Track & Field Dreams

Track & Field Dreams is a data-driven recruitment platform designed to automate the connection between high school athletes and college coaches. Founded by Fredie and Jonathan Glass, the platform disrupts the traditional recruitment model by "pushing" athlete performance metrics directly to college coaches when they meet specific conference championship standards.

By leveraging objective data like times, distances, and heights, Track & Field Dreams provides a scalable, affordable alternative to expensive generalist recruiting sites. The platform serves a diverse ecosystem including athletes aged 11–18, their parents, transfer portal athletes, and paying college recruiters.

Before Track & Field Dreams, the recruitment industry relied on "search-based" platforms where the burden of discovery fell entirely on manual effort. Despite track & field being a uniquely data-driven sport with objective measures, no existing solution leveraged this data to automate the matching process.

Developing Track & Field Dreams required addressing several deep-seated inefficiencies in the sports technology market:

• Financial Barriers: Existing platforms often charge athletes over $2,000/year for premium recruitment features.

• Search-Based Inefficiency: Both coaches and athletes spent excessive time manually searching databases and profiles rather than focusing on qualified matches.

• Lack of Specialization: Multi-sport platforms lacked the event-specific data integration required for track & field’s 30+ unique events.

• Compliance Complexity: Building a system that adheres to COPPA (for athletes under 13) and NCAA communication regulations.

• Verification and Trust: Ensuring performance data is verified through high school coach workflows and screenshot-based proof.

• No automated qualification matching: No platform matched athletes to programs based on actual conference championship standards.

• Exposure inequality: Athletes without extensive networks or geographic advantages were systematically disadvantaged.

• Time-consuming searches: College coaches wasted countless hours filtering through unqualified prospects or watching highlight videos.

• High costs for families: Parents were forced to pay high fees for uncertain recruitment results.

• Manual processes: Athletes had to actively market themselves and manually reach out to coaches.

The client’s original vision included a vast ecosystem with a social media platform called "The Bullpen," NIL marketplaces, and global athlete reach. Through discovery, the team distilled this vision into a Minimum Viable Product (MVP) that prioritized the core data-driven "push" system and critical compliance features first.

• Automated Matching Engine: A core innovation that compares athlete performances to conference standards (top 16 or 24) and notifies coaches.

• Multi-Role User System: Role-specific dashboards for athletes, parents, college coaches, and admins.

• Recruitment Board: A streamlined pipeline for coaches to track athletes by priority levels (Gold, Silver, Bronze) and recruitment status.

• Age-Aware Messaging: A dynamic system that adjusts permissions as the athlete grows, ensuring COPPA compliance and parental monitoring.

• Verified Performance Tracking: Recording 30+ events with screenshot proof and coach verification workflows.

Technology Stack:
• Backend: Django 5.2 (Python 3.13)
• Frontend: TailwindCSS + PostCSS with custom typography and layout plugins
• Database: PostgreSQL-ready (production)
• Payment Processing: Stripe (handling 11 webhook event types for recurring billing)
• Data Sources: NCES API (27,000+ high schools) and College Scorecard API (6,400+ colleges)

Web Application Development:
• Built a responsive web application optimized for mobile browsers to ensure accessibility on the field.
• Developed a Performance Tracking module for 30+ track & field events, including personal/season best flagging.
• Integrated National Championships Scoring with real-time leaderboards and school team aggregation to drive engagement.

Backend & Infrastructure:
• Implemented Django REST API logic to support complex multi-tenant recruitment workflows.
• Developed a Conference Standards Database storing standards per event, gender, and division to enable accurate ranking estimation.
• Utilized Celery for asynchronous email support and Playwright for browser automation testing.

Key Features Implemented:
• Automated Matching: A proprietary algorithm where Rank 1 equals 100% match score, scaling down to 70% for Rank 24.
• COPPA Compliance: Parent registration delegation where children initiate the process and parents complete it via secure tokens.
• Stripe State Synchronization: Invoice webhooks with billing_reason flags to distinguish initial subscriptions, renewals, and plan changes.
• School Request Workflow: Admin-approved process for adding new schools to the database while maintaining data quality.

Product Outcomes:
• Launched a fully functional multi-tenant platform featuring 13 Django apps and 40+ database models.
• Delivered a real-time matching engine comparing athlete performance to conference standards.
• Implemented a scalable subscription system supporting both individual and team-based plans.

Technical Achievements:
• Successfully integrated federal APIs (NCES and College Scorecard) for comprehensive school coverage.
• Built a robust communication layer with age-aware transitions and NCAA compliance validation.
• Optimized performance with 20+ composite indexes for high-speed query execution.

Business Impact:
• Democratized Access: Reduced athlete entry costs from $2,000+/year to a $24 fee.
• Efficiency for Coaches: Eliminated manual searching by providing pre-qualified athlete metrics automatically.
• Market Innovation: Established the first platform to automate matching based on actual conference championship standards.
• Sustainable Growth: Created a model where coach subscriptions enable cheaper access for athletes.

• State Machine Design for Permissions: Managing age-based transitions (Under-13 to 18+) requires treating permissions as a formal state machine to handle edge cases like active message threads.

• Verification Cascades: Data integrity in a verification-heavy system requires cascading invalidation; if a coach is banned, all athletes they verified must be automatically reverted.

• Webhook Idempotency: Handling complex billing requires more than just completion events; managing renewals and failures across 11 event types necessitates strict idempotency.