I think this book is perhaps best conceptualized as a follow-up or modernization of Darrell Huff's classic How To Lie With Statistics. That book, since it was first recommended to me by one of my math professors in college, has long been one of my favorites and represents a true triumph when it comes to communicating about technical mathematical ideas to a general readership. It's also many decades old and its examples, while still engaging and fascinating, are of less relevance to modern readers.
By his own admission, part of Best's goal with Stat-Spotting was to write a similar work with modern examples. In that goal, he largely succeeded. I still maintain that How to Lie With Statistics is a superior work and does a better job of helping the reader to really understand statistical thinking. However, Best's modern examples in Stat-Spotting will help modern readers understand the relevance of these ideas to reports they read every day in the newspaper.
In fact, I was surprised by the high quality of the examples presented. Because a lot of the examples, being related to modern issues, contain controversial ideas, I feared that they might be presented in a biased manner which at worst would cloud the statistical arguments and even at best, if the stats were all correct, would alienate a large portion of the potential readership. However, Best has done an admirable job of avoiding such political landmines. Different sides of controversial issues are presented along with their own supporting statistics, and the book openly discusses why such statistics--on both sides--may be unreliable, but makes no value judgments or final conclusions. Instead, the author merely equips the reader with the tools to more carefully evaluate numerical data, whether presented by one's own side or the opposition.
Where the book suffers a bit is in its treatment of statistics themselves. Everything in the book is focused on how statistics are reported, with very little consideration given to the mathematics. That's not to say I expect a book like this to provide detailed technical descriptions of statistical theory. However, it would have been incredibly useful to the reader if the author had included, even as an appendix, some discussions regarding the different kinds of statistical tests used, when they are or aren't appropriate, and how readers should interpret such matters as statistical significance or effect sizes.
All in all, while it's not the best book on statistics I've ever read, Stat-Spotting is an excellent guide to more mathematically literate consumption of information or news media, and for that I think the author should be applauded.