I created a game to memorize guitar/bass fretboard intervals

Hacker News

Hey all About 6 months ago I shared a game I made to help guitarists and bass players memorize the notes on the fretboard (Fretboard Fly). This time round, I’ve built some games to help you memorize the fretboard intervals as well. A lot of you also mentioned that the game was too hard so I also built courses to go along with the games. To be completely upfront about this, I’m trying to turn Fretboard Fly into a paid product but still stumbling my way through it. For now I’ve made all the intervals courses and games free to learn and play for at least a few weeks. In exchange I’d love to hear feedback about what you would want changed or added or if there’s anything you find confusing.

Visit product View on Hacker NewsOct 6, 2023

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2points

Did not reach leaderboard

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

83%83% 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.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

69%69% 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: using, notes · Missing: mac, agents, macos

50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

26%26% 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

19%19% 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.

Incorrect prediction on native model

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