Feedback on our new multiplayer game API?

Hacker News

This is a two man team and we're in full-on development of a new platform to assist in multiplayer games. We're looking to launch in about a month or two with an OpenID server accessible to customers (or they can use provider like Facebook/Twitter) and a couple cool multiplayer features. After we launch development will continue until we have a well-rounded API.<p>We're primarily targeting HTML5+JS developers but the system will work with any language that can make RESTful API calls. We know there's some stiff competition out there but we're looking for feedback and what features may make you swing towards our pay-for model?

Visit product View on Hacker NewsJun 2, 2014

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

79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

63%63% 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: month · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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