Sports Data Aggregation Platform

An existing sports data aggregation platform was already in place, but it required significant improvements to handle larger datasets, improve performance and enhance the user experience. The platform needed to fetch and display real-time sports data (e.g. live scores, upcoming games, leagues, teams and news) for multiple sports, including soccer, basketball, hockey, Formula 1, baseball and American football. Additionally, the database (MongoDB) required optimization to handle increased data loads efficiently.

We enhanced the platform by restructuring the data flow, optimizing the MongoDB database and improving the frontend UI/UX. Key improvements included: database optimizations such as adding indexes and improving query performance to handle larger datasets efficiently, reorganizing the data models to better align with the API responses and frontend requirements. Redesigning and adding new pages to improve navigation and user experience and fetching and utilizing more data from the API to provide more information. The platform now displays upcoming games with schedules for future matches across all supported sports, detailed information about leagues, teams and players, a news feed with short summaries and links to full articles. Supported sports include soccer, basketball, hockey, Formula 1, baseball and American football.

• Comprehensive Coverage: Detailed information on leagues, teams, upcoming and past games.
• Improved Performance: Optimized database and queries for faster data retrieval.
• Enhanced UI/UX: Redesigned pages and navigation for a better user experience.
• News Integration: Sports news feed with summaries and links to full articles.

• Frontend was developed using Next.js and for admin panel C# Blazor was used.
• For the backend we used .Net Core.
• MongoDB with optimizations such as indexes.
• Third-party sports data APIs for live scores, schedules, and news.

We began by analyzing the existing platform’s data flow and database structure. We then restructured the data model and optimized MongoDB by adding indexes and improving queries. Next, we enhanced the frontend by redesigning existing pages and adding new ones to display additional data. Finally, we integrated more data from the API, ensuring the platform provided comprehensive and real-time sports information.