Statistics in Baseball

Today's been pretty busy for me and I have not had the time to write a new article. However, since I know how eager and expectant everyone is on a new article at least 4 days a week, I have decided to post an excerpt from a paper I wrote last winter. The paper is essentially about the modern use of statistics in baseball. It's pretty interesting so I thought maybe people would enjoy it. That said, it was for a research class, and thus, pretty void of humor which, assuming that there is humor on this blog site to begin with, is a bit unfortunate.

As for the poll question, we had a tie (gasp! no, not a tie!) for the world cup and a personal story. So, I will attempt to write both at some point within the next week and a half.

Enjoy the excerpt!

"In 1977, James wrote his first book, the Baseball Abstract, which he advertised in various baseball publications. In this book, James questioned commonly held baseball theories. “’People say things about baseball,’ explains James, ‘and I want to find out whether they are true. So I have to figure out how to find out if they are true. I write about the process of finding out and about the results.’” This baseball analysis is known as sabermetrics, named after the Society for American Baseball Research. James’ abstracts had a small response but over the years, as he continued to improve them, his audience broadened. James introduced new statistics to evaluate players. His most notable ones were “Runs Created,” which combined total bases, hits, and walks, and “Range Factor,” a method of evaluating fielding beyond the number of errors made. By 1984 James found himself at the center of the baseball numbers’ world. His abstracts became perennial bestsellers and statistics in baseball had emphasis like never before.

Coinciding with James and his abstracts was the creation of rotisserie or Fantasy Baseball. In his highly respected book, Curve Ball: Baseball, Statistics, and the Role of Chance in the Game, Jim Albert writes, “Next to stock market analysis, [Fantasy Baseball] may be the most widespread application of statistics in the United States.” The roots of this craze can be traced back to Dan Okrent. In 1980, Okrent assembled a group of his friends and proposed an idea to make watching baseball more exciting. He claimed that “Rotisserie baseball,” which was named off the restaurant where they met, gave the common fan the opportunity to manage a baseball team vicariously, and without needing millions of dollars. On the first Sunday of the season, Okrent and eleven others drafted real baseball players onto their imaginary teams, which would be judged based on how each team’s players hit and pitched. It was not long before Okrent’s creation began to dominate the group’s lives. He said, “’Each morning, all of us ran to the box scores, manically searching the agate type for news.’” The following spring, Okrent wrote an article in Inside Sport and explained his creation. Across the country, Fantasy Baseball leagues formed. By the time the original twelve people were selling their book, Rotisserie League Baseball, there were hundreds of thousands of fans participating in rotisserie leagues.

The popularity of Okrent, James, and their respective creations can be attributed to the emergence of computers. In as early as 1965, various companies, such as General Electric and Information Concepts, Inc., were creating massive computers to grind out numbers to be used by statisticians. The Macmillan Baseball Encyclopedia was published in 1969 and created entirely by a computer program. Corporations with computers had means of calculating statistics faster, and with more accuracy. Once computers became available for personal use, individuals were given the same opportunities to calculate a wide range of statistics. In its infant stage, Fantasy Baseball required participants to sieve through the newspapers to find their players’ numbers. Finding and calculating data became simple with the invention of the computer, more specifically the Internet. In 1985 a program was created that instantly calculated Rotisserie League standings. According to the Sporting News, “’The Rotisserie phenomenon has a lot to do with the development of the personal computer. The computer makes it easier for everyone to get involved.’” The Internet is also responsible for the camaraderie that emerges because of online discussion. This will be discussed more in depth later.

A broad examination of statistics in Major League Baseball as a whole is well beyond the scope of this project. However, by analyzing one team, the Boston Red Sox, we can see how their recent actions epitomize the power of numbers in baseball today. At the end of 2002, the Boston Red Sox decided to take a statistical approach to winning baseball games after an 84 year World Series drought, during which they used a more traditional method. The front office for the Red Sox brought in Bill James to be an analyst. This move by the Red Sox was viewed as “cutting edge” by various baseball figures. He supplemented scouting operations and evaluated trade potentials. In addition, James was finally given an opportunity to test some of his long held beliefs. One of James’ theories is that closers should not be limited to ninth inning appearances. In many cases, these games are no longer close. James argued:

Essentially using your relief ace to protect a three-run lead is like a business using a top executive to negotiate fire insurance. If you have a fire and you’re not insured, obviously that’s a huge loss. But the reality is that, even if you don’t carry any insurance, you’re not likely to have a fire. And while you may desperately need insurance, that doesn’t mean that it is therefore essential to assign your best executive to negotiate it. There are other people who can take care of that kind of work.

