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MathActive – Solve math equations quickly to dominate the leaderboard

Hacker News

MathActive – Solve math equations quickly to dominate the leaderboard

- Solve math equations as quickly as possible. - Your total score increases with each equation solved. - The more math equations you solve, the more complex they get. - Build your speed bonus multiplier by solving equations even more quickly. - Keep playing to improve your math skills and move up the MathActive leaderboard. - Use Practice mode to practice solving math equations without a timer. The Remove Ads IAP is FREE until May 31, 2024.

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
43%43% 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: io · Missing: https docs, excited, just released
41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
14%14% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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