I've Built a IPTV Player for iOS

Hacker News

Hello everyone at HN, my name is Tiago, and I developed an iOS app for watching IPTV movies, Movie Stream. Right now I’m at version 6.0, and the app includes features like Search, Playlist Refresh, iCloud Sync, Picture-in-Picture & Airplay Support. https://moviesstreamapp.com The app is completely free, if you like (and only if you want) you can donate inside the app to support future development. I’m working by myself on the project since the beginning of this year. Do want to help me shaping the future development? What do you think the app does well and what it is still lacking? https://itunes.apple.com/us/app/movie-stream-ip-tv-films/id1...

Visit product View on Hacker NewsMay 8, 2019

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Actual performance

4points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

46%46% 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: apple · Missing: mac, agents, macos

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% 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, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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