The Red Sox announced that in 2003 relievers would be used, “according to logic, not legend.” However “logical” James’ theory may have been, the strategy failed miserably. Boston relief pitchers’ had an ERA of 4.83, third worst in the major leagues. Management attributed this to weak pitchers, not poor strategy. Nonetheless, the Red Sox were able to make it to the playoffs and the American League Championship Series. This is where the problems for the organization really began.

The Red Sox were in Game Seven of the ALCS against the New York Yankees. In the eighth inning, the Red Sox led five to two and were just five outs away from the World Series. When superstar pitcher Pedro Martínez gave up three straight hits and a run, manager Grady Little approached the mound, spoke with his ace, and decided to leave in Martínez. Little claimed his decision was based on his instincts, but he knew that after one hundred pitches, Martínez was a “ticking bomb.” The Boston Red Sox had arguably the most statistically adept front office in all of baseball, led by Bill James, yet they would suffer a downfall because of neglected data. Martínez was one of the best pitchers prior this benchmark but according to Peter Gammons, “afterward, nothing close.” The Yankees rallied against Martínez, won the game in the eleventh inning, and Little was fired.

Boston replaced Little with Terry Francona, a younger man who was supportive of the use of statistics. Apparently, the Red Sox wanted to have “’one unified organizational philosophy [towards statistics].’”However, management quickly realized that these words were too strong and clarified the above statement by saying that the Red Sox would not be a, “’stat geek organization.’” Even with the increased respect and use of statistics, the label of a “stat geek organization” is one that the front office fears. They could not risk a direct identification with the number-regurgitating, laptop-carrying figures who run the statistical world. The Red Sox needed to remain pure to the game of baseball and maintain its integrity. One general manager, Billy Beane, who is known for his respect of statistics, once responded to the notion of attending a SABR gathering with the words, “’That would be like Captain Kirk going to a Star Trek convention.’” Even after such tremendous evolution of statistics, managers must still make decisions based on other factors than pure statistics.

New statistics are created everyday to measure production, to prove a theory, or to reject a commonly held belief. In a project of any size, it would be an impossible endeavor to detail all of these obscure forms of measurement. Instead, we will look at one intriguing theory that has grown considerably in popularity over the last decade or so. For all of baseball’s existence, stories have been told of great hitters coming through in the clutch. Some of the most recognizable nicknames have been given based off this apparent skill. Reggie Jackson, whose plaque at Yankee Stadium reads: A prolific hitter who thrived in pressure situations, is known as Mr. October because of his “clutch” play during the playoffs. Statistical analysts would reject this notion claiming that “clutch hitting” does not actually exist.

The major argument is that no player consistently performs better in the clutch. Good players merely go on hot streaks. Sometimes these streaks occur during important situations but more commonly, they take place during insignificant points in the season. Statisticians contend that a player will eventually come to maintain his average in all situations. “’The problem with the postseason,” argues Keith Law, senior writer for Scouts Inc., “’is that we run into such small samples.’” One player that is typically viewed as clutch in modern baseball is Derek Jeter, “Mr. November.” Jeter is a career .316 hitter. With runners in scoring position he hits .311 and when there are two outs and runners in scoring position, he bats .317. In the postseason, the period in which he is best know for clutch hitting, Jeter has a .309 batting average. His numbers in pressure situations are very good, however they should be expected given his high career batting average.

In Curve Ball, Jim Albert lists the averages of the entire American League in various situations, which range from pressure-free to intense. A pressure-free situation would be batting lead off and an intense situation would be batting at the end of an inning with runners in scoring position. In total, there are ten different situations. The key observation is that the batting averages in those situations vary little. Between the lowest and highest averages there is only a twenty-seven-point difference. Therefore, even in so-called pressure situations, most players are not hitting significantly worse. When a player like Derek Jeter is able to maintain a high batting average in all situations, he is performing how major league baseball players do as a whole. Statistics are manipulated to prove a point convincingly in this analysis of clutch hitting.

