c 2014 RYAN XAVIER PINHEIRO ALL RIGHTS RESERVED EFFICIENT FREE AGENT SPENDING IN MAJOR LEAGUE BASEBALL A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Ryan Xavier Pinheiro May, 2014 EFFICIENT FREE AGENT SPENDING IN MAJOR LEAGUE BASEBALL Ryan Xavier Pinheiro Thesis Approved: Accepted: Advisor Dean of the College Dr. James P. Cossey Dr. Chand Midha Faculty Reader Dean of the Graduate School Dr. Stefan Forcey Dr. George R. Newkome Faculty Reader Date Dr. Nao Mimoto Department Chair Dr. Timothy Norfolk ii ABSTRACT During the 2012-2013 offseason, the Cleveland Indians signed a number of high pro- file free agents. Our goal is to determine whether these free agent signings were efficient. We will focus on Michael Bourn and Mark Reynolds for our paper, though our methods would easily apply to other free agents. To accomplish this we use statis- tical analysis to predict each player’s future performance, and we use game theoretic models to analyze the efficiency of the contracts. iii ACKNOWLEDGEMENTS Thanks to my parents, my sister, my extended family around the world, and all my friends for the support and encouragement you have always offered me. I would never have made it to this point without you. Thanks to my professors as well for challenging me intellectually and inspiring with your passion. A special thanks to my advisor, Dr. Cossey, for mentoring me throughout the process of this thesis. It has been more than a pleasure. Lastly, thank you to the Cleveland Indians. Following the Tribe has been my greatest hobby ever since I was a kid, and I was able to discover my passion for numbers and statistics through this hobby. I hope that the research done in this study will be useful to the organization at some point in time. iv TABLE OF CONTENTS Page LISTOFTABLES................................. vii LISTOFFIGURES ................................ viii CHAPTER I. INTRODUCTION............................... 1 II. USING PLAYER FAMILIES TO PREDICT FUTURE PERFORMANCE 8 2.1 Player Families and Similarity Scores Discussion . 8 2.2 BuildingofRegressionModel . 16 2.3 Obtaining Predictions Based on Regression Model . 23 2.4 Comparing Our Technique with Standard Similarity Scores Technique 26 III. PLAYER VALUE AND GAME THEORY . 29 3.1 EarnedValueFormula.......................... 29 3.2 ModificationtoEarnedValueFormula . 31 3.3 DevelopmentofGameTheoryModel. 32 3.4 Applying Double Auction Model to MLB Free Agency . 35 IV.CONCLUSION ................................ 42 4.1 ActualResultsfrom2013 . .. .. 42 4.2 Limitations................................ 45 v 4.3 FutureResearch ............................. 45 BIBLIOGRAPHY ................................. 47 vi LIST OF TABLES Table Page 2.1 Vladimir Guerrero Similarity Score Example . 11 2.2 MichaelBournFamilyWARAverages. 18 2.3 MarkReynoldsFamilyWARAverages . 19 vii LIST OF FIGURES Figure Page 2.1 MichaelBourn’sRegressionModel. 20 2.2 MarkReynolds’sRegressionModel . 21 2.3 Michael Bourn’s Regression Model Residual Plots . 22 2.4 Mark Reynolds’s Regression Model Residual Plots . 23 2.5 Michael Bourn Family Autocorrelations . 24 2.6 Mark Reynolds Family Autocorrelations . 25 2.7 Mark Reynolds Family Regression Model Using Our Approach . 27 2.8 Mark Reynolds Family Regression Model Using Standard Similarity ScoresApproach .............................. 28 3.1 MichaelBournSalaryHistory . .. .. 37 viii CHAPTER I INTRODUCTION The salary disparity between small-market and large-market teams in Major League Baseball is a major issue that has come under the spotlight in recent years. General Managers and the front offices of every Major League Baseball team are constantly looking for new ideas and ways to improve the efficiency of how to run their ballclub. This ranges from selecting the right players in the MLB First-Year Player Draft, to making smart trades that improve the team, to spending the right amount of money on the right players during free agency. We will be focusing on free agency and the efficient spending of money as our topic under investigation. We will perform a case study to help us examine this topic. Specifically, we will be examining the 2012-2013 offseason of the Cleveland Indians in terms of free agency. The Cleveland Indians are a small-market ballclub that has been notoriously stingy in recent years when it comes to spending money on free agents. However, during the 2012-2013 offseason this perception started to change as the Indians added four free agents to their squad on major league contracts. Two of these free agents were big-name players and signed to large multi-year deals. The major question we will be trying to answer in our study is whether or not the Cleveland Indians efficiently and effectively spent their money during the 2012-2013 offseason. 