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Curve Ball: Baseball, Statistics, and the Role of Chance in the Game Paperback – April 8, 2003

by Jim Albert (Author), Jay Bennett (Author)
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In its formative years, from the 1970s through the 1990s, sabermetrics was p- marily an amateur undertaking. Publications were aimed at a relatively small audience of baseball fans. To be sure, this ever-growing group of aficionados brought a lot of sophistication to baseball analysis, and were constantly looking for statistical insights beyond the listings of the top ten batters found in popular newspapers and magazines. But their influence on the baseball profession was very limited. A few consultants like Craig Wright developed temporary relati- ships with various teams, but none were able to stay long enough to create a p- manent sabermetrician staff position. (See Rob Neyer’s November 11, 2002, arti- 1 cle on ESPN. com. ) All of this changed, however, in 2002 with the hiring of Bill James by the Boston Red Sox. With that move, we have seen the admittance of the foremost proponent of sabermetrics into the top echelon of professional ba- ball management. The art and science of careful statistical analysis, it now seems, had made it into the big leagues. Since the publication of the first edition of Curve Ball in 2001, we have been overwhelmed by the positive responses from readers and critics. We’re pleased with the reception, of course, but we don’t want to rest on our laurels. Like a pitcher refining his repertoire, we’ve revised, expanded, and updated the book for its publication in this paperback edition. Several readers and critics took us 1 http://espn. go. com/mlb/columns/neyer_rob/1456664.
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  1. Print length
    428 pages
  2. Language
    English
  3. Publisher
    Copernicus
  4. Publication date
    April 8, 2003
  5. Dimensions
    5.98 x 0.84 x 9.02 inches
  6. ISBN-10
    9780387001937
  7. ISBN-13
    978-0387001937
  8. See all details
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Editorial Reviews

Review

From the reviews:

"...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." PHYSICS TODAY


"...a smart and energetic collection of essays on baseball statistics. Curve Ball doesn't play misty-eyed homage to baseball's traditions and conventional wisdoms....This is great stuff....Curve Ball makes clear how pleasurable [stats] can be, and arguably how important, to view the great American game with real precision." -- The Wall Street Journal

"Rating: 4.5 out of 5. Must own!" -- Baseballnotebook.com

"In [Curve Ball] Albert & Bennett explain the game in ways the conventional press - even titans such as Bill James - cannot." -- Baseball America

"[The book] illustrates how statistical reasoning can be useful in teasing out the role of chance from performance in baseball to better assess ability....Curve Ball represents another advance in the genre of baseball and statistics books." -- Journal of the American Statistical Association

"This is a very good, fun and highly interesting book, applying some straightforward, and some more difficult, statistical estimation and modeling concepts to baseball. … I am a statistician, and mostly Bayesian at that, and this definitely enhanced my interest and enjoyment of the book. … Initially this book starts out as a sneaky introduction to statistics and Bayesian concepts, however, it turns into a delight for sports fans and statisticians alike. Highly recommended … ." (Richard Gerlach, Gazette, Vol. 31 (5), 2004)

"This book treats a wide variety of topics, including: comparing measures of batting ability; the impact of situation on performance; streaks; measuring a player’s clutch performance; and did the best team win the World Series. 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." (Zentralblatt für Didaktik der Mathematik, September, 2003)

"Curve Ball … is a necessary addition to any library. … Written for all followers of baseball, this book caters to those who find joy in reading (and if you are like me, memorizing) the statistics on the backs of baseball cards or who played baseball simulation games … . 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. Readers with statistics backgrounds will enjoy the book … ." (Jonathan L. Templin, Chance, Vol. 15 (4), 2002)

About the Author

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.

