====== How To Analyze SimRacing Car Telemetry Data ====== "**The cornerstone of telemetry analysis lies in understanding //car dynamics//, which refers to the //physics and handling of a car//**" Telemetry data analysis is a crucial skill for racing engineers, drivers, and enthusiasts alike. It offers insights into a vehicle's performance and helps optimize setups for better results. Below, you will find a short guide on how to analyze racing car telemetry data, along with useful resources and tips to enhance your understanding. ===== Understanding Car Dynamics ===== __The cornerstone of telemetry analysis lies in understanding **car dynamics**, which refers to the //physics and handling of a car//__. When delving into telemetry data, it's essential to comprehend how variables such as speed, acceleration, tire pressure, and suspension settings relate to the car's behavior on the track. ==== Key Concepts to Understand ==== * **Aerodynamics**: Understanding how downforce and drag affect speed and handling. * **Suspension Dynamics**: How the car's suspension affects wheel contact and stability. * **Tire Behavior**: The importance of tire pressure, temperature, and wear in performance. * **Engine Performance**: Analyzing power output, gear ratios, and fuel efficiency. Once you grasp these dynamics, reading telemetry data becomes intuitive, allowing you to make informed decisions about changes to vehicle setup and driving strategies. ===== Steps to Analyze Telemetry Data ===== - **Gather Telemetry Data**: Use [[https://simracingtelemetry.com/|Sim Racing Telemetry]] to [[manual:recording|collect]] data during race events or practice sessions. This data will typically include speed, throttle position, braking, steering angle, and more. - **Visualize the Data**: Employ visual plots of telemetry data (like [[manual:lap-charts]], [[manual:lap-view]], etc) and [[manual:lap-stats|mathematical statistics]] to help in identifying trends, correlations, or anomalies in the vehicle's behavior. - **Identify Key Metrics**: Focus on specific areas such as //braking points//, //throttle application//, //cornering speeds//, and //gear usage//. Understanding these metrics will help you decipher the car's performance. - **Compare Data**: use the [[manual:comparison-mode]] to compare telemetry data from different laps or sessions and uncover what changes worked best. Analyzing data from better racers can also provide benchmarks to strive for (see [[manual:sharing-data|]]). - **Adjust Setup**: Based on the insights from your analysis, make calculated adjustments to the car’s setup. This may involve changes to the suspension, tire pressure, aerodynamics, or driving strategy. ===== Engaging with the Community ===== Engaging with a community of like-minded individuals can aid in improving your skills and understanding. You can join discussions, ask questions, and share knowledge with others interested in telemetry data analysis. **Sim Racing Telemetry Community**: Join the [[https://www.reddit.com/r/SimRacingTelemetry/|r/SimRacingTelemetry sub-Reddit]] to discuss telemetry in sim racing games. It hosts useful links and videos. ===== Recommended Resources ===== For further reading and skill enhancement, explore these resources: - [[https://scarbsf1.wordpress.com/2011/08/18/telemetry-and-data-analysis-introduction/|Telemetry and Data Analysis Introduction]], by Brian Jee, 2011-08-18. - [[http://racingcardynamics.com/speed-data/|How Fast Are You? The Secrets of Speed Data Interpretation]], by Rodrigo de Oliveira Santos, 2015-03-12. ==== Books on Car Dynamics ==== - [[http://a.co/d/dQuhJIi|Going Nowhere Fast In Assetto Corsa: Race Driving On A Simulator]], by Amen Zwa, 2020-10-20. - [[http://a.co/d/8RTKsDg|Tune to Win]], by Carroll Smith, 2004. Conclusion Analyzing racing car telemetry data is a multi-faceted process that combines a deep understanding of car dynamics with data literacy skills. By leveraging available resources and engaging with like-minded communities, enthusiasts can significantly enhance their understanding and application of telemetry data. Start with the basics, use the recommended resources, and keep experimenting to achieve optimal performance on the track.