Ma

Match HN Comments to Posts

Hacker News

Match HN Comments to Posts

This is my HN comment-to-post guesser game. I posted this back in 2022. It didn’t get much buzz, so I’m posting it again. :) I use it myself almost daily as a sort of Wordle alternative. It’s written with SolidJS, and I remember spending quite a while on the animations. I polished it primarily for mobile interaction. Let me know how many flips you get!

Share card

Actual performance

1points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
69%69% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% 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
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
30%30% 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, 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 · Missing: web3, chat, crypto
18%18% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

A
A game where you match HN comments to posts50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A game where you match HN comments to posts

Hacker News3
th
the best hn posts and comments since 200768%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

the best hn posts and comments since 2007

Hacker News1
Se
Search over 100M archived posts and comments scraped from Parler66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Search over 100M archived posts and comments scraped from Parler

Hacker News16
Cl
Clicking this will collapse all comments even if you didn't do so50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Clicking this will collapse all comments even if you didn't do so

Hacker News11
Tr
Tremapping Comments from HN with WebGL73%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tremapping Comments from HN with WebGL

Hacker News4
Em
Embeddable hackernews comments69%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Embeddable hackernews comments

Hacker News3
Le
Lectio, contextualized comments for lectures75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Lectio, contextualized comments for lectures

Hacker News21
Co
Collapse HN Comments54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Collapse HN Comments

Hacker News141
Fl
Flocking comments63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Flocking comments

Hacker News3
Co
Collapsible comments for HN (Greasemonkey)66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Collapsible comments for HN (Greasemonkey)

Hacker News1