I created a free website that pairs Philips Hue lights with NBA games

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I created a free website that pairs Philips Hue lights with NBA games I just released a beta version of a site that allows you to connect your hue lights to live basketball games. Say the Miami Heat are playing the Los Angeles Lakers -- As the Heat start to take a big lead, the room will grow more and more red in real time. I originally made this app just for myself so that I could ambiently follow along with basketball games in the background while my partner and I watch movies, but I started using it during games and it turned out to really enhance the experience of watching. Looking for anyone to try it out and give me some feedback! Note: This doesn't play nicely on mobile currently unless you tell your internet browser to allow pop-ups. The first time you use this site, you will be warned in a pop-up that there is an insecure connection and you will have to click through that message and accept before returning to the site. This is due to something on the Hue API side. https://basketball.lighting

Visit product View on Hacker NewsDec 30, 2021

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

86%86% 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 HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos

48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: just released, ide, io · Missing: https docs, excited, exist

40%40% 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 · Missing: mobile apps, ios, personal

38%38% 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

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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