Designing Schemas for Sports APIs: What I Learned Building Football Player Data Systems
The article discusses the challenges of designing schemas for sports APIs, particularly for football player data systems. It highlights the difficulties of managing messy sports data and the importance of creating a scalable and predictable schema. The author shares insights on transitioning from flat structures to nested structures to improve frontend reusability and versioning.
- ▪The initial flat player object schema led to organization issues and repetitive frontend components.
- ▪Switching to nested structures improved UI predictability and made versioning easier.
- ▪Handling multiple versions of players as immutable entities simplified caching and querying.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3826374) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Alex Posted on May 19 Designing Schemas for Sports APIs: What I Learned Building Football Player Data Systems #api #football Over the past year I’ve been building football-related tools like: player comparison apps squad builders analytics dashboards stat visualizations And I kept running into the same issue: Sports data is messy. Not because the data itself is complicated — but because modeling it cleanly for developers is surprisingly difficult.
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