schmidiiii/sim-racing-engineer — explained in plain English
Analysis updated 2026-05-18
Compare braking points and corner speeds across multiple iRacing laps.
Get AI coaching feedback pointing out specific corners where you lost time.
Track lap consistency across a race session.
Compare car setups used in different iRacing sessions.
| schmidiiii/sim-racing-engineer | 0xradioac7iv/tempfs | 52191314/web-agent-proxy-sdk | |
|---|---|---|---|
| Stars | 0 | 0 | 0 |
| Language | TypeScript | TypeScript | TypeScript |
| Setup difficulty | easy | moderate | moderate |
| Complexity | 2/5 | 3/5 | 4/5 |
| Audience | general | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Windows only, single installer with no Python or Node.js setup required, AI coaching needs either a free local Ollama model or an API key.
Sim Racing Engineer is a Windows desktop app for analyzing telemetry data recorded by the racing simulator iRacing. You load the session files iRacing saves after each drive, and the app shows you overlaid charts comparing multiple laps at once, covering throttle, braking, speed, steering, tire temperature, and many other measurements, so you can see exactly where you gained or lost time. The app automatically detects braking zones and corners on the track and compares your entry speed and braking point across laps, showing whether you braked earlier or later than a reference lap. It also draws a live track map generated from GPS data that highlights whichever measurement you are viewing, such as throttle or gear, and a consistency score that tells you how repeatable your lap times are across a session. One of the main features is an AI coach built into the app that reviews your data and gives direct feedback about specific corners and laps, rather than generic advice. You can choose which AI service powers this: Ollama, which runs a language model for free on your own computer, or a paid API from OpenAI or Google Gemini if you would rather use a cloud model. The coaching works in ten different languages. The app also reads the car setup saved inside each session file, so you can compare setups between sessions, and it includes a shortcut that opens a YouTube search for onboard videos of your specific car and track combination. To use it, you download a single Windows installer, no Python or Node.js setup is required, and the app updates itself automatically when new versions come out. It is built with a Rust backend using Tauri and a React and TypeScript frontend.
A Windows app that analyzes iRacing telemetry and gives AI powered coaching feedback on your driving.
Mainly TypeScript. The stack also includes TypeScript, React, Rust.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly general.
This repo across BitVibe Labs
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