America's Pastime: Business Analysis

This project investigates how salary and performance of offensive players in Major League Baseball are linked. We believe this is an interesting problem because it is traditionally believed that professional athletes play with hopes of earning a high salary, yet it often seems a batter’s performance is not linked to their salary (Jensen). Therefore, it seems as if the link between a player’s performance and their salary is different than their true performance. Performing a statistical analysis of this conundrum will give us great insight as to if it is accurate to say that performance changes salary drastically. Studies that prior statisticians have done differ from this study because their studies focus on salary and team performance rather than on the performance of individual players (Jane). Our study focuses on salary and individual performance in the current season. While there is extensive data on both game performances in the MLB and salaries, we can contribute to the statistical community by comparing how salaries are affected by different performance indicators for randomly selected individual players. Essentially, our hypothesis is an examination into how a batter 's game performance affects salary. We expect that the better a player’s statistics are, the higher their salary will be.

The book Moneyball by Michael Lewis is about a former major league baseball player who became the manager of the Oakland A’s. It tells the story of how he led the team to success despite their low budget by using computer based analytics to draft players. With the help of Bill James, the Oakland A’s came up with a new plan based on statistics to draft players. He went after players nobody wanted due to their low budget and his new plan. Billy led the Oakland Athletics to a successive win seasons by changing the way he measured players. He abandoned the traditional 5 “tool” the other scouts used and adopted empirical analytics. The abandonment of the traditional assessment of

Baseball statistics are meant to be a representation of a player’s talent. Since baseball’s inception around the mid-19th century, statistics have been used to interpret the talent level of any given player, however, the statistics that have been traditionally used to define talent are often times misleading. At a fundamental level, baseball, like any game, is about winning. To win games, teams have to score runs; to score runs, players have to get on base any way they can. All the while, the pitcher and the defense are supposed to prevent runs from scoring. As simplistic as this view sounds, the statistics being used to evaluate individual players were extremely flawed. In an attempt to develop more

Today men and women live equal lives. They have the same opportunities when it comes to jobs, voting, education, and practically any other entitlement that comes to mind. According to the Constitution, equality for women came about in 1920. That was the year women received the right to vote, and in their eyes received the right to be seen as an equal instead of a lesser person. However, to the dismay of many women, that idea was not entirely true. Women were still viewed differently than men by the public. This difference in perception can be seen by focusing on the job opportunities for a woman through the 1920s and up until World War II. Before World War II women were not supposed to work in the factories, instead they were supposed to work at home. During World War II however, many workingmen were drafted into the army, thus creating the necessity for women to step in and work in the factories and other higher-class jobs. Thrusting women into the working class emphatically changed the ideology that men and women were not equal, however, I argue that the greatest change of mind was not created by the women working in the factories, but by the women who were elected to substitute in to keep the game of baseball afloat. The female athletes who played baseball during World War II were brought in as a last resort to save baseball, forced to fulfill stereotypes, and taught how to act, but were still persevered through all of those strikes

The game of baseball has been around for approximately 150 years and throughout its history there have been different genres used to discuss or write about the sport. The two genres are a blog post and a news article about win-loss projections for teams. Each genre will look at the sport and write about the projections in a different way because they have different authors, audiences, and purposes. The two different genres will also differ in the style and context because they have different reasons and goals for their writings. The blog post will attempt to prove how the preseason predictions made by the news article are unreliable. On the other hand, the news article will attempt to show how the predictions are still trustworthy. The genres

Everyone has a specific skill set that they are good at. Some people are good with numbers, others have a gift for writing. The same is true in sports. The Buffalo Bills are very good at losing and disappointing their fans, while the Patriots are fantastic at bending the rules and winning Super Bowls. In baseball, each team is built around a specific group of players in order to create the best possible chance to win the World Series. Some of the greatest players have created seemingly unbreakable statistics. Joe DiMaggio had a hit in fifty-six consecutive games. Barry Bonds hit seven hundred and sixty-two home runs over his twenty-two-year career. Statistics like these only come about once in a generation. Teams are comprised of various talent. Some are like Miguel Cabrera. Cabrera always has a batting average over .300 with at least 25 home runs. These types of players are considered great hitters. Other’s, like Stephan Drew, get a hit less than 20% of the time they have an at bat. Players similar to Drew’s skill set have a job because they are very good at defense and their value on defense out ways their value on offense to their specific team. Baseball is sport rich with statistics. Almost anything one can come up with, has a statistic. In the last ten years alone, top executives, such as Billy Bean, have constructed teams based on advanced statistics and have been fairly successful, like the 2002 Oakland Athletics. Other teams, like the Houston Astros,

