Probably more than any other sport, baseball makes use of statistics. We see this with every baseball game on TV: not just the basic stats like batting average and home runs, but more detailed information like how well a particular batter does against a particular pitcher. The statistics on TV or in the newspaper, however, only scratch the surface. Baseball Between the Numbers provides a much more in depth look at the numbers behind the game and how to analyze them.
This process involves two parts. First, there is a look at the popular statistics to see how well they really track a player performance and contribution to the team. Batting average, for example, is not a really good indicator of performance; slugging percentage and on-base percentage provide a better reading. There is also a look at certain beliefs in baseball - such as the existence of clutch hitters - and whether they are based in reality or more of a myth.
The second part of this statistical analysis is coming up with new stats to provide more information. There are a lot of these, but the one that seems emphasized the most is VORP, Value over Replacement Player. In simple terms, VORP gives the value of a player compared to a replacement player of minimal major league skills (like a 0.200 batting average). If a player gets 200 hits in a year, he does not really contribute 200 hits to his team; instead, he contributes only the difference between his hit total and that of the replacement player; if this value is 110, then the player contributes 90 hits.
The purpose of all this analysis is two-fold. For one thing, it helps evaluate the potentials of players, so it is useful from a scouting perspective. It is also good for comparing players who played in different time periods. The introduction of the book gives a good example as it tries to show who the better player is, Babe Ruth or Barry Bonds. Superficially, some stats favor Ruth (such as batting average) while others favor Bonds (such as steals). But for any comparison to be legitimate, many other things need to be taken into account, particularly with the environment that the two played in; for example, Ruth played in a "whites-only" era that excluded many great players of other races. The more elaborate statistics take these differences into account; this particular analysis favors Ruth slightly, primarily because of his contributions as a pitcher.
To some extent, this book covers some of the same ground as a book I read a couple years back called Curve Ball, but it also offers a lot of new stuff too. The principal flaw with the book seems to be inadequate editing, leading to a lot of redundancies between chapters (which are written by different people); hence, we get the same explanation for what a statistic means over and over again. In addition, considering its importance to the game, pitching is underrepresented in the book; although covered, the primary emphasis is on batting. Other topics covered include fielding, base stealing and managing.
There is a danger with a book like this to get TOO into the statistics of the game and lose appreciation for the game itself. Statistics are great for looking at trends, but in any one given event, you can never be certain what's going to happen. That's why when it's the bottom of the ninth, two out and the tying run's at third, it doesn't really matter what the numbers say, and that's when baseball is at its most exciting. This book will make you look at the numbers of baseball more critically, but it won't diminish the pleasure of watching the game. Despite the flaws, I am giving this book five stars; for a baseball fan, this is a compelling read.
on March 15, 2006
Some of this will be old hat to those who already take stats like fielding independent pitching for granted, but it's a nice next step for baseball fans who enjoyed "Moneyball" and want to dive deeper into the numbers.
The book is arranged into 27 short chapters - one for each out in a regulation game, obviously - which frame each concept through an interesting question like, does Derek Jeter deserve a Gold Glove? This makes the more esoteric concepts easier to relate to, although familiarity and ease with numbers, charts and probability concepts helps a lot. The questions also serve as a reminder that the conclusions and predictive powers of this type of analysis have major implications for real world GM's, managers and players, as well as fans and fantasy leagues.
Quibbles: some of the analysis occasionally feels unbaked, which is understandable given this is an emerging field dealing with enormous amounts of data and probabilities. The writers do acknowledge this, such as when comparing pitching stats to relatively more reliable batting stats. It would also be nice to have more real life examples to back up each conclusion, including more quotes from GM's and managers - now that there are a number of admitted practitioners - on how they have used these concepts and with what results.
All in all, certainly not the last word on this subject, but a very good introduction.
on March 15, 2006
Derek Jeter bunts Robinson Cano over to second base in the 10th inning of a tie game. Is this an example of a team leader doing whatever it takes to win or an example of a career .300 hitter foolishly giving up a critical out? David Ortiz hits yet another game-winning home run. That man is "clutch." Or is he? The authors of "Baseball Between the Numbers" turn conventional baseball wisdom on its head in a series of chapters each dealing with a specific aspect of the game. They cover everything from the value of stolen bases to the economic impact of new ballparks. This book takes the reader step by step through the type of analysis that has increasingly influenced baseball decision makers from Billy Beane's "Moneyball" approach to Theo Epstein's Red Sox.
You don't have to be a math major to get the points of the book, but some basic knowledge of statistical principles is a big help. It's easy to get lost in the numbers sometimes, and the presence of numerous typographical errors and incorrect charts exacerbates the problem.
This book should be required reading for any baseball fan. If you're already familiar with sabremetrics and how statheads view the baseball universe, this book consolidates many of the key ideas in one volume. If you're not, this is a great introduction.
I enjoyed this book. However, it felt like a big advertisement for Baseball Prospectus, a site which I actually subscribe to and read quite often. This book didn't bring any real new information to the table that they don't already cover on their site, so if you're choosing between the two, just subscribe to their site.
