Video Competition Website

Hacker News

Hi HN, I created a site that allows people to create competitions from videos in YouTube: https://competitiontube.com Anything from comedy competitions like this: https://competitiontube.com/competition/HGX20xe7ziLXpIQOQ6 to political debates: https://competitiontube.com/competition/NOW20xe7ziLXpIQOQ6 or whatever else they like (anything at all). I have a catch-all "Misc" genre for anything not fitting the drop down options when categorizing new competitions. I created it mainly to teach myself the following technologies: 1- ReactJS 2- Redis 3- MongoDB 4- Python 5- Docker 6- Docker Swarm 7- nginx The site is something I thought about long ago but put on the back burner until I decided to learn ReactJS and Redis. It is very simple and has some simple rules. 1- Just like any real competition it has rounds (I limit it to 4) 2- It allows users to either pause the competition so that they could swap out videos in different rounds or allow winning videos to auto propagate upwards towards the final round 3- It allows the competition creator a chance to decide what to do in the event of a tie between competitors: allow the server to decide or they can break the tie themselves. In cases where manual intervention is needed, i.e. they decide to change videos or break ties at the end of the round, the next round is paused and they are sent an email asking them to login and update the competition. In all it took about a month to complete (life, family, learning, etc) but it was tons of fun. Next projects will be centered around computer vision, machine learning, and lots of other crazy ideas I have. Please check out the site and create a competition to get a feel for what it does. If you view it from a desktop, I show the entire competition tree so it is immediately clear what is going on. On mobile it uses a sliding carousel of competing pairs.

Visit product View on Hacker NewsSep 23, 2019

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

80%80% 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.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user, computer · Missing: agents, macos, agent

52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% predicted probability of success on TrustMRR, 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

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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