Full-stack software engineer specializing in Rust, IoT, and real-time data systems.
I build production systems end-to-endβfrom backend services and data pipelines to hardware-integrated applications and user-facing tools.
- Build full-stack applications (React, Node.js, PostgreSQL, Docker)
- Develop high-performance systems in Rust (multi-threading, simulation, optimization)
- Design IoT and real-time data platforms using AWS and edge devices
- Create sports probability models for European football using real-world data
Iβve developed applications that model football match outcomes using probabilistic and statistical methods, including:
- Match outcome prediction (win/draw/loss probabilities)
- Performance modeling using historical match data
- Data pipelines for ingesting and processing league data
- Tools for analyzing trends and identifying value opportunities
π See: EnglishPremierLeaguePredictions
Languages: Rust, JavaScript (Node.js), C#, SQL
Frontend: React, HTML, CSS
Backend: REST APIs, data modeling, system design
Cloud: AWS (Lambda, DynamoDB, S3)
Other: Docker, IoT (Raspberry Pi), CNC systems, G-code
- β½ Football Probability Models β predictive modeling & data pipelines
- βοΈ CNC Simulation (Rust) β high-performance simulation engine
- π IoT Monitoring System β real-time data collection & analytics
- π¨ Cupertino Rounded Corners β UI package (top 20% on pub.dev)
- Data-driven platforms
- IoT & real-time systems
- Performance-critical software
- Sports analytics & decision systems
- GitHub: https://github.com/monksc
A sports analytics project that models football (soccer) match outcomes using probabilistic and machine learning techniques.

