A Practical Guide to Race Car Data Analysis

Christmas gift for my son. He loved it, just as described.

Excellent book if you want to learn some theory and math behind racing. I used it to create some programs for a family racer who was not happy with the regular output from his racing programs.

Easy to read, simple to understand, immediate to apply.The topic isn't simple to explain, nonetheless the author has done a wonderful job taking the reader through all the main topics using as example the most common data logging softwares. You'll want to read it more than once and use it as a quick reference guide too.

One of the best so far. Easy to read and a lot of questions answered and explained very clearly. Real life data, reasons, solutions, options , tips, etc,....Perfect for first timers , drivers or like me, technicians who run and prep cars on there own.

This is an excellent book that really helps to understand how to look at things that are the most useful.

I thoroughly enjoyed reading A Practical Guide to Race Car Data Analysis by Bob Knox. The author does a great job breaking down data, such as, determining car health, diagnosing handling issues (whether set up issues or driver induced), and driver characteristics. Real examples with color and annotated figures are provided throughout the book. A reasonable number of clearly explained math formulas are also included. In fact, the author provides these math channels in the formats native to a number of data systems (AIM, MoTec, Pi, and STACK). If you don't own one of these data systems, that's ok as the formulas are clearly written so they can be written in applicable formats for other data systems.Two particular strengths of this book are the discussions on damper potentiometers and some recommended templates for interpreting data. The topic of damper potentiometers isn't covered in many of the books I have found. The author spends an entire chapter (around 25-30 pages) on interpreting damper data: displacement plots (are the dampers hitting their bumpstops), velocity histograms, ride frequency, roll/pitch, determining downforce, and test methods to generate aero maps. The only other book that I have found which covers this material in any significant detail is the book by Jorge Segers. Jorge's books is quite mathematical and likely has a different target audience.Bob Knox's book also includes some standardized templates for interpreting data. He suggests how to organize x-y plots, time/distance graphs, etc into logical groups. For instance, an example of a pressure report shows how a page could be organized to show x-y plots of lateral acceleration vs. oil pressure, longitudinal acceleration vs. oil pressure, lateral acceleration vs. fuel pressure, track maps, as well as min/max/average tables on a single page so trends can be quickly determined yet have details immediately available. In addition, a detailed data analysis outline is provided which will give the reader a list of things to look for whenever a new set of data is acquired.There are around half a dozen books currently available on race car data acquisition. I have read nearly all of them and the three in particular that I and would recommend are:1) This book, which is a great introductory to medium level book on the topic.2) Competition Car Data Logging Manual by Graham Templeman: Another introductory to medium level book with lots of great examples and color plots. Dampers aren't really covered.3) Analysis Techniques for Racecar Data Acquisition by Jorge Segers: Another great book with LOTS of details and formulas targeted more towards engineers. Great details, including formula derivations, are provided.I have yet to read Making Sense of Squiggly Lines by Christopher Brown. That is next on my reading list.

This book was recommended to me by Roger Caddell from AiM when I took one of his training classes and I gotta say I wasn't disappointed.As the title of book indicates, this book is about cars and not motorcycles. As a motorcycle club racer this unfortunately the state of things as there are no books on doing motorcycle data analysis. That said, most of the data here translates over, but there are exceptions of course. Bikes and cars experience under/oversteer very differently for example. I'd still recommend this book for motorcycle data analysis, but be sure to also read Andrew Trevitt's website "DataMC" as a supplement.The book covers AiM, MoTeC, Pi and Stack and probably has over a hundred different math channel formulas you can can use for your analysis. That said, I'd classify this as an intro to intermediate book because it covers a bunch of different areas of data analysis, but doesn't go really deep into any of them. Some topics like suspension analysis are probably a book all to themselves, so that's not too surprising. But it does go deep enough into every topic so you can start asking intelligent questions, extract some useful and ACTIONABLE information to go faster. Reading this book should give you a solid foundation for more advanced books/topics.Bob's writing style is clear and to the point. The layout of the book makes it easy to read and the color photos are awesome. I do wish the margins were bigger so that it was easier to write my own notes down though.Overall, I'd recommend this book over "Making Sense of Squiggly Lines" even though this book is twice the cost. It covers more topics (like suspension analysis) and more importantly provides a lot more math channels that you can add to your own data to learn more about what you and the vehicle are doing out on the track.

Very informative. Good read if you want to go fast