A very compelling book of baseball . I found so many useful info . Not to be read by those who don’t understand a whole lot about the game

If you don't know much about baseball, but you're looking for a book to help you gain a better understanding of the sport, this is NOT the place to start. This is a book for a pretty advanced baseball enthusiast, someone who not only likes baseball, but is also generally interested in economics and thinking about numbers. It is a collection of essays, each dealing with a different topic, but using the same techniques to analyze how we understand what we are seeing when we watch a baseball game. The following anecdote isn't included in the book, but I feel like it does a good job of explaining what its pages contain.

Background:
People have been playing baseball for a very long time. What makes baseball different from football or any other sport is that people have been playing baseball essentially the same way for a very long time. Statistics for a baseball player who played in the 1920s are still comparable to statistics for a player who plays today. Baseball fans have grown up looking at the back of baseball cards, seeing the statistics of players, and making judgments about the value of players based on those "traditional" stats: Batting Average and RBI (Runs Batted In) for hitters or Wins and Losses for pitchers. What this book says is that those established statistics which have been used to measure a player's ability are flawed and cannot give us the best concept of a player's skill.

Example:
Ask a baseball fan if he could tell the difference between a .300 hitter and a .250 hitter and he would say "Of course!" A .300 batting average has been the hallmark of excellence for over a century; .300 hitters are rare and exceptional, players who have long and storied careers. A .250 batting average, by contrast, is the hallmark of mediocrity. A player who manages a .250 average might play for a few seasons, perhaps even a full career, but will hardly be remembered and certainly not revered. A baseball fan has trained himself to think a .300 hitter will look excellent when he is at bat, while a .250 hitter will look mediocre.

A baseball season stretches from the beginning of April to the first few days of October, around six months or 26 weeks. For the sake of argument, let's say that over the course of a season a typical player might have around 600 At Bats (a little high, but close enough). Over those 600 ABs, a .300 hitter will get 180 hits, while a .250 hitter will get 150 hits. While a 30 hit difference might seem like a lot, it really isn't. Six hundred ABs over a 26-week season breaks down to about 23 ABs a week. A .300 hitter will have 6.9 hits a week; the .250 hitter will have 5.75 hits a week, a difference of about 1.15 hits a week.

What does it mean?
A baseball fan thinks he can recognize the difference between a .300 hitter and a .250 hitter very easily, but what he really recognizes is the context the statistic gives him. If batting averages weren't compiled and prominently displayed all over the ballpark during every At Bat of every player, a baseball fan would not be able to distinguish between the player who gathered an extra 1.15 hits per week and the player who didn't, even if he watched every At Bat of both players all season! The difference between excellence and mediocrity is too marginal to be determined with the naked eye - we use statistics to make the determination for us, and they matter for baseball because the meanings of these statistics and labels have mostly remained the same for over a century.

The purpose of this book is to look at all of the statistics we have been using over that century and seeing if they actually help give us the best concept of a player's skill level. As the authors claim, what you think you know about baseball statistics is wrong, or at least not completely right. This book gives the baseball fan new statistics to help him understand the game a little better.

Put on your regression analysis caps, gang. Even for geeks, this one is pretty dense.

It's Moneyball without a protagonist, a series of challenges to baseball's sacred cows. The book is often fascinating, though some of its original conclusions--bunts are wasted outs, Derek Jeter isn't the greatest defensive shortstop--aren't as revolutionary in 2014 as they were when the book was published.

In that sense, you can say the statheads won.

Not for me. Could be for bigger baseball stats fans

Outstanding so far! Again, like J.C. Bradbury's book, it peaks interest at looking at baseball stats in a non-traditional way. It's continuing to encourage me to do more statistical research, but not just on traditional stats.

This collection of Baseball Prospectus (BP) articles is a great intro to sabermetrics. There are discussions on Value Over Replacement Player, Win Expectancy, Equivalent Runs, and many other statistics that the BP team developed to get a deeper, more accurate understanding of how measurable metrics reflect actual player value.

