KittyRace – race CryptoKitties, win ETH

Hacker News

We launched KittyRace today, and would love to know what HN thinks! KittyRace is a dApp that lets CryptoKitty owners combine skill and chance, and race their kitties for a winner-take-all pot of Ether. The outcome of each race is decided by the logic defined in our Ethereum smart contract, and is based on each kitty's DNA (stored in the CryptoKitties smart contract), and a random roll. Check it out here: https://kittyrace.com For the best experience, please have MetaMask, a CryptoKitty, and headphones :)

Visit product View on Hacker NewsMar 29, 2018

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Actual performance

6points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

48%48% 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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

32%32% 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

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

17%17% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto, smart · Missing: web3, chat, cryptocurrency

14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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