Legend Stickers

Legend Stickers

Indie Hackers

Collect legendary sports stars across 7 categories

I grew up collecting physical sticker albums (Panini-style) and missed that feeling as an adult. Most digital sticker-collecting apps are tied to one sport or one tournament, so I built Legend Stickers to bring that same

Share card

Actual performance

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, physical · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

To
Tokenship – A Sports Stars ERC20 Exchange25%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tokenship – A Sports Stars ERC20 Exchange

Hacker News1
Ma
Markbook – Automagically Collect, Organize, Search Your Upvotes/Stars46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Markbook – Automagically Collect, Organize, Search Your Upvotes/Stars

Hacker News10
Ki
KittyHats – Stickers for CryptoKitties38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

KittyHats – Stickers for CryptoKitties

Hacker News3
Ge
Get Corgi Stickers39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Get Corgi Stickers

Hacker News1
HO
HOV Mags – we made removable mag strips for the California CAV stickers39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

HOV Mags – we made removable mag strips for the California CAV stickers

Hacker News2
I
I Drew Stickers for Programmers53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I Drew Stickers for Programmers

Hacker News4
orion stars 777
orion stars 77715%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

orion stars 777

Indie Hackers
An
An AI for identifying porn stars24%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An AI for identifying porn stars

Hacker News6
He
Hexagonal stickers design40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hexagonal stickers design

Hacker News5
A
A website for exchanging McDonald's Monopoly stickers43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A website for exchanging McDonald's Monopoly stickers

Hacker News4