ZombieRun – retro platformer that brings back sexy to local co-op

Hacker News

I have now finished 2 years of hard work with an indie game called ZombieRun. Game description: After a massive apocalyptic thunderstorm you find yourself in the middle of a dark graveyard with two hungry zombies drooling over you. It seems that the thunder wasn’t the only thing that hit the world while you were out. Do you want to know what it was? It’s time to act fast, stay alive and get to the city for some answers. That’s where it all begins - it's you, your fast reflexes and guns against all the dead lurking around. The game features classical weapons, gang of living dead and superpowers. Yes, you have SUPERPOWERS! ZombieRun has addictive single player mode and awesome local multiplayer games. Up to 4 players can play at the same time in either single screen co-op mode, where you have to work together as one or split screen competitive mode, where everyone's running for their lives. And also there's the Battle mode where players can blast at each other with what they've got. ZombieRun has controller support, so you can dust off the old joypads. ZombieRun requires a graphics card with OpenGL support and JRE 1.6 or later. Announcement Trailer: https://www.youtube.com/watch?v=a-vWPXxtevE You can get ZombieRun from http://zombierun.eu All feedback and comments are welcome.

Visit product View on Hacker NewsOct 29, 2014

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

79%79% 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.

Product HuntOn track for Day 1 leaderboard · Strong signals: single, open · Missing: mac, agents, macos

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: answers · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% 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

14%14% 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.

Incorrect prediction on native model

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