Squaple – A Deceptively Simple and Challenging Puzzle Game

Hacker News

I'd like to share a new puzzle game concept I've been working on called Squaple. Drawing inspiration from the elegant simplicity of classic sliding puzzles and the profound mental challenge of chess, I set out to develop an entertaining game that doubles as a stimulating brain exercise. Squaple's core mechanics are quite straightforward, utilizing a 4x4 grid of tiles. The goal is to rearrange the tiles to match a given target pattern by swapping adjacent tiles of different colours. While the concept might seem simple at first glance, the game offers an unexpected degree of depth and complexity, providing ample opportunities for players to flex their cognitive muscles. I'm looking forward to your thoughts and feedback on Squaple as I continue to refine the concept and gameplay. Thank you.

Visit product View on Hacker NewsApr 25, 2023

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

80%80% 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: new · Missing: mac, agents, macos

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

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 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.

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

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

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

11%11% 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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