My biggest disappointment is that while they explain what Eqa and VORP are, in essense, they don't tell me exactly how they calculate it. I suppose they are protecting their assets, but one of the pleasure of reading Bill James is knowing his thought process in coming up with formulas that measure performance. As the Baseball Prospectus team would have it, I'm supposed to trust that VORP measures it precisely without me being able to understand exactly why. That irritates me, but it might not get to you.
The book is fairly well-written and is entertaining enough to pick up if you're interested in this kind of book.
"Baseball Between the Numbers" contains 29 provocative questions handled with numbers and critical thinking. One of the first topics involves deciding whether Babe Ruth or Barry Bonds is the best player. The first step was to determine how much each was relative to his league, after taking park effects into account. Doing so demonstrates that Ruth was the superior hitter relative to his time.
However, athletes are bigger, better than they used to be - eg. gold-winning time in the men's Olympic 100-meter swimming even fell over 40% between 1896-1996. At the same time technology has improved - baseball bats, gloves, and sports medicine and nutrition. Meanwhile, the U.S. population roughly doubled from Ruth's time til today, and blacks and players from Latin America have also been added to the player pool. (Foreign-born players now make up close to 30% of major league players; in '30 there were about 300,000 people/major league player - now it is close to 900,000.
The authors addressed these problems by tracking and comparing performance of players remaining in a league from one year to the next - generating an index of difficulty change, and also comparing one league to another. Doing so shows Bonds far superior to Ruth (even though he undoubtedly would have benefited from better nutrition and not drinking for his depression, while Bonds has benefited from surgery not available to Ruth). Two more adjustments later (for factors not well explained), it is concluded that Ruth was the better.
Then there is the question of steroids. Bonds' post 2000 performance was compared to that expected based on his stats to that point. Conclusion: Bonds produced 142 more H.R. between 2000 and 2004.
Bottom Line on Ruth vs. Bonds: Who knows; however, if you can follow all the math you probably belong on Wall St, if you're not already there.
Players' Salaries vs. Ticket Prices: Salaries averaged less than $30,000 in 1970. Then an arbitrator ruled that players could play out their "option year" and become free agents. Since '76 (first year of free-agency), average player salary went from $51,501 to $2,632,655. Average ticket prices during the same period rose 68% above inflation to $19.82 - the big event was the 6/89 opening of Toronto's Sky Dome with 161 luxury suites and a concession mall. Attendance skyrocketed there. But 12 teams without new stadiums raised prices about 50%, after inflation, from '91 - '05.
Analysis found that the only segment attending more games in the '90s than the '80s was households with over $50,000 income (plus those in the new skyboxes). Normally this new demand would be met with increased supply - but not in the closed world of baseball. Bottom Line: No link between player salaries and ticket prices.
Another particularly interesting chapter was titled "Are New Stadiums A Good Deal?" (for taxpayers). The short answer - "No," the money would be spent elsewhere anyway and be more likely to stay within the area (vs. rich team owners, players). In addition, creating room for skyboxes has resulted in cheap seats being located further away. As for revitalizing the area, there are too many "dark nights" for local businesses to grow and thrive. Finally, auditors have found that new stadiums don't even cover the costs of construction and operation - subsidies are required. Yet, it goes on - N.Y. city plans about $400 million in subsidies (free land and infrastructure; foregone taxes, etc.) for both the Mets and Yankees to build new stadiums.
And then are are almost 20 other chapters!
on May 12, 2014
Baseball is a game of statistics and probabilities, yet "sabermetrics", as the study of advanced baseball statistics has come to be called, proves scientifically that much of what's been historically valued in baseball is wrong. This book is broken down into case studies that definitively settle some of the hottest debates in baseball. What's the ideal batting order? When should you bring in a closing pitcher? How long should a starting pitcher stay on the mound? Who's the best hitter of all time? And more.
It's really an interesting book if you go into it with an open and analytical mind. Some of the conclusions may be controversial - for example, don't tell any New Yorker that Derek Jeter's actually a below average shortstop, a Pirates or Tigers fan that Jim Leyland didn't really do much to help his team, or an A's fan that Rickey Henderson's steals were mostly worthless! But reading through how the authors got to these conclusions is fascinating, and ultimately impossible to argue with. Math doesn't lie, and the statistics that back up these conclusions - while requiring a few more calculations - are no less factual than batting average or on-base percentage (OBP itself is a sabermetric stat!).
It would be easy for this to have been a dry, reductionist book, as you might expect from a bunch of mathemeticians. It's written by multiple authors and while it's true that some chapters are a little livelier than others, generally speaking everyone seems to realize they're writing about a game - and that game is supposed to be fun. This book exists because these people love baseball and have fun thinking about it, and thinking of different ways they can challenge conventional wisdom.
It's taken a while to overturn baseball's old guard, but many teams these days incorporate some level of sabermetric thinking into their team building and on-field strategy. Times are changing, and this book will help you understand why that pitcher's swinging away instead of bunting, why your favorite team doesn't have a "speed guy" in the leadoff spot, and why you shouldn't be too upset when a manager gets fired.