The other widespread use of baseball statistics is in Fantasy Baseball. The evolution of Fantasy Baseball has reached new heights within the last few years. In his exploratory study of Fantasy Baseball, “Gambling in a Fantasy World,” Bo J. Bernhard discussed the evolution of Fantasy Baseball and the game’s pros and cons. Like real baseball, Rotisserie Baseball began as an activity for a specific group of people. Baseball was originally associated with the burly American and Fantasy Baseball was tied to socially challenged “geeks.” Over time Fantasy Baseball became a mainstream game and resultantly, an enormous industry. Bernhard estimates that 1.65 billion dollars are spent on Fantasy Baseball annually.

There are several pros surrounding Fantasy Baseball. The entire game is numerically based and several individuals have pointed to it as beneficial on the cognitive level. Bernhard discusses one school’s pre-algebra course that encouraged students to participate in Fantasy Baseball leagues. In addition, the nature of Fantasy Baseball lends itself to in depth discussions over the Internet, further benefitting the learning process. While this argument might seem rather farfetched, similar learning connections have already been found to exist in video games.

A more obvious benefit of Fantasy Baseball is that the game provides an outlet for competition. Rotisserie Baseball was originally created to validate the common fan’s claim that he or she can run a baseball team better than actual managers. Through playing Fantasy Baseball people can not only test this theory, but can see whether their friends can succeed in the same objective. Since people are most likely participating in a league with friends, Fantasy Baseball also builds camaraderie. This is done through lengthy online discussions as well as to face-to-face interactions at venues like the workplace.

For all of its positives, several people see Fantasy Baseball as an unfortunate phenomenon. As Bernhard’s title suggests, Rotisserie Baseball is a form of gambling and resultantly, has some negative effects. Most leagues involve some type of monetary incentive. People will naturally become more consumed. He sites several factors that contribute to diagnosing a gambling problem such as preoccupation, loss of control, restlessness, and irritability, all of which can develop through Fantasy Baseball. Participants are often consumed by their team and spend hours on their computers, often instead of performing their jobs.Fantasy Baseball can become so engrossing that one office in Chicago displays a sign, which reads, “’No Rotisserie in company common areas.’”

Another perceived problem with Fantasy Baseball is that it takes away loyalties. In a letter to Sports Illustrated, one irate fan expressed his feelings stating, “’[Fantasy sports] are a plague. Because individual statistical gluttony is the objective, the fantasy player’s rooting interests are perverted (who cares who wins, as long as my guys get their numbers?), and the true virtues of sports – teamwork and sacrifice – are obliterated.’”Historian Christopher Lasch calls Fantasy Baseball the epitome of a “’culture of narcissism.’” Furthermore, one critic protested that actual baseball has been buried “under the manipulation of stats and the exertion of wills.” Whether the manipulation of statistics in baseball is beneficial is a matter of opinion, but there is undeniable evidence that statistics have profound effects on the game.

Statistics control decisions made by managers and executives in baseball today and are the center of entertainment for the fans. Beginning with Chadwick’s simple introduction of the box score in baseball, the value and use of statistics have steadily grown over the last one hundred and fifty years. Statisticians, writers, players, and common fans have all increased the value of numbers in baseball. There is evidence for both the usefulness and inefficiency of these statistics. While managers like Terry Francona value statistics in the decision making process, they still like to make moves based on other factors. Bill James admits he is frequently wrong and often raised questions for which he does not know the answer. On the other hand, the Red Sox have won two World Series titles since bringing James aboard. Although it often seems that figures have been calculated for every situation, people continue to find more innovate and detailed methods of evaluation. For example, Ron Antinoja, a fifty-year-old former software engineer, invented an elaborate computer program that could chart hot and cold zones of any hitter facing any pitcher, in any situation imaginable with a click of the mouse. After witnessing Antinoja’s innovation, Bob Bowman, the CEO of mlb.com, clunked his forehead on his desk in amazement, exclaiming, “’That’s the slickest fuckin’ thing I’ve ever seen in my life.’” As these innovations continue to be made, statistics will continue to hold the interest of baseball fans."