Curve Ball: Baseball, Statistics, and the Role of Chance in the Game (Hardcover)

by James Albert (Author), Jay M. Bennett (Author) "Two boys stared out the window at the rain-swept streets..." (more)
Key Phrases: World Series, American League, National League (more...)

Editorial Reviews

From Publishers Weekly
Baseball fans love statistics. Box scores, batting averages and pitching records are published on the backs of baseball cards and in books, revised daily on Web sites and newspapers and quoted easily and authoritatively by sportscasters and in casual conversation. But how to make sense of all this information? Curveball: Baseball, Statistics, and the Role of Chance in the Game by Jim Albert, professor of mathematics and statistics at Bowling Green State University, and Jay Bennett, principal scientist with Telecordia Technologies both former chairs of the sports section of the American Statistical Association and lifelong Philadelphia Phillies fans has 273 scary-looking charts and tables (and some bothersome formulas), but will be welcomed by many fans seeking to better understand the numbers.

Copyright 2001 Cahners Business Information, Inc.

From Library Journal
Baseball is a fascinating game for the statistical analyst. On the surface it appears so simple and limited. But the more closely one studies the game, the more, it seems, there is to know. The coauthors are both former chairs of the American Statistical Association Section on Statistics in Sports and fans of the Philadelphia Phillies. Though there are many other books about baseball statistics, these authors are particularly sophisticated statisticians. As they illuminate baseball, they demonstrate the power of college-level statistics to interpret the numbers. Starting with simplified board game simulations, the authors show how to model player performance or predict game outcomes. Then they use actual statistics to make the models more complex and true to life. Part of the fun is that statistical results can be counterintuitive. Does the best team always win the World Series? Not necessarily. No matter how talented other teams are, the element of chance means that Phillies fans can still hope for victory. Recommended for public and academic libraries, especially in cities with a major league baseball team. Amy Brunvand, Univ. of Utah Lib., Salt Lake City
Copyright 2001 Reed Business Information, Inc.

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Product Details

• Hardcover: 350 pages
• Publisher: Copernicus/Springer-Verlag (June 8, 2001)
• Language: English
• ISBN-10: 0387988165
• ISBN-13: 978-0387988160
• Product Dimensions: 9.3 x 5.7 x 1.2 inches
• Shipping Weight: 1.6 pounds
• Average Customer Review: 4.2 out of 5 stars See all reviews (13 customer reviews)
• Amazon.com Sales Rank: #1,158,884 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

53 of 57 people found the following review helpful:

5.0 out of 5 stars baseball statistics as studied by professional statisticians, July 7, 2001

By	Michael R. Chernick "statman13" (Malvern, PA) - See all my reviews (REAL NAME)

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.

26 of 26 people found the following review helpful:

5.0 out of 5 stars baseball statistics interpreted by professional statisticians, January 23, 2008

By	Michael R. Chernick "statman31147" (Holland PA) - See all my reviews (REAL NAME)

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.

24 of 27 people found the following review helpful:

3.0 out of 5 stars Disappointing, September 25, 2001

By	Mark (Ottawa, Canada) - See all my reviews

This is a book that I was excited to buy but unfortunately I did not enjoy it as much as I had hoped for. The two main reasons for this are 1) the lack of major insights and 2) the huge quantity of typos (I stopped counting after around 20). The copy editor for this did an absolutely terrible job, I'm afraid to report (writing this guarantees a typo somewhere in my review :) ). Some of the players' names are spelled incorrectly, and some of the numbers in the charts are inconsistent. This is very distracting.

The book is divided into 12 chapters, starting with a fairly trivial look at tabletop baseball games. The authors devote much attention to evaluating offensive performance, comparing various measures such as batting average, SLG, OBP, linear weights, total average, runs created and a few other more obscure ones. There is also some discussion of clutch hitting and a look at "Did the best team win the World Series?"

One of the other problems I found was that the authors stop short of providing actual statistical formulas and get into hand-waving a few times. I see that they have all the academic credentials but it seems as though they took the "book sales are inversely proportional to number of equations in the text" relationship to heart. I felt the book suffered because of that.

I'm not sure who I could recommend this book to. I have a feeling that some of the concepts might be too advanced for kids, and not deep enough for those who have a decent understanding of statistics. If you are into baseball stats but you don't know much about real statistics you will definitely find some new concepts in here, so I guess that is the audience.