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F1 Race Performance Analytics

Project Overview

End-to-end data analytics project analysing 75 years of Formula 1 race data (1950–2024) to uncover performance patterns across drivers, constructors, and championship competitiveness.

Business Questions

  1. How does starting grid position translate to race wins across eras?
  2. Which constructors have the highest mechanical DNF rates?
  3. Which drivers consistently overperform their grid position?
  4. How has championship competitiveness changed by decade?

Key Findings

  • 79% of all race wins come from the top 3 grid positions
  • Pole position converts to victory 42% of the time
  • Mercedes leads modern reliability at 90% finish rate
  • F1 reliability improved from 42% finish rate (1980) to 89% (2024)
  • Lewis Hamilton leads the modern era with 105 wins and 202 podiums

Tech Stack

Layer Tool
Cloud Warehouse Snowflake
SQL Analytics Snowflake Worksheets
Visualisation Power BI Desktop
Publishing Power BI Service
AI Assistance Claude API
Documentation Notion

Data Source

Ergast Motor Racing Database via Kaggle — 14 tables, static snapshot covering 1950–2024.

Dashboard

View live Power BI dashboard →

Presentation

Download PDF ↓

Documentation

View Notion Docs →

Project Structure

  • /sql — All SQL scripts for setup, table creation, and analytics views
  • /powerbi — Power BI Desktop file (.pbix)
  • /presentation — Final stakeholder presentation (.pptx)
  • /docs — Data dictionary and project documentation

About

End-to-end F1 data analytics project using Snowflake, SQL, Power BI, and AI-assisted insights

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