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Sandlot Stats: Learning Statistics with Baseball

MAA Review

If this had been the textbook for a basic statistics course that I took as a student, I might have remembered that course forever as the best class I ever had. Generally speaking, the content is that of the standard basic course in statistics (very strong in descriptive and weak in inferential), but the actual data is derived from major league baseball. All of the data is from the hitting side of the game and covers a great deal of history as the great hitters are used as data sources.

Rothman delves beyond what have for decades been the standard statistics used to base player performance: batting average, slugging percentage and the numbers of hits, home runs and runs batted in. He moves into the new baseball science of Sabermetrics, the equivalent of data mining in baseball. Questions such as the probability of a 56 game hitting streak and a player hitting 0.400 for a season are used to solidify the topics in the mind of the reader.

I, however, am a lifelong baseball fan, so all of the raw data, baseball history and most of the descriptive statistics were very familiar. Given my experience with the fragility of the mathematical egos of many students that take (often required) statistics and the reality that most are not solid baseball fans, I question whether this book could be used as a text in a standard college course in statistics. Yet it would be the best possible choice for a class where the student body is pre-screened as being baseball fans. There is no question that those people would have the educational time of their lives and that they would learn something.

Charles Ashbacher splits his time between consulting with industry in projects involving math and computers, teaching college classes and co-editing The Journal of Recreational Mathematics. In his spare time, he reads about these things and helps his daughter in her lawn care business.

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