A repository of Formula 1™ circuits in GeoJSON format.

Unofficial Android and web app for Formula 1 and Formula E fans!

F1 Game Telemetry Client written in Go (no dependency)

Formula 1 App is a simple app developed with Xamarin to display information about Formula 1

Helps Assetto Corsa's F1 simulation be more in line with real life.

Get the F1 Team Radio conversations from the latest GP and RaceControl messages also. It also provides list of Drivers participating and information about them.

🏎️ A curated collection of high-quality Formula 1 and motorsport resources — APIs, datasets, telemetry tools, visualization, sim racing, and learning materials.

🏎 Formula1 CLI

Open-source multi-agent AI platform for Formula 1 race replay, strategy simulation, and explainable race strategy recommendations. (work in progress, PMV in legacy branch)

Singer tap for F1 data

2021 Formula One World Championship teams GRUB themes

NodeJS implementation to get a historical record of F1 data from Ergast Developer API.

An interactive web application that allows Formula 1 fans to create and share their predictions for the latest F1 season. Users can drag and drop drivers into grid positions for each race, track points, and share their predictions with others.

Emotional Chatbot AI Question & Answer Text-Generation Knowledge-based on Formula 1 sport.

Um site feito com NextJS para acompanhar pilotos e corridas da Fórmula 1

F1 Speedtrap speeds for Sector 1/2/Finish line and Longest Straight

Compare any two F1 drivers across 70+ years of racing — career stats, head-to-head results, championship timelines, and constructor histories. Then use the "What If?" mode to recalculate every career under any scoring system from 1950 to today. Built with React, TypeScript, Recharts, and Framer Motion. Dark mode, mobile-ready, shareable URLs.

An interactive F1 engineering workbench built with Streamlit and Bayesian Optimization. Designed for racing fans, data scientists, and engineers to explore optimal car setups by balancing lap time, tire wear, and handling performance.

This a project which aimed at predicting whether a Formula 1 driver will finish on the podium (top 3) using historical data, advanced feature engineering, and machine learning.

Physics-informed F1 lap simulation. Six coupled ODEs integrated along arc length: velocity, slip angle, ERS state of charge, fuel mass, tyre temperature, and tyre wear. Gaussian thermal grip window, spatial aero mode filter, and regen/deploy gate logic. No ML. No proprietary data. One Python file runs the full lap.