I

I Built a Click-to-Simulate 2024 Electoral College Calculator

Hacker News

I Built a Click-to-Simulate 2024 Electoral College Calculator

I built an interactive tool to simulate Electoral College scenarios for the 2024 U.S. presidential election. The app lets you: - Click states on a U.S. map to simulate electoral scenarios - See real-time electoral vote counting - Experiment with different state combinations Try it here: https://mirjamelad.github.io/adax-core-raw-example/ This is a non-partisan educational tool to help visualize how electoral votes add up. PS: What started as a mini project to test my adax-core library turned into a toy that people kept asking to play with. So I thought why not share it here :)

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios · Missing: supports, reddit linkedin, podcasting
66%66% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
46%46% 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: visual · Missing: mac, agents, macos
39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, visualize, education · Missing: mobile apps, personal, entrepreneurs
33%33% 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
13%13% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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