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Track Your Flights and Compete on Global Leaderboard for Free

Hacker News

Track Your Flights and Compete on Global Leaderboard for Free

Hi Guys, Over the past few years I've been collecting my boarding passes a way to think back to the places I've been and the flights I've been on. I know there are a lot of travel geeks like myself out there so I want to create simple repository for your flight and travel history. And I thought why not have a leaderboard so show how many miles people have flown and how many cities they been too. The website is completely free. All you have to do is login and upload an image of your boarding pass and we handle the rest. If you don't want to be on the leaderboard there is an opt out option. I'd love for you guys to check it out.

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Actual performance

1points
1comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% 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.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
50%50% 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 · Missing: mac, agents, macos
49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% 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.

Correct prediction on native model

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