Product details

  • ASIN ‏ : ‎ 038700193X
  • Publisher ‏ : ‎ Copernicus; Softcover reprint of the original 1st ed. 2001 edition (April 8, 2003)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 428 pages
  • ISBN-10 ‏ : ‎ 9780387001937
  • ISBN-13 ‏ : ‎ 978-0387001937
  • Item Weight ‏ : ‎ 2.31 pounds
  • Dimensions ‏ : ‎ 5.98 x 0.84 x 9.02 inches

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Jim Albert

Jim Albert

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Jim Albert is Distinguished University Professor of Statistics at Bowling Green State University. His interests include Bayesian thinking, statistics education, statistical computation, and applications of statistics to sports. He is a former editor of the Journal of Quantitative Analysis of Sports.

Customer reviews

4.1 out of 5 stars
21 global ratings

Top reviews from the United States

James Braswell
5.0 out of 5 stars STATISTICIANS PROBE BASEBALL STATS AND CHANCE IN THE NATIONAL PASTIME
Reviewed in the United States on June 2, 2014
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Excellent book on the role of chance and probability theory as reflected by baseball statistics and also individual and team play. Written for the baseball fan who does not need a degree in higher mathematics.
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John A. Mitchell III
4.0 out of 5 stars An Important Addition to a Baseball Library
Reviewed in the United States on December 29, 2008
Verified Purchase
For anyone who wishes to understand cause and effect in baseball, this is a very insightful book. The authors clearly and convincingly demonstrate that many of the statistical outcomes we generally attribute to a player's ability are really nothing more than random effects. For example, a player with a lifetime batting average of .300 who hits .280 during a season is said to have had an "off year." The authors show that any player who has a true batting ability to produce base hits in 30% of his at bats (i.e., a .300 hitter) can be expected to hit .280 or less or .320 or higher about one-third of the time. For someone who grew up thinking that all these year-to-year fluctuations were the result of "good years" and "bad years," the very significant impact of randomness came as a rude awakening! But for the serious student of the game, this is a critically important insight.

Similarly, the authors show that a team's win-loss record during any single season may not reflect the team's real ability. Again, in 162 game season, randomness rears its head. It is not that uncommon for a team to win 12 to 15 games less (or more) than its underlying talent would suggest.

As we reduce the number of games in a series (for example, consider the typical best-of-seven post-season playoff format), the effects of randomness are greatly magnified. Thus it is not at all uncommon for the best major league team in any season to fail to win the World Series.

"Curve Ball" is well written, and the authors do a good job of explaining the statistical models they employ. I often find myself returning to this book to refresh my understanding of baseball probabilities.

The one deficiency that bothers me most is the lack of a subject index. Thus the reader is forced to thumb through the book to locate some particular topic of interest. But even so, this is an excellent book that belongs in any good baseball library.
3 people found this helpful
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Michael R. Chernick
5.0 out of 5 stars baseball statistics interpreted by professional statisticians
Reviewed in the United States on January 24, 2008
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.
32 people found this helpful
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The Huntington Book Depository
3.0 out of 5 stars You had better really like statistics
Reviewed in the United States on July 16, 2020
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Just as a cautionary note, this is a statistics book first, and a baseball book second. If you love statistics and baseball, this book is right up your alley. If you love just baseball, or just the math behind the game a little bit, this book is going to be a bit painful. I had worked my way toward this book by enjoying reading about sabermetrics in Baseball Prospectus, Moneyball, and Baseball Between the Numbers - all of which did a great job of explaining the statistical revolution in sabermetrics while keeping the subject matter approachable to the novice or intermediate reader.

This book however is much more geared to the advanced statistics lovers out there. Lots of equations/charts/formulas to explain various concepts in the game, without the necessary explanatory narrative to keep it grounded for the non-statistician. It may be a five star book for others out there, just wasn't what I was looking for. So consider my review a cautionary tale before you buy!
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Kindle Customer
4.0 out of 5 stars Non Fiction
Reviewed in the United States on September 3, 2007
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A look at baseball from a sports statistics and published mathematical analysis front. Interesting, but not as ground breaking as some of the amateur non university researchers came up with not too much later. A bit of an overview.
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