Overview
Built a repeatable tournament system to validate bot behavior, run games, track results, and produce structured outputs for comparison across multiple chess agents.
Problem
What started as a competition among friends turned into a useful exercise in system design, automation, game logic, and performance tracking.
System Architecture
- Built a Python-based tournament system for multiple chess bots.
- Implemented move validation, timing rules, and result tracking.
- Added PGN logging and structured JSON summaries for tournament outputs.
- Designed the framework to test different decision-making strategies.
What I Built
- Bot execution and tournament orchestration flow
- Validation logic for legal moves and timing rules
- Match result capture and repeatable reporting
- Structured outputs for bot-to-bot comparison
Tools
- Python
- python-chess
- validation logic
- PGN logging
- JSON summaries
- tournament automation
Business Value
The project shows my ability to build structured systems, enforce rules, and analyze performance in competitive decision-making environments.
What I Learned
This project reinforced disciplined systems thinking: define rules clearly, validate every edge case, and make results easy to compare across repeated runs.
Next Steps
Future iterations can add richer analytics, more tournament formats, and stronger benchmarking across different bot strategies.
Limitations
The framework prioritizes orchestration and reporting over advanced chess-engine evaluation. The case study focuses on systems discipline rather than chess-engine research depth.