Show HN: Hooper – AI-driven stats and highlights for basketball play

grub007 | 124 points

This is a cool idea, nice work. I spent some time as an assistant college coach in the NCAA and the amount of time spent reviewing film and capturing key plays/schemes etc is huge. I do some computer vision and always wondered if it would ever be accurate enough to skip over dribbling up the courts, time outs etc so scouts could just get to the important parts of the film—it looks like you are on track with what you claim it can do. I might sign up for the beta... good luck!

elpakal | a month ago

This is awesome, thanks for sharing! Hooper sounds like a fantastic app for pickup basketball players. I love the idea of tracking actual gameplay and creating highlights. The ability to sync recordings and differentiate shots is impressive. Can't wait to try it out and see how it tracks my games. Great work!

Avisan | a month ago

Amazing. Pitched something like this to a friend a few days ago and its awesome that you've built it. Headed to a game now and down to use it and give feedback (im in two groups and both have people setting up phones to record). Now add in an AI ref so people can stop arguing for 10 minutes over wether someone stepped out of bounds or not in a pickup game.

frankdenbow | a month ago

This is very interesting and well executed for the initial release. Good luck!

One thing I found odd was that the default/main screen in the app is a feed. That feed is just short videos without any of the game data the app captures. Perhaps an overlay would showoff the app as well as the skills. The videos by themselves don't add much differentiated value.

jussy | a month ago

This combines three of my greatest passions - basketball, computer vision, and analytics. I love it! Thanks for sharing :)

goochphd | a month ago

I love this! looked into doing a similar project, you're competing against Hudl but using the phone instead of custom hardware (always preferred). Highlight segmentation may be a challenge with SOTA cv methods, but there are lot of directions you can go in.

goodmattg | a month ago

Cool but offence is only half the story! Any plans to add defensive stats or stuff like turnovers / steals etc?

Also any plans to make it work from camera footage e.g. A 360 camera that can capture the whole court at once instead of syncing?

drited | a month ago

Are you using some sort of naive profanity filtering for profile names? I couldn't create an user name with "assist" in it due to "ass" being included?

pierrefermat1 | a month ago

Awesome! I someday hope to find the time to make something like this for soccer - individual skill drills as well as gameplay analysis.

Care to share any technical details about how your analysis pipeline works? :)

bl0b | a month ago

Very awesome, congrats on your release! I know of a similar golf app that made absolute bank, so if there's a niche and you can tap into it, you guys will likely do quite well.

dvt | a month ago

92% accuracy is really good! Is this just action recognition and player identity at the moment or are you actually generating full tracking data under the hood?

thom | a month ago

This looks pretty sick and the site and promo video is very well done also. Nice job.

seanhunter | a month ago

This looks great. curious, Is is something similar for tennis and/or ice skating?

apwell23 | a month ago

Well done, ai_bullish++

foobarkey | a month ago

Please do surfing next and add it to Surfline

dabs | a month ago

What are you using for video analysis?

marban | a month ago

sweet

bbstats | a month ago

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bkjshki | a month ago

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jmkx | a month ago
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