SoccerPredictAI — End-to-End MLOps System¶
SoccerPredictAI is a production-style end-to-end MLOps platform for football match prediction. Raw web data is scraped, versioned, transformed into features, used to train a validated model, exposed behind a live REST API, and monitored — all with reproducible pipelines and explicit contracts.
This is a portfolio project demonstrating Applied ML / MLOps engineering at system level: not a notebook experiment, but a full-stack ML product designed for operational clarity.
System at a glance¶
flowchart LR
A[WhoScored.com] -->|Scraping| B[Airflow ETL]
B --> C[(PostgreSQL)]
C -->|Export| D[MinIO / S3]
D -->|DVC| E[Versioned Datasets]
E --> F[DVC ML Pipeline]
F --> G[MLflow Tracking & Registry]
G -->|Model URI| H[FastAPI Inference Service]
H -->|Sync / Async| I[Users / Streamlit UI]
H --> J[Prometheus /metrics]
J --> K[Grafana – planned]
E --> L[Evidently – planned]
H --> L
Solid arrows are operational. Grafana and Evidently are planned. See Implementation Status for the exact current state.
Where to go next¶
| Goal | Page |
|---|---|
| What is built and what is not | Implementation Status |
| Navigate by role or time budget | Review Guide |
| Reproduce the training pipeline locally | Quickstart |
| Prepare for an interview demo | Demo Guide |
| Understand the system design | Architecture Overview |
| Understand key design decisions | Architecture Trade-offs |