1 This is an important question to answer because small-market teams have very little room for error when they spend their money. Small-market teams simply cannot afford to tie down large amounts of money to the wrong players for a prolonged period of time. This puts the organization as a whole in a bind, and makes it difficult to make subsequent transactions to significantly improve a team’s roster. The past 10 to 15 years have seen a significant shift in the approach of MLB front offices. Teams have shifted to mathematics and analytics to help determine the optimal ways to add the right players and spend an efficient amount of money. There are many different approaches that teams have attempted in order to determine whether or not money has been efficiently and effectively spent. We will be developing our own approach to determine this by using the Cleveland Indians as a medium for our analysis. The approach that we will take can be applied to any team, and can be a valuable analysis tool for small-market teams in particular. The new-age thinking of using mathematics to run a MLB front office has led to many publications regarding player valuation and front office efficiency over the past couple of decades. One of the more well-known books describing the mindset and thought process behind using analytics in baseball is Moneyball by Michael Lewis. Lewis describes the story of Oakland Athletics General Manager Billy Beane trying to build a successful small-market baseball team while spending the least amount of money possible. Beane decided to invest in cheaper players that were able to play good defense and post a high on-base percentage [1]. While Moneyball does not show the in-depth mathematics behind front office decision-making, it does provide 2 some framework for our study and some motivation as well. The ideas of efficient spending and optimization of player value while minimizing costs were two driving factors behind many of the decisions that Beane and the Oakland Athletics made. Accurate player valuation plays a large part in achieving efficiency while spending money. The Book on The Book by Bill Felber develops a formula for a player’s Earned Value. The formula simply indicates how much the player is worth in a dollar amount. We will be discussing and using Earned Value more thoroughly later. The player valuation study completed by Felber simply compares players’ Earned Value to what they really earned. The conclusion was that the vast majority of big-name free agents are highly overpaid, while young players who have yet to experience free agency can be a major bargain for teams [2]. The study does not discuss the negotiation process or efficient spending in depth. Lewis, Sexton, and Lock (2007) did a thorough study of organizational effi- ciency in the front office. Data envelopment analysis was used to help measure the efficiency of each MLB team. Next, the authors used logistic regression to determine whether teams were competitive or noncompetitive, and finally used the Gini Index to determine the minimum Total Player Salary (TPS) to be competitive and the max- imum TPS a team could spend without overspending. The authors find that teams with a large market size have rarely ever been noncompetitive due to low TPS. The authors also find that teams that play in large markets were more likely to overspend on free agents than small-market teams. Again, this study does not consider the bargaining process during free agency which does have an effect on whether a team 3 overpays for a particular player along with the amount spent on the player as well. One of the goals of our study will be to take this bargaining process into account. This way we will be able to simulate the entire free agency process with more accuracy. Rockerbie (2009) focuses on the negotiation process that takes place during free agency in baseball. Rockerbie studies the impact of supply and demand of free agents in Major League Baseball. The author uses an auction model of free agency with multiple bidders to examine the impact of supply and demand. The author also uses a regression model to help determine a player’s salary. The author finds that a greater supply of free agents at a given position can lead to a lower salary in general. Thus, it might be beneficial for potential free agents to defer free agency until the supply is lower at their given position. The author assumes a simple auction in this study, which limits the effect of negotiating from the free agent’s party. We will be using a double auction model in our study. Baseball Prospectus published their book Baseball Between the Numbers in 2006. A chapter in this book is devoted to a case study analyzing the free agent moves of a front office, as we will be doing later on. Jonah Keri, the author of this chapter, examines the transactions made by Wayne Huizenga, the General Manager of the 1997 World Champion Florida Marlins during the Marlins’ rise to the top.