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A news aggregator for statistical and opinionated news

Hacker News

A news aggregator for statistical and opinionated news

Get it on the iOS App Store! - https://itunes.apple.com/us/app/newstats/id1447909632?ls=1&m... -- News is something people read everyday - it's the source for readers to educate themselves on politics, science, sports, or whatever else crosses their feeds. With news being such a strong source of information in society, wouldn't you want it to be straightforward and factual? Newstats: Where news meets statistics Welcome to Newstats, a news aggregator tailored specifically for those who want their news to be simple and factual, without the distractions of images, clickbait articles, and stories and sources you just don't want to see. Our stories come from RSS feeds from sources we have hand-picked for being forthright and efficient. -- Hi, I'm Noah. Newstats is the first app I have submitted to the App Store - and the first mobile app I have ever created! The beta group and the people who have used it so far have given it great reviews and have provided valuable feedback, and I decided to share it here for all you guys as well. I hope you enjoy it!

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting
89%89% 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.
Product HuntUnlikely to reach the leaderboard · Strong signals: apple, new · Missing: mac, agents, macos
46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: reviews, efficient · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% 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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