By Sanjay Pothula
Introduction
In this article, I wanted to create a review piece a little different from the typical analytics article.
In the sphere of Econometrics, there are many great journal articles that reflect on sports labor rates and labor productivity.
Although there are significant insights to the baseball industry in these articles, the problem with these highly technical Economics research analyses is that the language can be typically difficult to understand.
Thus, for this AriBall article, the focus will be on providing a proper translation on a great Econometrics piece called, Major League Baseball’s First Year Player Draft: A Natural Laboratory for the Study of Bargaining by Christopher Garmon.
The goal of Christopher Garmon’s study was to measure the various factors that affect the signing bonus of a player drafted in the MLB Draft.
Before getting into the empirical model that the researcher used, it is important to go over the economic principles in play that determine the drafting and signing process for MLB teams and newly drafted players.
This math might look scary, but do not worry too much about the math.
The important takeaway from this equation are that as the g(Xi) increases, Wi should decrease because, as the function of player characteristics increases, the player should feel more confident with choosing to sign a contract rather than choosing “the next best option” (Equation 1).
Now, with a simple model of player’s decision for signing an entry level MLB contract, it is time to apply this equation into the team’s decision making process for signing a draft pick.
The two variables Vij and Vij represent the decision making process for an MLB team during the drafting and signing process in accordance to the MLB Draft (Equation 2).
The best way to explain these two dichotomous variables is to present the Houston Astros’ tough decision to not sign their number one draft pick from last year, Brady Aiken.
Coming out of high school, Brady Aiken was drafted with the number one pick by the Houston Astros in the 2014 MLB draft.
Both sides had originally agreed to an agreement with a $6.5 million signing bonus. However, after Brady Aiken’s physical, the Astros felt that Aiken would soon need Tommy John surgery and lowered their original offer.
Ultimately, both sides failed to come to an agreement on an offer.
In the realm of this equation, Vij - Vij was evidently greater than 0 before Brady Aiken’s physical because the Astros had envisioned Aiken as a future ace for their club and had offered him a large sum of money.
However, after the failed physical, the difference between Vij - Vij decreased from its original value.
This points to the fact that the Houston Astros began to see value in the compensation received through not signing Brady Aiken, which is the number two pick in the 2015 MLB Draft.
In addition, by Brady Aiken choosing not to sign a significantly lowered contract, Vij - Vij became less than Wi because Brady Aiken chose to go for the “next best option”.
In this case, Brady Aiken opted to attend the IMG Academy to prepare for the 2015 MLB Draft.
The decision to opt to attend a baseball academy or, in most cases college, points to another intricate aspect to the MLB Draft.
This aspect is the differences in signing bonus potential between high school seniors, college juniors, and college seniors (Equation 3).
To sum up this equation, the bonus of a drafted college senior is represented by the function bij(0, Vij, Vij).
In this case, the 0 represents “the value of the next best option” for a college senior because drafted college seniors do not have the option to return to college, so MLB teams hold more bargaining power over signing bonuses. As can be learned from this economic theory, high school seniors hold a “Value of Next Best Option” greater than 0, which evidently means that they hold the most potential for the highest signing bonus compared to college seniors because of their option to head to college (Equation 4).
Empirical Model
In Garmon’s empirical model, he used MLB Draft data from 2003 to 2010. In the model, Garmon used signing bonus as the dependent variable and used a wide array of independent variables such as dummy variables for First Round Pick, Second Round Pick, etc. Slide, and other variables as well. However, for this review, we will only focus on the dummy variables (1 or 0) for high school seniors and college seniors.
From his analysis, Garmon found that high school seniors, on average, make $110,000 more than college juniors. While, college seniors, on average, make around $17,000 less than college juniors. In general, these conclusions are no surprise because they follow the economic theory as presented before (Equation 5).
As the researcher stresses throughout the paper, these bonus differentials play a huge role in whether an agreement can be reached between the drafted player and the team.
In a separate empirical model, Garmon used a dummy variable (1 or 0) to see the probabilities of high school seniors and college seniors signing with their drafted teams.
From his analysis, he found that high school seniors were 5.86% less likely to reach an agreement with their drafted team compared to college juniors.
While, college seniors were 3.83% more likely to sign with their drafted team compared to college juniors.
Thus, these conclusions play perfectly into the economic reasoning from above because this essentially means that high school seniors are more difficult to sign compared to college seniors based on signing bonus potential (Equation 6).
Conclusion
The important takeaways from Christopher Garmon’s journal article on the MLB Draft and Signing process is to understand the dichotomy of decision-making between MLB teams and newly drafted amateur players.
From the drafted amateur player side, these people are trying to negotiate the best contract for themselves, so understanding how teams value them and potential advantages from going to college is evidently important.
From the team’s perspective, they need to take into account those same factors, but also weigh the potential compensation from not signing the player as well.
This complicated decision-making process is most prominent when highly ranked players slide in the draft because of signability issues.
For example, in the 2012 MLB Draft, Mark Appel was projected as the number one pick in the draft as a college junior.
However, he had reportedly rejected a $6 million signing bonus from the Houston Astros, the holder of the number one pick in the draft.
Thus, Appel fell to the Pittsburgh Pirates, the holder of the 8th pick in the draft. Ultimately, Appel used his “Value of Next Best Option” bargaining leverage and returned to Stanford University for his senior year after rejecting a $3.5 million bonus offer from the Pirates.
As shown from this analysis, the drafting and signing process can be a back-and-forth chess match between MLB teams and drafted players.
However, by understanding the economic principles behind the whole process, much of the beauty in Major League Baseball is revealed and plays perfectly into the field of microeconomics.
References:
Much Thanks to Christopher Garmon for his work in the field of Econometrics.
1. Garmon, Christopher. "Major League Baseball's First Year Player Draft: A Natural Laboratory for the Study of Bargaining." Journal of Sports Economics 14.5 (2012): 451-78. Web. 20 May 2015.
2. McTaggert, Brian. "No. 1 Draft Pick Appel Signs with Astros." Major League Baseball. N.p., 19 June 2013. Web. 30 May 2015.
3. Oz, Mike. "Brady Aiken, Unsigned No. 1 Draft Pick, Announces He Had Tommy John Surgery." Yahoo Sports. N.p., n.d. Web. 30 May 2015.
NOTE: All statistics accurate as of 05/31/15
By Sanjay Pothula
AriBall.com
