College Hoops Data was built with one goal: to help college basketball fans see the game differently. We believe that the best basketball analysis combines the eye test with data-driven insights, and our platform brings advanced analytics to every NCAA Division I team and game in a way that is accessible, visual, and actionable.

Whether you are a casual fan tracking your alma mater, a bracket enthusiast preparing for March Madness, or a serious analyst studying matchup tendencies, College Hoops Data gives you the tools to understand the game at a deeper level.

Live Scores and Box Scores: Real-time scores for every Division I game with detailed box scores, player statistics, and game flow data. Our scoreboard updates automatically so you never miss a crucial moment.

NET Rankings and Quad Records: The official NCAA NET rankings updated daily, with complete quadrant record breakdowns that the Selection Committee uses to evaluate tournament teams. Understand the difference between a Quad 1 road win and a Quad 4 home win.

CHD Scout Predictions: Our prediction model analyzes team efficiency metrics, player form, home court advantage, strength of schedule, and historical matchup data to forecast game outcomes. Each prediction includes a detailed breakdown of which team has the edge and why.

Tournament Simulator: Simulate remaining schedules to see how future results would impact a team's tournament resume. Get tournament grades from A+ to F based on the same criteria the Selection Committee evaluates.

Team and Player Analytics: Deep dive into every Division I team with offensive and defensive efficiency ratings, shooting percentages, rebounding rates, turnover margins, and more. Track individual player performance with hot and cold streak indicators.

In-Depth Game Coverage: Game previews and recaps that analyze matchups, highlight key players, and provide context for every game. Plus long-form editorial features on the coaching carousel, transfer portal, recruiting, and the biggest stories in college basketball.

The CHD Scout prediction model uses a multi-factor approach to forecasting game outcomes. Key inputs include adjusted offensive and defensive efficiency, NET rankings, recent team form, player hot/cold streaks, and venue-specific home court advantage calculations.

The model uses a dual-architecture approach: a primary model for standard predictions and a specialized close-game model that activates when projected margins are tight. This dual approach helps avoid overconfident predictions in what are genuinely uncertain matchups.

We continuously backtest and refine the model throughout the season to improve accuracy.

College Hoops Data was created by Brian Coleman, a software engineer with over a decade of experience building data-driven applications and a lifelong college basketball fan. What started as a personal project to better understand team matchups and tournament selection grew into a full analytics platform serving thousands of fans during the college basketball season.

Brian designed and built every layer of the platform — from the prediction model and data pipeline to the frontend experience and editorial content. He writes the site's long-form articles covering the coaching carousel, transfer portal, recruiting, and the biggest stories in college basketball, combining statistical analysis with the kind of narrative depth you'd find in a national sports publication.

The CHD Scout prediction model has been refined through multiple iterations across the 2025-26 season, with each version backtested against thousands of real games before deployment. The model's 76%+ winner prediction accuracy and transparent track record on the accuracy page reflect that commitment to getting the analysis right.

College Hoops Data is built with modern web technologies including Next.js, React, and Tailwind CSS for a fast, responsive experience across desktop and mobile devices. The backend uses Supabase for real-time data storage and retrieval, with Firebase Cloud Functions handling data synchronization, article generation, and prediction calculations.

Data is sourced from publicly available NCAA and ESPN feeds and is updated in real-time during live games.