Slaviyy

Overview

Sports analytics engine that predicts match outcomes across 5 European football leagues. The platform collects live and historical match stats, calculates statistical probabilities using Poisson distributions, and presents betting insights and expected goals (xG) on an interactive dashboard.

Architecture & Implementation

The system uses two coordinated services: a Go backend that ingests fixture feeds and serves API routes, and a Python worker running mathematical modeling for expected goals and probability distributions. Match records and model outputs are stored in PostgreSQL, and the frontend is built in React.

Key Features & Results

• ▪Automated data ingestion pipeline in Go to normalize live fixture feeds and historical CSV records into PostgreSQL.
• ▪Statistical modeling: Python engine calculates Poisson distributions for expected goals (xG), clean sheets, and over/under markets.
• ▪React dashboard groups match forecasts into confidence tiers (High, Likely, Risky) with visual percentage reasoning.
• ▪Sub-second query responses on PostgreSQL across multi-season league fixtures.