Developer Builds AI Baseball Simulation Engine with Claude Code in Two Weeks
Project Overview
A developer built a complete AI-powered baseball simulation system using Claude Code over two weeks. The project includes a plate-appearance-level simulation engine with real player statistics sourced from FanGraphs, 30 distinct AI manager personalities (approximately 800 words each) based on real MLB managers, and a full content pipeline that generates game recaps, postgame press conferences, and analysis.
Technical Implementation
The system was developed using Claude Code via a Framework laptop running Omarchy. Sonnet manages all 30 MLB teams within the simulation. The developer implemented smart query gating to reduce API calls from approximately 150 per game to 25-30, significantly optimizing costs. A Discord bot broadcasts 15 games simultaneously with a live scoreboard, and the entire project includes a 21-page website built with Astro 5 and Tailwind v4.
Cost and Components
Total development cost was $50 in API credits. The developer noted that Opus was quite expensive and was used for one aspect of the simulation, with caching helping to keep its costs down. The project consists of multiple components: a simulation engine, AI manager layer, content pipeline, Discord bot, and website. Audio podcasts are generated using an ElevenLabs clone of the developer's voice.
Project Context
The developer describes themselves as a professional writer, not an engineer, and built this as a non-monetized project that actually costs them money to run. The site is available at deepdugout.com. This demonstrates how AI coding assistants can enable rapid development of complex systems even for those without traditional engineering backgrounds.
📖 Read the full source: r/ClaudeAI
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