Na
NaSC – Do maths like a normal person
Hacker NewsNaSC – Do maths like a normal person
Share cardActual performance
127points
24comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos62%62% predicted probability of success on Product Hunt, 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 · Missing: https docs, excited, just released52%52% 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, personal43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto41%41% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
Similar products
So
Socially distant ordering for in-person venues44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Socially distant ordering for in-person venues
Hacker News1Th
This Person Exists42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
This Person Exists
Hacker News11Na
Name-classifier – infers attributes about a person from a name49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Name-classifier – infers attributes about a person from a name
Hacker News2Add Person To Photo49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Like They Were Always There.
Indie Hackerscommitment-full-timeSh
Shuruka Boxing – First person Boxing game42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Shuruka Boxing – First person Boxing game
Hacker News1Co
Collete-01 - Person in a Model47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Collete-01 - Person in a Model
Hacker News3Ts
Ts3d: Ncurses-Based First-Person Shooter45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Ts3d: Ncurses-Based First-Person Shooter
Hacker News5He
Help a Laid Off Person – Halo40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Help a Laid Off Person – Halo
Hacker News1pr
procedurally generated first-person Roman ruins44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
procedurally generated first-person Roman ruins
Hacker News1hc
hcode One-Person Engineering - SDLC Approach54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
hcode One-Person Engineering - SDLC Approach
Hacker News4