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| View Larger Image | Curve Ball: Baseball, Statistics, and the Role of Chance in the Game | Paperbackby Jim Albert (Author), Jay Bennett (Author)
| List Price: | $19.95 | | Price: | $14.96 | | You Save: | $4.99 (25%) | | | Available: | Usually ships in 24 hours |
| | Binding: | Paperback | | Publisher: | Springer | | Page Count: | 432 Pages | | Publication Date: | April 08, 2003 | | Sales Rank: | 379,424th |
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ACCESSORIES |
| Rare Earth: Why Complex Life Is Uncommon in the Universe
by Peter Ward (Author), Donald Brownlee (Author)
The sweeping diversity of complex life on Earth, Ward and Brownlee argue, evolved out of an extraordinary set of physical conditions and chance events that would be extremely hard to duplicate- though not impossible. Many planets throughout the vastness of the Universe may be teeming with microbial life, but advancement beyond this stage is very rare. Everyone with an interest in the possible extent of life in the Universe and the nature of life's evolution on our own planet will be fascinated...
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| If the Universe Is Teeming with Aliens... Where Is Everybody? Fifty Solutions to Fermi's Paradox and the Problem of Extraterrestrial Life
by Stephen Webb (Author)
FROM THE REVIEWS: "Webb offers coherent, understandable, and sometimes humorous coverage of a diverse range of topics. He provides readers with non-trivial insights into research fields they may not have encountered previously . . . I think everyone who has ever considered the possibility that other intelligent civilizations exist elsewhere within our galaxy will enjoy Where Is Everybody? They will find much to agree with, and much to argue about, in this very accessible volume." ...
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EDITORIAL REVIEWS |
Product Description
"... 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 There is a fascination among baseball fans and the media to collect data on every imaginable event during a baseball game and to use these data to try to understand characteristics of the game. But 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 - including how to rate players, predict the outcome of a game or the attainment of an attainment, make sense of situational data, and decide the most valuable players in the World Series. Curve Ball is directed to a general audience and does not assume that the reader has any prior background in probability or statistics, although knowledge of high school algebra will be helpful. |
CUSTOMER REVIEWS (Average Customer Rating: 4.0 based on 13 reviews)
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Manages to explore relatively uncharted territory by John Craven (Seattle, WA, USA)  4 Stars
February 05, 2009
The world of sabermetrics is a much-explored one. Many topics have already been explored by some stat guy or another in the last 20 years. Some have been explored many times (clutch hitting, for instance). One of the best things about this book is that because the author isn't particularly immersed in sabermetrics, he manages to strike out (NO PUN INTENDED) into new territory and has some somewhat new insight on things that have already been looked at elsewhere.
Baseball game nerds will recognize the game at the beginning of the book as Ethan Allen's All-Star Baseball, one of the oldest on the market. It is, as noted, pretty basic, which is why it's so much easier to use as a model than, say, Strat-o-Matic or APBA (additionally, it isn't really, really awful, so it beats APBA there as well). He does return to the simulation from time to time, which is kind of fun but isn't really necessary: most statheads are well aware of the concepts of probability and random chance.
One area he does really strike some new ground in is in the category of consistency. It's really just an introductory look at the subject (to sum it up shortly, he demonstrates that Todd Zeile in the late 90s was subject to a lot more streaks and slumps than you'd expect by random chance) and as such it doesn't really *prove* anything, but it's definitely an avenue that deserves more look.
The book as a whole is worth nuggets of stuff like this. A full-on stathead will decry the All Star Baseball format because it doesn't truly model the way baseball works (as a guy who's done beta testing for a computer baseball game, I can confirm that people like this exist), but IMO that's a small criticism to make. A bigger one is that there are a lot of ideas tossed out but not a lot of proof made. However, if you already have TangoTiger's "The Book", subscribe to Baseball Prospectus, and have thrown away your Derek Jeter bobblehead because he sux, this is a good book to have on your bookshelf.
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An Important Addition to a Baseball Library by John A. Mitchell III (Jacksonville, FL USA) 4 Stars
December 29, 2008
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.
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baseball statistics interpreted by professional statisticians by Michael R. Chernick (Holland PA)  5 Stars
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.
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Non Fiction by Blue Tyson 4 Stars
September 03, 2007
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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good statisticians, pretty good writers by Russell A. Carleton 4 Stars
February 07, 2007
This one is a book for the Sabermetrically inclined who already have a background in stats. In the first couple of chapters, the authors review some basic concepts through the lens of baseball before getting into some deeper analyses. To be honest, there's nothing in here that you can't get in Baseball Between the Numbers (although to the authors' credit, this book predates BBTN by 6 years) but it's a decent starter's guide. Worth the read, although those with a background in Sabermetrics will probably want to pass.
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SIMILAR PRODUCTS |
| Teaching Statistics Using Baseball
by Jim Albert (Author)
"Teaching Statistics Using Baseball " is a collection of case studies and exercises applying statistical and probabilistic thinking to the game of baseball. Baseball is the most statistical of all sports, since players are identified and evaluated by their corresponding hitting and pitching statistics. There is an active effort by people in the baseball community to learn more about baseball performance and strategy by the use of statistics. This book illustrates basic methods of data...
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| Understanding Sabermetrics: An Introduction to the Science of Baseball Statistics
by Gabriel B. Costa (Author), Michael R. Huber and John T. Saccoman (Author)
Born in the 1970s as a radical challenge to traditional baseball statistics, sabermetrics has developed into a new way of understanding many aspects of the game. Its practitioners have created new statistical tools and revised our old ways of thinking about established measures such as the batting average, tactics such as the sacrifice bunt, and even who among the greats was truly great.
This introduction to the basics of sabermetric analysis explains concepts including normalization,...
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| The Book: Playing the Percentages in Baseball
by Tom M. Tango (Author), Mitchel Lichtman (Author), Andrew Dolphin (Author), Pete Palmer (Foreword)
Written by three esteemed baseball statisticians, The Book continues where the legendary Bill James's Baseball Abstracts and Palmer and Thorn's The Hidden Game of Baseball left off more than twenty years ago. Continuing in the grand tradition of sabermetrics, the authors provide a revolutionary way to think about baseball with principles that can be applied at every level, from high school to the major leagues. Tom Tango, Mitchel Lichtman, and Andrew Dolphin cover topics such...
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| A Mathematician at the Ballpark: Odds and Probabilities for Baseball Fans
by Ken Ross (Author)
In A Mathematician at the Ballpark, professor Ken Ross reveals the math behind the stats. This lively and accessible book shows baseball fans how to harness the power of made predictions and better understand the game. Using real-world examples from historical and modern-day teams, Ross shows:
• Why on-base and slugging percentages are more important than batting averages
• How professional odds makers predict the length of a seven-game series
• How to use...
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| Baseball Between the Numbers: Why Everything You Know About the Game Is Wrong
by The Baseball Prospectus Team of Experts (Author), Jonah Keri (Editor)
For baseball fans young, old, and in between, the ultimate guide to the new statistical thinking that's revolutionizing the game. The revolution in baseball statistics that began in the 1970s is a controversial subject that professionals and fans alike argue over without end. Despite this fundamental change in the way we watch and understand the sport, until now no one had written the book that reveals, across every area of strategy and management, how the best practitioners of...
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