19 Good Motorsports Books

List of Good Motorsports Books

If you are struggling to work out the good motorsports books to buy, then here are my suggestions. Below you will find a curated list of all the good motorsports-y type books I have. Click on any image to get the price and peoples reviews. They are affiliate links.

Most are technical, although the Adrian Newey one is really an autobiography.

These motorsports books range from helping you with your data analysis to understanding your race car setup. A couple are very maths heavy, race car engineering and design books I have used professionally. There are also a couple with good practical tips on running a race car at the track. Some are definitely old (!) but I feel you would still find them relevant.

If you get any and like them, or if you think I have missed any good motorsports books, be sure to sign up and let me know.

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The Science of Vehicle Dynamics, Massimo Guiggiani. Recommended text for some courses. Has good reputation although not read completely myself.

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How to Build a Car. Adrian Newey’s autobiography. Includes loads of fascinating tech insights into the cars he has designed. Ideas for your car?

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Making Sense of Squiggly Lines. Chris Brown. Modern book on how to interpret consumer level data analysis traces. Often highly recommended.

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Race Car Vehicle Dynamics. Milliken. The seminal text on how to design, develop and setup a car suspension system. For the engineers. Seriously.

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Race Car Aerodynamics. Katz. Introduction to race car aerodynamics and how race teams apply these principals to go faster.

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Tune to Win. Smith. Regularly recommended text on running a racing car in competition. Not for all but well written. You’ll learn something.

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Speed Secrets (series of books.) I’m a big Ross Bentley fan. Listen to him on my podcast and buy his stuff. I could put all his books here as they are great.

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Competition Car Data Logging. Good practical guide to race car data logging. A bit out dated and I struggle with the style. Many like it.

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A Practical Guide to Race Car Data Analysis. Knox. Another older book but still well worth having on the shelf. Often referred too. Ideas have evolved but good to have.

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Vehicle Aerodynamics – Testing, Modification & Development. Edgar. Very practical book on how to understand and improve aero. Listen to him on the podcast.

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Analysis Techniques for Racecar Data Acquisition. Jorge Segers seminal book on how to interpret race car data analysis. Good intermediate to advanced book. Listen to him on the podcast.

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The Multibody Systems Approach to Vehicle Dynamics. Had the pleasure of Mike teach me simulation at Uni. Damian is one of my best podcast guests. Their book is, unsurprisingly, very very good.

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Race Car Design. Derek Steward. Motorsports book on how to design a racing car. Includes many simple approaches for better setup.

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Smith’s Fundamentals of Motorsport Engineering. Smith. Often a recommended text on college courses. Focused on design side.

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Driving on the Edge. Krumm. A great insight into the mind of a pro racing driver. How they approach their career, data and team mates. Good.

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Fundamentals of Vehicle Dynamics. Gillespe Another engineers engineering book. This is what pro vehicle dynamics engineers use daily. For those that like maths.

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Chassis Design Olley. Rarely seen book. This is what the Milliken guys studied used before they wrote their book. Collection of papers. Engineers book.

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Hands-on Race Car Engineer. Looks at the practical side of prep’ing and running a racing car. Aim is to ensure you are always learning. Get organised to win.

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Data Power. Fey. Older book. You might struggle to find it. It has a good reputation and included here for completeness. Others better.

Further Reading For FREE 😉

Race cars are all about tyres –> https://www.yourdatadriven.com/guide-to-interpreting-tyre-temperatures-in-motorsports/

Take the mystery out of Gear Ratio selection –> https://www.yourdatadriven.com/how-to-use-the-gearing-optimisation-spreadsheet/

How to measure the impossible –> https://www.yourdatadriven.com/how-to-measure-the-impossible-and-the-inferred-metric/

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