Maybe more than that, it'll leave you wondering why teams still do things that are mathematically proven to be self-destructive. (Usually it's because it's what the fans and media expect them to do.) Baseball still has a ways to go to catch up to its own science, but reading this book will literally put you ahead of the game.
on May 24, 2006
The book consists of 29 chapters, in which some decision-making aspect of baseball is scrutinized by the evidence, all the way from whether attempting to steal a base is a good idea or whether that new stadium was a good idea. Be warned: this is a book written by Sabermetricians. If you're a fan of the romance and pageantry of baseball and recoil at the thought of managing with a computer, rather than by instinct, this book will offend you. (Psychology says systematic data is much better than instinct.) However, for the casual fan, this is a way of looking at the game from a new angle. The subtitle really does encapsulate the book. A lot of what you think you know about baseball is wrong, and the data are there to prove it.
The writing is uneven (it's a edited compilation of essays), and at times, the writers are too quick to introduce and explain complicated Sabermetric concepts. Folks unfamiliar with Sabermetrics will be a little befuddled at times, although a good slow read of the book serves as an excellent introduction to the field. In fairness, this is not a boring book either. Concepts are introduced and explained within context, and the numbers never overwhelm.
Hardcore statisticians will probably nitpick some of their methods, (e.g., "significant at the 90% level"... why did they set their alpha level so high?) and another review has pointed out that their work was a little sloppy, but even still most of the points are minor and probably wouldn't affect their overall conclusions. However, hardcore baseball statisticians have a reputation for not letting minor things pass...
on October 19, 2012
Baseball Between the Numbers is obviously a book for baseball fans and one that will appeal to both those who are and are not into sabermetrics. The top-notch writing and the way the book presents its findings and arguments combine to present a work that I give it the highest rating I possibly can.
The group I was in when I first started reading--newer to advanced statistics and looking to get more into how all the numbers work--will eat this book up. The best aspect of BBTN, however, is that it does not ignore what the game has been for so long, and still is to most people.
It is not a bunch of cold numbers or saying a player stinks because stat X is under Y, as if each guy is an answer to a third graders' math test--which is too often the impression people get of advanced stats, particularly among the non-sabermetric crowd. It's quite the opposite. Had somebody shown me concepts in math class--a few of which I recognize from school--and explained I could actually apply them to sports, you bet I would've been a heck of a lot more excited to go to math every day and probably actually understood the concepts.
Nobody is claiming these findings are gospel either. In many cases, they let the numbers themselves point out why a statistic is or is not repeatable. Or say flat out, that in certain cases it comes down to luck. This may seem to weaken the entire argument of why to use sabermetrics in the first place, but it is actually quite the opposite; understanding the weaknesses of your field will allow you to apply the findings more appropriately.
The most eye-opening sections are why the statistics shown with every batter on television are often poor gauges of performance. Many of these figures were developed at a time when the game was very different and while the game has changed, our ways of analyzing it has not (at least in the mainstream).
Each chapter seeks to answer a simple question: "Is David Ortiz a Clutch Hitter?" or "Is Joe Torre a Hall of Fame Manager?" While they seem simple, those questions encompass a great deal and each author does a solid job of explaining why they look at the figures they do to answer the questions. A side effect of which is training the readers to not only come up with their own questions, but figure out how to answer them. That is, if they are not too busy reading this book's sequel.
on October 9, 2006
The guys (and gal) at Baseball Prospectus (they have a premium web site)have been producing brilliant, mind-expanding, funny and analytically-based books for 10 years.
If you watch baseball on TV (networks, national and/or local cable channels), you almost certainly pull your hair and shout at your TV when the announcers talk about any of the following: the importance of chemistry, why being aggressive at the plate is gggrrreeeaattt, how bunting leads to winning, and how pitch counts are ruining the pitchers and slowing down the game (actually, advertising is slowing down the game).
A lot of fans are very emotional about baseball and are often not open to new ideas or different ways of looking at things. The people at BP have done exhaustive research and have broken new ground in the area of statistical analysis. In this book, they show the following: why batting order really doesn't matter; how closers are often misused (in low leverage situations rather than when there are 2 men on in the 8th); that most managers do not make any difference; that new stadiums are just a horrific deal for the tax payer; and why steroids really haven't effected the game much at all (I know, very hard to swallow).
It's a very well written book. It is a little dry at times because of the reliance on statistics and graphs, but it is a most-own book for baseball fans.
on February 9, 2016
If you love numbers or statistics, this book is a FIVE. It you don't or if you don't like page after page of intense mathematics, this book is a ONE. if was inevitable that computers would be used to work their devilish magic on the sport of children but I never realized that there were people who thought like this...and apparently there are thousands of them. These are the same people who figured out a way to compute the value of Pi (3.14159....) to more than million digits which is enough numbers to provide a UPC for every molecule in the universe. And they are trying to do this to baseball and connect every manager to a neural computer with a 1 pico-second response time and a one terabyte memory. If you want to know why the center fielder moves one step back and the shortstop moves two steps to the right when a new hitter comes to the plate, this is your book.