Average Reviews:
(More customer reviews)Jim Albert and Jay Bennett share two traits that make them the perfect authors for this type of book (1) they are both baseball fans who know the game and have seen many games and much statistics from many angles and (2) they are both professional statisticians who understand probability and the subtle aspects that chance can have on statistics. By being professional statisticians they also know how sophisticated statistical techniques can add to ones ability to seriously address questions of strategy and comparison of player performance. That is what they accomplish in this book, teaching some basic probability and statistics along the way.
They also make it very interesting to the baseball fan by raising interesting baseball questions related to players that the fans relate to, namely the stars that the fans follow and the great clutch hits and clutch defensive plays that we baseball fans have imprinted in our memories, like Mazeroski's game winning home run in the 1960 World Series, or Willie Mays' famous over the shoulder catch of Vic Wertz's long fly ball in the 1954 series, or Bobby Thompson home run that won the 1951 playoffs for the Giants.
In the very beginning Albert and Bennett distinguish themselves from the sports statisticians that are hired by the teams. The sports statisticians collect the data and present it in various ways. However, this is merely exploratory data analysis. Albert and Bennett point out that a numerical difference in a hitting statistic such as on base percentage between Chuck Knoblauch and Kenny Lofton may be a real difference in ability but may also be a small enough difference to be merely due to chance. Finding ways to analyze the baseball data to make probabilistic inferences like answering the question of whether Lofton is better at getting on base than Knoblauch is the focus of what professional statisticians do and is the theme of the book.
In the course of reading the book you will learn many things about baseball. Some may agree with previous notions and some will be surprises. You will learn about the massive amount of major league baseball data available, about SABR a society for baseball research and more. You will be opened up to the hinden world of professional statistics where probability models have been used for over a century to handle military, engineering, energy, environmental, agricultural and medical problems. These same tools in recent years have been used to handle baseball questions also.
They start with simple table top baseball games like All Star Baseball to introduce concepts. They then move on to baseball data and probability. Then they look at statistical questions, situational effects in Chapter 4, hot hitting in Chapter 5, methods of measuring offensive performance in Chapter 6, more sophisticated measures in Chapter 7, simulation models in Chapter 8, measures of clutch play and team value in Chapter 9, ways to predict performance in Chapter 10, analyzing World Series results in Chapter 11 and final comments in Chapter 12.
This is a great book for any one who loves baseball and baseball statistics. It also is a great way to learn and become interested in the techniques of the professional statistician.
For statisticians that teach statistics, it provides a wealth of interesting examples to help illustrate important statistical concepts in basic or even advanced courses, including the value of Bayesian methods, the need for overdispersion models (e.g. batting averages) and the value of linear and nonlinear prediction models.
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