I'd planned, and even drafted, a long review for this book, but decided not to post that. Instead I'm posting this short note.

Curve Ball is a look at sabermetrics by a pair of professional statisticians. It begins by discussing how statisticians view numbers and analysis, then moves to baseball's. The authors are apparently familiar with every important sabermetrician, including the commonly-cited sabermetric predecessors, and with many (perhaps all) professional statisticians who study baseball. Some of the book's chapters are overviews, while others examine specific topics.

The chapters I found most interesting were a series about modeling baseball offenses. On the whole, these guys give the leading sabermetricians good marks; in particular, Bill James' Runs Created and Pete Palmer's Linear Weights are given high accolades.

The book's enjoyable if you've some background in academic statistics, but it's likely difficult reading if you've not encountered that notation and vocabulary. I worked my way through the discussions, but was rummaging through four-decade-old memories from time to time. It's certainly an essential book if you're seriously interested in serious baseball analysis.






This review has also been published on a dabbler's journal.
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As an introduction into sabrmetrics, this ranks pretty high. It also manages to introduce a lot of important statistical concepts through graphs and monte carlo-type simulations—neither of which require much of an advanced math background. ( )