HighlightIQ

Unlock the Game, Elevate the Experience.

Comment

Inspiration

Baseball is a data-driven sport, but fans and analysts often struggle to access and interpret real-time insights from ongoing games. HighlightIQ was born out of a passion for making baseball statistics and game highlights more interactive and accessible, allowing users to engage with live MLB games in an intelligent and intuitive way.

What it does

HighlightIQ is an AI-powered platform that provides real-time insights into MLB games. Users can:

  • View live game statistics and analytics.
  • Interact with an AI assistant to get in-depth explanations about plays, teams, and player performance.
  • Watch key game highlights through integrated YouTube videos or uploaded files.
  • Analyze advanced statistics with AI-powered breakdowns.

How we built it

We developed HighlightIQ using cutting-edge technologies to ensure real-time data processing and seamless AI interactions:

  • Frontend: Built with Next.js for a fast and dynamic user experience.
  • AI Integration: Leveraged Google's Gemini API to process and interpret game data.
  • Data Processing: Trained a custom model with baseball statistics using Google's AI infrastructure.
  • Media Integration: Embedded YouTube highlights and enabled user uploads for deeper analysis.
  • Real-time Updates: Integrated APIs to fetch live game data and provide instant insights.

Challenges we ran into

  • Real-time Processing: Ensuring AI responses and game data updates were instantaneous.
  • Data Accuracy: Validating AI-generated insights against official MLB statistics.
  • Seamless User Experience: Designing an intuitive interface that caters to both casual fans and professional analysts.
  • Scalability: Managing large volumes of live data without compromising performance.

Accomplishments that we're proud of

  • Successfully implemented real-time AI-powered game insights.
  • Created a seamless video and data integration to enhance user experience.
  • Developed a custom AI model tailored to baseball analytics.
  • Built a scalable architecture that can handle live interactions during high-traffic game events.

What we learned

  • Optimizing AI models for sports analytics requires balancing speed and accuracy.
  • Real-time applications demand efficient data streaming and API optimization.
  • Sports fans engage better with a mix of AI-driven analysis and video highlights.
  • Seamless UI/UX is crucial for keeping users engaged during live games.

What's next for HighlightIQ

  • Expanding coverage to other sports leagues beyond MLB.
  • Enhancing AI capabilities with predictive analytics for game outcomes.
  • Developing personalized insights based on user preferences.
  • Adding multi-language support to reach a global audience.
  • Partnering with sports media platforms to bring exclusive AI-powered content to users.

Built With

Share this project:

Updates