They demonstrate the error of trusting some of the traditional statistics that have been used to value players for years. Stats such as RBIs & batting average for hitters, and ERA and Wins for pitchers are shown to be highly random and dependant more on opportunity and luck than actual skill or talent.

In addition to the many articles on individual player assesment, there are articles that delve into team efficiency and defense, as well as the importance a manager plays on his team's success.

Overall, this is a great book for an avid baseball fan; it is not an intro book for a novice to the game. I'd highly recommend this book to anyone interested in Fantasy Baseball also. Eventhough there are a handful of statistics that only describe past value, there are many more that can be used as predictive statistics to forecast future performance. Specifically, BP has their PECOTA system which uses past statistics, as well as player age, player type (e.g. big vs fast), and expected career arc path (e.g peak early, average, or late) to predict upcoming yearly stats.

My only complaint of the book is a small one. As this is a collection of previously stand-alone articles, there is some degree of redundancy from chapter to chapter. That's not enough of a complaint to knock it down from 5 stars though.

I thought this book was going to teach me a bunch of things I didn't already know, but in fact most of the big news is already old hat. The authors pose several interesting questions and come up with clever ways to answer them, but to a large extent they're just updating arguments made more than twenty years earlier in Bill James' Baseball Abstracts and in The Hidden Game of Baseball by John Thorn and Pete Palmer.

This is the book to show people who think RBI is a meaningful stat, or that Derek Jeter is 'clutch'. It's on par with "The Book" by Tango and Dolphin, but much better written.

Highly recommended

First, I love when book titles include "Why Everything You Know About ______ Is Wrong". Second, one of the best closing sentences ever: "So, you know, don't be a fool." As with any collection of essays some are more interesting than others and this can make the book feel uneven at times. I see baseball differently after reading this than I did before reading it. Overall, it was very enjoyable.

There are so many questions inherent in every professional baseball game: Which pitcher should start (and when)? Should the sacrifice bunt be laid down? Is the closer best saved for the ninth inning? What more important: on-base or slugging percentage? The list could go on and on. This book takes a purely statistical approach towards answering those questions, using averages and complicated (to the layman) formulas to parse the facts.

For the baseball junkie, almost every chapter in this book raises a new and interesting question. Though a game based on averages can never quite be predicted accurately (the worst hitter in the league always has a chance against the best pitcher), this book takes the stats-bases approach to finding answers, parsing through decades of raw numbers to do so. This is intriguing because most baseball fans only see the sport through small sample sizes like games, weeks, or even months. This crew from Baseball Prospectus, however, uses substantially larger sample sizes to more accurately interpret the information. The result is some very interesting findings that will likely challenge some of your long-held notions about the game.

The only drawback of this book is that the statistical formulas used will go over the head of those not familiar with high-level number manipulation. You basically have two options: Spend hours trying to understand all the graphs/data points, or just trust that the stat-heads are feeding you good information. I took the latter approach, and was still able to enjoy the experience.

Overall, then, Baseball Between The Numbers is an interesting little read for the hard-core hardball fan (others will be scared away by the intense subject matter). Think of it like Moneyball, but without the specific focus on Billy Beane and his Oakland A's.

This is a terrific introduction to advanced statistical analysis, and how a better objective understanding of how baseball games are won can lead to better player evaluation and projection. Baseball Between the Numbers also does a great deal to diffuse the manufactured argument of "stats versus scouts." As the authors of this book point out, a successful team needs both stats AND scouts. Each of these methods make up for the weaknesses and limitations in the other. Thankfully, most MLB organizations nowadays are incorporating both into their player evaluation and development systems. More and more scouts are using statistical analysis to give themselves a context in which to evaluate the players they are assigned to observe. This is a most welcome development, and hopefully the beginning of the end of a very tiresome argument.