Document Type

Honors Capstone Project

Date of Submission

Spring 5-1-2013

Capstone Advisor

Rodney Paul, Professor

Honors Reader

Michael Veley, Director & Chair

Capstone Major

Sport Management

Capstone College

Management

Audio/Visual Component

no

Capstone Prize Winner

no

Won Capstone Funding

no

Honors Categories

Professional

Subject Categories

Sports Management

Abstract

In 2003, Michael Lewis published Moneyball: The Art of Winning an Unfair Game, which forever changed the finances and economics of baseball. It began a movement towards using advanced statistical analysis to determine the value of baseball players, in order to build a roster that will win the most games at the lowest cost. The Moneyball movement has resulted in a multitude of new statistics to try to drill a player’s value down to one number that represents his marginal revenue product, or his individual contribution to the team’s success.

Player salaries are typically the largest cost for Major League Baseball teams. Players often get paid millions of dollars because there are so few people who have their athletic abilities and skill sets needed to succeed in baseball at the major league level. The average salary of Major League Baseball players in 2012 was over $3.2 million (Associated Press, 2012). It is of the utmost importance for Major League Baseball teams to efficiently spend their money on players in order to win games at the lowest possible cost.

The biggest factor that determines how much a player will be paid is his production on the playing field. The better one plays, the more he will be paid. However, there are many other factors that affect how much players are paid that are often overlooked. This project looks at many other factors, aside from a player’s talent and production levels, that may influence how much he is paid.

This study used linear regression analyses to isolate relationships between player salaries and a multitude of different factors which may have significant relationships to salaries. I have used online websites and databases to gather contract data and player performance data for a time period of one decade. The data includes a sample size of 761 player contracts signed between the 2002-2003 offseason and the 2011-2012 offseason. The project includes statistical breakdowns for hitters only, pitchers only, and all players combined, in order to gain the best understanding of what is actually impacting player contracts, and which kinds of contracts are being affected.

I have concluded that the impact of agents can be quite significant and large, although varied. Furthermore, I have uncovered several strategies that agents can use to maximize the salaries that they negotiate for their clients, like trying to position clients to sign contracts in December. I have also analyzed practices of teams to try to find the best value players at a given talent level, looking at the teams which have done so successfully.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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