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

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.

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.

From the reviews: PHYSICS TODAY "...a most interesting and useful introduction to the subject. It should make enjoyable reading for physicists who are also baseball fans, and it ought to be required reading for baseball managers, executives, and commentators." MAA ONLINE "With the exception that some of the models build on previous ones, this book has the appealing quality that you can start reading at almost any chapter and enjoy and understand the journey. And for those of us who are not statisticians by training, we can also learn some statistics…CURVE BALL is a fascinating source book for both baseball and statistical applications thereof. It’s a good read, and good mathematics." TECHNOMETRICS "…a wonderfully fascinating book…it is an absolute necessity for any statistician who still follows baseball to run right out to borders or amazon.com and buy a copy." "Jim Albert and Jay Bennett’s Curve Ball is an attempt to apply the techniques of statistical analysis to the understanding of baseball statistics. … The book seems to be addressed primarily to baseball fans who are not necessarily educated in probability theory. … Physicists who understand baseball will find the mathematical reasoning quite easy to follow. … It should make enjoyable reading for physicists who are also baseball fans, and it ought to be required reading for baseball managers, executives, and commentators." (C. Alden Mead, Physics Today, October, 2002) "Curve Ball by Jim Albert and Jay Bennett is a necessary addition to any library. … the book is an interesting read, full of detailed examples that include data from Major League Baseball games along with many classic stories from the sport. For readers possessing no knowledge of statistics, this book is a great way of learning how to view and interpret data from a statistician’s standpoint. … I found the book to be well-written and non-technical." (Stanley Wasserman, CHANCE, Vol. 15 (4), 2002) "Subtitled ‘Baseball, Statistics, and the Role of Chance in the Game,’ this is a wonderfully fascinating book. … For me reading this book might be a completely entertaining experience. … it is an absolute necessity for any statistician who still follows baseball to run right out … and buy a copy." (Eric R. Ziegel, Technometrics, Vol. 44 (1), 2002) "I particularly enjoyed the middle three chapters, which were devoted to nonstandard ways to measure offensive performance and the value of a hitter to a team. … this book has the appealing quality that you can start reading at almost any chapter and enjoy and understand the journey. And for those of us who are not statisticians by training, we can also learn some statistics. … a fascinating source book for both baseball and statistical applications thereof. It’s a good read, and good mathematics." (J. Kevin Colligan, MAA Online, June, 2002)

"For numerical loyalists, this book delivers a new degree of bliss."

The intent of this book is to 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 to use this data to try to understand characteristics of the game. The problem is that patterns in baseball data are difficult to detect due to the inherent chance variation that is present. This book addresses a number of questions that are of interest to many baseball fans. These issues 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. This book will be directed to a general audience of baseball fans and does not assume that the reader has any prior background in probability or statistics, although a knowledge of high school abgebra will be helpful.

We're surrounded--some might say inundated--by baseball statistics. We find them in newspapers and magazines, in books and on the back of baseball cards, and on TV, radio, and the Internet. There are stats on teams, players, and managers, broken down by year, by month, by on-base situation, by home/away, by turf/grass, by night/day, by lefty/righty. And with the widespread use of computers, we find that we can drill down through layers of statistics to reach the truly arcane (and small) data set: When he's behind in the count facing left-handers in parks with artificial turf. . . . The question is, can fans--or anyone--make sense of this proliferating data?

Authors Jim Albert and Jay Bennett believe that just a slightly more sophisticated approach to statistics can greatly increase our understanding of baseball numbers, and our appreciation of the game. Whether they are describing situational statistics (a favorite of broadcasters), the phenomenon of "streaks" (Can a player actually have a "hot hand"?), or fascinating alternatives to traditional measures like the time-honored Batting Average, Albert and Bennett help us take a fresh look at the numbers that are an integral part of our national pastime.

All professional batters can hit a fastball down the middle--if they are prepared for it. But to get to the top level of play, they have to know how to hit a curve. The same can be said of those who pore over baseball statistics. True fans get a great deal of intriguing and suggestive information from the stats found in newspapers, emanating from the broadcast booth, and compiled on the Web. But to see the truth behind the numbers, fans need to bring just a little more statistical sophistication to the data. They need to master the curve.

Jim Albert is Professor of Mathematics and Statistics at Bowling Green State University. He currently chairs the Sports Section of the American Statistical Association.

Jay Bennett is a Senior Scientist with Telcordia Technologies and editor of Statistics in Sport (1999). His views on baseball statistics have appeared in USA Today, Time, and Omni.