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Sudecku – A Deck-Building Sudoku (For iOS)

Hacker News

Sudecku – A Deck-Building Sudoku (For iOS)

Hi HN, I'm excited to share Sudecku, my first iOS game. It combines classic Sudoku with deck-building strategy. If you enjoy logic puzzles or card games, you might enjoy Sudecku. The idea started from playing a lot of Sudoku with my wife and watching Cracking the Cryptic solve some wild sudoku variants. I was also inspired by Balatro, which showed how much depth and replayability can be added to a simple cards game. That got me thinking about what would happen if Sudoku had power-ups sort of like Uno action cards or Balatro’s combos, and deck-building mechanics. After countless hours of playtesting and feedback (mostly from my wife), Sudecku finally came together. It's a paid app. One-time purchase kind of deal. There are no in-app purchases or ads. You get the full game up front. It's also iOS only for now, but I'm definitely open to releasing on other platforms if there's demand. You can check it out here: - App Store: https://apps.apple.com/app/sudecku/id6747517140 This was a labor of love for me, and I'd love to hear what you think, any feedback or questions are welcome. Thanks for checking it out! (Happy to answer any questions about the game or the development.) PS. If you'd like to try the game but can't pay for it for some reason, please email me (me at my first name dot com) and I'll happily provide you with a promocode. Thanks!

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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: started, wife, ios · Missing: supports, reddit linkedin, podcasting
94%94% 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 HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, email · Missing: mac, agents, macos
56%56% 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, apps · 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: excited, ide, io · Missing: https docs, just released, exist
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.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
37%37% 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
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · 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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