Formula 1 driver comparison and analyzing tool.

An naive anomaly detection and data visualization tool for F1 on board telemetry data.

Finding explainable models to predict Formula 1 Qualifying Results

Machine learning model that predicts Formula 1 race results for the 2025 Shanghai Grand Prix using historical performance data, team strengths, and driver characteristics. Features data visualization, team change handling, and position progression forecasting.

Suzuka 2025 F1 race predictions by Otto.rentals — built for fans who love speed, stats, and bold visuals.

F1 data analysis & telemetry workstation — lap comparison, throttle/rpm charts, track visualization

A Set Of Tools To Analyse F1 Sessions, Powered By The Fast F1 Library

Jeddah 2025 F1 race predictions by Otto.rentals — built for fans who love speed, stats, and bold visuals.

A comprehensive command-line tool for analyzing Formula 1 race data using the FastF1 library.

Estimate Formula 1 qualifying results using ML

A comprehensive conglomeration of Formula-1 data in an organised representation.

Analyze F1 telemetry data on past sessions. View driver and constructor standings

Change my room's bulb colors based on F1 race leaders

Miami 2025 F1 race predictions by Otto.rentals — built for fans who love speed, stats, and bold visuals.

A Python-based GUI tool for visualizing F1 telemetry with multiple data representations.

Production-ready F1 strategy simulator with real-time telemetry analysis, pit optimization, and faster API responses via Redis caching.

TyreWearWiz is a F1 telemetry visualization project mainly focused on Type Degradation in Formula-1 Races. The Repository collects, visualizes Tyre degradation data which an X-factor in building Race Strategies

No description provided.

This project uses the FastF1 Python library to analyse Lewis Hamilton's race wins during the 2020 Formula 1 season.

Personal Project working with the FastF1 API and hoping to practice data representation and management. Hope to create a fully fleshed out UI that can help new Formula Fans to understand and read the data in a digestible and understandable manner.

The Briefing Room is an open source tool, that lets you analyse telemetry data from any Formula 1 session starting from the 2021 season. Built with Flask, data provided by the FastF1 package. 🏎️⚡️

Formula 1 data platform for analysis & community. Features a Chatbot, multiple API integrations (Ergast, FastF1), and a data science stack (pandas, scikit-learn, Plotly).

This project builds a machine learning model to predict F1 qualifying lap times using telemetry, weather, tyre, and driver performance data. The model is trained on data from 2021 to 2025 (up to Monaco GP) and makes predictions for the upcoming Spanish GP 2025.

Machine learning pipeline that predicts F1 podiums using practice and qualifying session data.

Formula Stats is a Django web app for exploring and visualising detailed Formula 1 data. It provides telemetry, lap times, tyre usage, and more with downloadable graphics. Ideal for F1 fans, analysts, and enthusiasts who want clean, insightful race visuals.

Analyzing Formula 1 data using the FastF1 library. This project explores race telemetry, driver performance, and strategic insights through data visualization and analysis.

Publish SignalR live data from fastf1 to a Kafka topic.

A REST API providing comprehensive Formula 1 statistics, built with Django and FastF1.

Attempts to predicts the best fantasy F1 team using 50 years of historical data.

🏎️ An AI-powered Formula 1 Strategy Engineer. Features a Llama 3.3 agent, physics-based simulations, and an automated ML pipeline that retrains itself every race week. Built with Streamlit, FastF1, and Groq.