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DropZap World game for iOS and tvOS. [TestFlight Public Link, Videos]

Hacker News

DropZap World game for iOS and tvOS. [TestFlight Public Link, Videos]

Videos of three levels from the beta (there are over 100): https://youtu.be/N5RxNDTmsPQ https://youtu.be/NkCcYdBLrHY https://youtu.be/V0mXspbCW3U You can join the DropZap World beta anonymously using this TestFlight public link: https://testflight.apple.com/join/CdEXgjst The basic gameplay mechanic is that when a circle lands, it fires lasers of its color in four directions. These lasers destroy pieces of the same color. Any feedback would be appreciated!

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Strong signals: ios, video · Missing: mobile apps, personal, entrepreneurs
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
53%53% predicted probability of success on Indie Hackers, 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
37%37% 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, using · Missing: mac, agents, macos
31%31% 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
17%17% 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
10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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