4A
A podcast for socialist techies45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
A podcast for socialist techies
Hacker News4Ba
Banter – Podcast Together45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Banter – Podcast Together
Hacker News1Se
Settled Afar Podcast40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Settled Afar Podcast
Hacker News6Wa
Wannabe Entrepreneur Podcast45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Wannabe Entrepreneur Podcast
Hacker News2Po
Podcast of me trying to become an entrepreneur37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Podcast of me trying to become an entrepreneur
Hacker News1Th
The first episode of my podcast48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
The first episode of my podcast
Hacker News1