Python for Motorsport Telemetry : Building Data Pipelines and Predictive Strategy Engines for Race Analytics
Overview
Reactive Publishing
Python for Motorsport Telemetry provides a comprehensive, hands-on framework for software engineers, data analysts, and motorsport enthusiasts looking to process, analyze, and visualize high-frequency vehicle dynamics data. Using practical Python tools, this guide walks you through the end-to-end architecture required to transform complex sensor outputs into actionable track insights.
What You Will Learn:
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Data Ingestion & Cleaning: Parse and normalize telemetry logs (CAN bus, GPS, and ECU outputs) using pandas and NumPy.
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Lap Time & Telemetry Analysis: Build custom algorithms to evaluate speed traces, throttle/brake inputs, line selection, and driver consistency.
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Predictive Strategy Modeling: Model tire degradation, fuel burn rates, and undercut/overcut scenarios to simulate race dynamics.
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Pipeline Architecture: Develop efficient, scalable data pipelines capable of processing continuous stream data for real-time decision-making.
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Visualization Frameworks: Create clear, interactive trace overlays and dash displays using matplotlib and plotly for rapid telemetry feedback.
Whether you are designing custom analysis tools for a race team or engineering software for telemetry simulation, this book offers the practical code structures and domain logic required to build professional-grade motorsport data systems.
This item is Non-Returnable
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Details
- ISBN-13: 9798191400983
- ISBN-10: 9798191400983
- Publisher: Independently Published
- Publish Date: August 2026
- Dimensions: 9 x 6 x 1.7 inches
- Shipping Weight: 1.79 pounds
- Page Count: 686
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