Building a Fantasy Baseball Analytics App with Claude Code: A Law Student's Experience

A Navy veteran and law student with a 2017 computer science degree who hadn't touched code since graduation built a complete fantasy baseball analytics iOS app called Ball Knower using Claude Code for implementation while making all product and domain decisions. The app is live on the App Store and was developed during the student's final year of law school.

What Was Built

Ball Knower is a fantasy baseball analytics app that includes:

• 1,313 MLB player profiles with Statcast percentile bars (color-coded bars from Baseball Savant)
• Daily streaming pitcher picks scored 0-100
• Keep-Trade-Cut dynasty rankings with ELO scoring
• 1,241 MLB players + 72 FanGraphs prospects
• 87 distinct metrics tracked per player

Technical Stack

Frontend: SwiftUI (iOS 17+), Swift Charts, StoreKit 2

Backend: Python 3.12, FastAPI, SQLAlchemy async, PostgreSQL, Redis, APScheduler

Infrastructure: Single DigitalOcean droplet, Docker

Data Sources: 30 scheduled jobs pulling from MLB Stats API, Baseball Savant via pybaseball, ESPN RSS, The Odds API, and Open-Meteo weather

Where Claude Code Excelled

• Wired a FastAPI dependency injection chain to an async SQLAlchemy session to a Redis cache layer in minutes (would have taken days from documentation alone)
• Debugged an async race condition in the subscription validation flow where the refresh token coordinator and StoreKit 2 listener were conflicting
• Identified the problem and wrote an actor-based fix after being described the symptoms
• Wrote approximately 70% of the raw lines of code

Where Claude Code Fell Short

• Mapped 85% of data source columns correctly, but 15% returned nil silently with no errors or crashes
• Missed column name mismatches (e.g., pybaseball returns brl_percent while database column was barrel_pct)
• Confidently generated code requesting App Tracking Transparency permission for non-personalized ads, causing Apple to reject the build
• Generated SwiftUI modifier chains that compiled but rendered incorrectly on edge cases
• Used deprecated API patterns without mentioning they were deprecated

Developer's Role

The developer wrote or corrected the remaining 30% of code, which included:

• Scoring algorithm weights
• Cache invalidation logic
• Subscription flow
• Data column mappings
• App Store compliance
• Domain-specific decisions (dome stadiums don't have wind, spring training stats shouldn't weight equally, Baseball Savant's percentile API requires gap-fill logic for non-qualified players)

Development Metrics

• 300+ development hours across one semester
• 30 automated cron jobs running nightly starting 2:25 AM ET
• 9 external data sources synced daily
• 2 App Store rejections before acceptance (EULA labeling + unnecessary ATT permission)
• Break-even: 13 subscribers at $3.99/month