Description
A look at baseball data from a statistical modeling perspective! There is a fascination among baseball fans and the media to collect data on every imaginable event during a baseball game and this book addresses a number of questions that are of interest to many baseball fans. These include how to rate players, predict the outcome of a game or the attainment of an achievement, making sense of situational data, and deciding the most valuable players in the World Series. Aimed at a general audience, the text does not assume any prior background in probability or statistics, although a knowledge of high school abgebra will be helpful.
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In this lively and thought-provoking look at the numbers and the game, Jim Albert and Jay Bennett examine just what we learn, and just what we think we learn, from baseball statistics. The authors consider the key questions every serious fan obsesses about. By incorporating the seldom-used statistical techniques of probability, the authors come to some original and surprising conclusions: It turns out, for example, that the phenomenon of "streakiness" is measurable and can serve as a very useful predictor of performance. Conversely, they find that a lot of situational statistics (home versus away games, play on artificial turf versus grass) are, statistically speaking, little more than "noise".
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