Subjective and Objective Data in Moneyball

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.

Moneyball, the story of a dynamic change agent who rallied a small group of undervalued professional baseball players and executives to overturn convention and rethink how Major League Baseball (“MLB”) was managed and played. Its really a book about hustlers. Moneyball consecrated the notion that its noble to win inexpensively, but believe its good to stay a cheap baseball club, because of their fat annual revenue-sharing check they get at the end of the year. Michael Lewis wrote an un-organizational confusion, his misunderstanding of baseball, to his constant interruption of financial and statistical talk, that turned interest in the book away from many.

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

Teams with large payrolls routinely win at a higher rate than teams who cannot afford to spend the massive amounts of money other teams do. For example, in the last fifteen years the New York Yankees and Los Angeles Dodgers, two teams which regularly are among the highest spending teams in baseball, won on average 94.7 and 86.8 games respectively. By comparison, the San Diego Padres and the Kansas City Royals, two teams who are not able to compete financially with teams with deeper pockets, won an average of 77.1 and 71.6 games respectively in that same time span (Major League Baseball). This disparity in season wins is a direct cause of Major League Baseball’s lack of a salary cap. Over the course of a 162 game season, teams with higher payrolls, and therefore better talent on their roster, will prevail more often than

MLB teams are finding new innovative ways to use analytics, one way is to use the statistics for a more effective way to evaluate free agents. “Astros employed an analysis based on the TrackMan system to acquire an unaccomplished pitcher called Collin McHugh, because of his fast-spinning curveball” (“Every Step They”). “They then told him to throw that pitch far more often during the next season, and he blossomed into a star” (“Every Step They”). General Managers and coaches can use these analytics to scout areas they have never scouted before. Analytics gives teams more resources and more assistance to evaluate players. “For example, by comparing the number of strikes called for a catcher in relation to every other catcher in the league, the data can illustrate how good any one catcher is at getting umpires to call strikes” (Nadler). “Additionally, general managers and scouts can use

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

Jayson Stark, ESPN columnist, presents an interesting argument of the downfall of baseball after free agency. He uses sarcasm and slight humor to introduce the reader to the topic of free agency and uses the argument style of comparison and contrast to predict what today might have held had there been no free agency. But within his column, player agent Tom Reich states, “The people who criticize free agency to easily today don’t realize how bad baseball was twenty-five years ago” (Stark). It is Stark who realizes that the talent of the game has improved, but the overall passion in each player may have decreased.

Therefore Billy Beane decides to set an unconventional strategy in order to be able to compete with other wealthy teams “out there”. His goal setting is based on the strategy he sets for his game in what he calls “an unfair game”. Manager Billy knows that decreasing cost is the main concern of the top executives of his team. The main shareholders and stakeholders have set their goals based on their conservative approaches. To be more specific, the top manager of Oakland Athletic is not willing to take any risk in order to pay more money to recruit better players.

The development of sports from their early stages, their metamorphosis and evolution to their current form and status is one of the most interesting areas of study. Unfortunately, most writers on such subjects only concentrate on the sport itself and players without exploring other ulterior factors that influence the development of a sport such as the emotional, economic and social environment. The book, Playing for Keeps: A History of Early Baseball by Warren Goldstein is one of the few that have managed to avoid this perennial mistake. This paper is a review of the book,

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.

The A's recent success is attributed to the innovative approach taken by Billy Beane in assembling a baseball team with a very limited amount of financial resources. Billy Beane has built a successful ball club because he has found an efficient and cost effective way of measuring baseball talent thus essentially creating a loophole in this unfair game because winning percentage is a result of talent not

Michael Lewis’s Moneyball is a fascinating story about a small group of undervalued professional baseball players and executives who had turned themselves into one of the most successful franchises in Major League Baseball. The underlying question to this story is where the real discussion should begin. That question is: how did one of the poorest teams in baseball, the Oakland Athletics, win so many games? This question can lead into a series of discussions regarding strategy or luck, but the real answers can be found in the leadership of the organization. This leadership is found in the form of

Sabermetrics is a systematic statistical approach in evaluating teams and players. Based on this science it was found out that this basis for judging the performance of the player should be on-base percentage. The Oakland A’s recruitment would prioritize college players rather than high school players. This was due to the fact that college players have already played more games against better competition. Beane was convinced with the fact that “a young player” is not what he looks like, or what he might become, but what he has done. The bottom line is what the player has produced in college. Beane and DePodesta believed that they could forecast future performance of college players more efficiently than high school ones.

Do Major League Baseball teams with higher salaries win more frequently than other teams? Although many people believe that the larger payroll budgets win games, which point does vary, depending on the situation. “…performances by individual players vary quite a bit from year to year, preventing owners from guaranteeing success on the field. Team spending is certainly a component in winning, but no team can buy a championship.” (Bradbury). For some, it’s hard not to root for the lower paid teams. If the big money teams, like Goliath, are always supposed to win, it’s hard not cheer for David. This paper will discuss the effects of payroll budgets on the percentage of wins for the 30 Major League

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.