Brawl.dev

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Brawl.dev

https://brawl.dev/ Hi everyone, I made a game that's ready for some early testing. It's a programming game where you program bots to compete against other players (and/or predefined bots). You play by making web requests to the game APIs (see https://brawl.dev/documentation). The first type of game is a last man standing type game where you have to be the last one left inside a shrinking ring. (see https://brawl.dev/game?gameId=5845efdd-6fd4-48b2-b39c-0dd3a4f7a45b for example gameplay) I'm looking for feedback and if there's any killer features you'd like to be see. I'm planning on developing these next: - Paid private leagues - by default the game will be free but you are ranked globally with everyone. I'd like a way to allow players to compete in closed ranked leagues against their friends and/or coworkers. - Matchmaking - Right now it's first in first out for match placement. The ranking system takes that into account, but I'd like to utilize the ranking system and put players with same-ish ranks together.

Visit product View on Hacker NewsSep 9, 2019

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Actual performance

3points

Did not reach leaderboard

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

66%66% 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: apis · Missing: mac, agents, macos

55%55% predicted probability of success on Product Hunt, 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

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: way · Missing: mobile apps, ios, personal

39%39% 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

36%36% 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

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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