Bridging the Gap Between Complex Data and Basketball Fans with the Power of AI
- HoopsGPT is a tool designed to analyze over 18 million plays, 340,000 games, and 3,000 NBA players using GPT-4.
- The platform uses a Natural Language to SQL approach, leveraging Large Language Models (LLMs) to make data analysis more accessible.
- HoopsGPT is part of a larger project, textSQL, which plans to integrate data visualization and bring-your-own-data (BYOD) capabilities.
HoopsGPT.ai, a new online tool utilizing GPT-4, aims to revolutionize how basketball enthusiasts access and analyze NBA statistics. From match-up specific shot charts to career averages against individual opponents, HoopsGPT uses the power of AI to provide users with a wide range of in-depth statistics for over 18 million plays, 340,000 games, and 3,000 players.
HoopsGPT is the latest addition to the textSQL project, which employs Large Language Models (LLMs) to democratize data analysis. By translating natural language inquiries into SQL, textSQL opens the door for anyone, regardless of their technical proficiency, to analyze and gain insights from vast data sets. Two other prominent use cases of textSQL are San Francisco GPT and CensusGPT, which serve as natural language interfaces to public data from San Francisco’s city data and US census data respectively.
The interface allows users to input queries in simple English, such as “Lebron’s shot chart against the Nuggets in the playoffs,” or “AD’s career averages against Jokic.” The system then uses GPT-4 to transform these queries into SQL, which it uses to extract relevant data.
The roadmap for textSQL is split broadly into two areas: visualizations and BYOD (Bring Your Own Data) functionality. Current visualizations are limited to interactive maps and bar charts using Mapbox + Plotly. However, there are plans to expand this into other visual formats, such as heatmaps and pie charts, as well as a text-to-vega engine for creating and iterating on data visualizations in natural language.
The BYOD feature is a significant development, enabling users to connect their databases and datasets to textSQL and self-host the service. This makes textSQL a potentially valuable tool for various stakeholders such as researchers, journalists, and non-technical employees in the business intelligence domain, enabling them to explore data and build queries with ease.
The release of HoopsGPT marks a significant step towards democratizing data analysis and enhancing accessibility to advanced NBA statistics for basketball fans worldwide. As part of the wider textSQL project, HoopsGPT’s launch signifies an exciting direction for data analysis, where complex databases can be navigated and understood through simple natural language queries.