The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball

by Benjamin Baumer, Andrew Zimbalist

From the front office to the family room, sabermetrics has dramatically changed the way baseball players are assessed and valued by fans and managers alike. Rocketed to popularity by the 2003 bestseller Moneyball and the film of the same name, the use of sabermetrics to analyze player performance has appeared to be a David to the Goliath of systemically advantaged richer teams that could be toppled only by creative statistical analysis. The story has been so compelling that, over the past decade, team after team has integrated statistical analysis into its front office. But how accurately can crunching numbers quantify a player's ability? Do sabermetrics truly level the playing field for financially disadvantaged teams? How much of the baseball analytic trend is fad and how much fact?

The Sabermetric Revolution sets the record straight on the role of analytics in baseball. Former Mets sabermetrician Benjamin Baumer and leading sports economist Andrew Zimbalist correct common misinterpretations and develop new methods to assess the effectiveness of sabermetrics on team performance. Tracing the growth of front office dependence on sabermetrics and the breadth of its use today, they explore how Major League Baseball and the field of sports analytics have changed since the 2002 season. Their conclusion is optimistic, but the authors also caution that sabermetric insights will be more difficult to come by in the future. The Sabermetric Revolution offers more than a fascinating case study of the use of statistics by general managers and front office for fans and fantasy leagues, this book will provide an accessible primer on the real math behind moneyball as well as new insight into the changing business of baseball.

Genres: Baseball, Sports, Nonfiction

208 pages, Paperback

First published December 26, 2013

Reviews

[Eric · Rating 3 out of 5]

If you loved Moneyball, you should read this.

Not always as well thought-out as possible, it is nevertheless marvelously researched and provides fascinating insights into analytic data in baseball (and one weird chapter about football and basketball). The main reason for 3 stars is that it presents itself as a book about sabermetrics but spends a lot of time challenging claims and assumptions in Moneyball. This is both good and valuable, but not what the shell promises.

Basically, sabermetrics are most useful for the business side of baseball, and this book is a companion to Moneyball in that Lewis explained "why" with a brilliant story but Baumer and Zimbalist explain "how."

[David · Rating 2 out of 5]

an interesting summary of public sabermetrics, but they use circular logic in the last chapter to determine the effect of sabermetrics on winning (by finding some measures that correlate better with win % than the traditional baseball metrics, and then seeing if teams that focus on these metrics win more games than other teams, after controlling for payroll).

I'm glad I read the book, but it leaves me worried that the state of statistical research among teams (one of the authors was a long-time sabermetrician for an MLB team) is quite low, and instead of hiring graduate level statisticians, they are hiring amateur statisticians/journalists to do their quant research

[Brad · Rating 3 out of 5]

I'm a baseball fan, and I appreciate the emphasis on sabermetric analysis in the sport, so even though this book is - what - ten years old, I mostly enjoyed reading it. I have to say "mostly" because to really get the most out of this book you'd have to be a pretty serious statistician. These guys use terms like regression, standard deviation, and many, many others as though they were having a conversation over their morning coffee. As a result, I just zipped over most of the charts and graphs and tried to appreciate the text and the conclusions they drew from their "cipherin'". I am not at all saying that the authors pretended that this book was anything other than what it was - in its way, a "sabermetric" analysis of sabermetrics.

[Justin · Rating 4 out of 5]

I came into reading this without knowing too much about sabermetrics other than Moneyball, so I learned a lot from this book. I found it pretty accessible with a basic stats background.

[Matt · Rating 3 out of 5]

In the wake of Moneyball mania, a math professor and an economics professor set out to evaluate what impact statistics have had on major league baseball in recent decades. They find some misrepresentations from Michael Lewis' tale of how the 2002 Oakland A's used data to win. Then, they evaluate the history of statistical analysis in baseball. It's a history that stretches back before Bill James drastically increased its popularity in the 1980s. The authors note: "the early and easy insights of baseball analytics have been exhausted". MLB teams no longer overlook on-base percentage (OBP), nor do they over value stolen bases. The frontier of the field appears to be more accurately evaluating defense. They point out how inept fielding percentage is as an indicator of individual skill and note that the new metric of ultimate zone rating (UZR) is not particularly reliable at evaluating fielding skill from year to year.
They wrap up the book by discussing how much statistics have influenced major league teams and whether or not adopting statistical approaches have made teams more successful. While it is hard to say that all analysts provide good value, those that do are a steal for major league front offices. If good scouts/analysts can help teams improve their strategy and player development, their salaries are much smaller than the multi-million dollar contracts of the best players in the league. And this makes them a great value.

[Nelson · Rating 5 out of 5]

Peer-reviewed page turner! Baumer and Zimbalist did for sabermetrics what Terryl Givens did for Mormon apologetics: Cite them all in a high-end, peer-reviewed book on intellectual history where arguments are evaluated. In spite of its academic style, this book was more interesting than the other sabermetrics books I've read.

It devotes two chapters on the findings of sabermetrics, a couple on the myth of Moneyball, and a couple more that evaluates, quantitatively, the impact of sabermetrics on the game.

I even read the appendix and a lot of the footnotes in chapter three and four this was so good.

[Ivan Taylor · Rating 4 out of 5]

A good antidote to Moneyball. It points out where Moneyball was right and where in many cases it was wrong. It does a critical review of sabermetrics; what is good and what is bad. He likes consistency and predictive value. He is also very critical of propriety work being done that cannot be validated by peers. He has an interesting statistic on the value of sabermetrics to MLB teams. Although most teams have jumped on the bandwagon, there is the notable exception of the very successful Atlanta Braves.

[Simon · Rating 2 out of 5]

It's definitely not "Moneyball" entertaining, but a higher level look at the use of sabermetrics in baseball.

[BC · Rating 4 out of 5]

Very interesting data oriented book which is a true antagonist to Michael Lewis' Moneyball.