Scrimr - The Ultimate Scrim Finder

Hacker News

Scrimr: http://scrimr.com Those not familiar with what a scrim is: http://www.urbandictionary.com/define.php?term=scrim Scrimming with your team and friends is always fun and exciting, but why does finding a scrim have to be such a hassle? Typically the process starts off with one person saying "Somebody find a scrim!" which is almost instantly followed by one of the following responses: “I don’t have an account on [Insert Game Forum Name].” “I don’t know how to use IRC.” “I don’t have an IRC client installed.” “Ugh, it takes too long and I’m too lazy.” So, we decided that enough was enough and created Scrimr; the fastest and easiest way to find scrims. Check it out!

Visit product View on Hacker NewsDec 24, 2012

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1points

Did not reach leaderboard

Launch Intel predictions

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

73%73% 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

69%69% 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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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