During the research of this paper there were several discoveries about the inner workings about the great American past time of baseball that was brought to my attention. The realization of how players are selected requires a great deal of thought and ingenuity (Thaler & Sunstein, 2003). As a former ball player (softball player), the remembrance of selecting individuals to play usually meant picking the best hitters and fielder for the team. However, with the tremendous amount of revenue generated in the game of baseball the organization providing the highest salary usually determines the player’s team.

Batting average was the norm adopted by other baseball teams. But training for Oakland was focused on the player’s ability to obtain on-base scoring. The team relied more on selecting players by their on-base percentages. According to Sabermetrics model, teams always win with players having attained high on-base percentages.

My study proposes to examine the New York Times sports pages between 1997 and 2017 as a way of testing some ideas about the nature of the changes in the discourse about baseball as that discourse has evolved over the last 20 years. Although these ideas did not necessarily take hold in professional baseball circles until the 21st century, outsiders like Bill James have been promoting non-traditional baseball statistics as more accurate ways of describing the game since the 1970s, while in the 1990s Baseball Prospectus, a publication which debuted the PECOTA predictive baseball model developed by eventual data celebrity Nate Silver, began to spread these ideas to increasingly wide groups of baseball fans. Today, these ideas have widespread popularity, and the yearly Bill James Baseball Abstracts and Baseball Prospectus anthologies both have high circulations, while websites like FanGraphs, which approach baseball journalism from a statistical point of view, have significant daily readership (among them, yours truly).

MoneyBall, explored the Oakland A’s franchise under the management of Billy Beane, an ex-baseball prospect. This book displayed to the reader the misgrievances many pro scouts make when recruiting players, including; the exclusion of certain players when building teams, the wrong analysis of stats, and the use of conventional wisdom. This book explains how a poor baseball team went from a winning percentage under .500 to almost beating the richest team in baseball. The book is most accurately depicted by what the back of the cover articulates, MoneyBall is “The most influential book on sports ever written”.

Dasgupta’s paper, titled "The Overlooked Element: An Empirical Analysis of Team Chemistry and Winning Percentage in Major League Baseball," examined how salary disparity, the number of veteran players, the number of foreign-born players, managerial efficiency, and total payroll affected a team’s winning percentage from 2010-2015. He collected data concerning birthplace from baseball-reference.com and used this data to determine the percentage of international players on each roster for each year. This percentage was used as a variable in two regressions, shown in Figure 1, which described how several factors affect winning

With the advent of technology in baseball expanding with instant replay and newfound statistics to measure player success the MLB and their respective clubs are trying to find new ways to answer the question: How do measure one players worth from another? Is there one statistic by which we can measure performance or player worth across a specific league? There is a strong idea in baseball today that with Sabermetrics someone can only be held responsible if what they make a difference to their team (WAR: It Works | FanGraphs Baseball."). There are two specific ways to judge the extent to which a person made a difference to their team. The first way is to make an action-based contrast and compare the actual action a person took with alternative actions she could have taken (Gerstenberg). In the following modeling experiment the researcher will attempt to answer these questions and model the Sabermetrics, Wins Above Replacement, statistic to measure its effectiveness and compare to its monetary worth. This theoretical model of sabermetrics will give insight to how teams prepare for a players injury, a player who leaves the team or leaves via Free Agency and which players are underperforming.

Baseball is a great game to analyze from game theory perspective because of the scale of strategic decisions that are continuously made on the fields and each play. In every play, there are various players (baseball players, coaches, team managers and owners) with different goals and payoffs, and thousands of pitch-by-pitch decisions are made in course of an at-bat, inning, game, and season.

Major League Baseball is known as America’s favorite pastime, and MLB teams spend an extensive amount of money in the excess of a billion dollars with the ultimate goal to win the World Series. This learning team’s focus throughout this descriptive statistics paper is the MLB players’ performances, salaries, salary caps, and winning percentages. Though salaries will by no means be a trade for wins, the goal is to use the less experienced players and pay them a lower salary. Research has been done on whether or not player’s salaries and wins are connected.

and analyzing vast amounts of baseball data. Then came the boom in baseball players’ salaries: this dramatically