BLITZ – Weekly Fantasy Football with Live Drafts

Hacker News

Hi guys, It's my pleasure to introduce to you something I've been working on over the summer - BLITZ. https://blitz.zone/ It will require an access code when you first download it (this access code has 1000 uses): Access Code: cPJCeF4F Looking for feedback on the draft experience. Thanks! Known Issues: Android is not done yet, only iOS can play today. Anticipate Android completion by Week 2. If you don't find a match, cancel and re-queue.

Visit product View on Hacker NewsSep 2, 2014

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Actual performance

3points

1comments

Did not reach leaderboard

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRLess likely to generate early MRR · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

37%37% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos

26%26% predicted probability of success on Product Hunt, 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 · Strong signals: introduce · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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