Prospects are the lifeblood of any baseball organization. They have the ability to provide large amounts of value for their team while making a fraction of what they could earn on the open market. This provides a huge competitive advantage for teams that have a superior player development system. Every organization has a different plan for their prospects and the purpose of this research was to attempt to determine which development plan yields the most production in a team’s cost controlled years for each group of players.
The first step in gathering the data was to find every hitter that debuted from 1995-2009. I stopped at 2009, because this covers most of the prospect’s cost controlled years. I chose to start in 1995, because it gave me a big sample size and I got to avoid the strike year of 1994. Next, I omitted anyone who debuted at the age of 29 or older. I did this, because players that are over 28 are usually not considered prospects and their clubs would not consider them to be future building blocks for their organization.
The final step was to eliminate anyone who did not exceed their rookie limits. I decided to omit these players, because any player that cannot amass 130 at bats in their career was probably never considered a serious prospect. If they were, at least one team would have given them more opportunities to earn a starting job.
To determine a player’s production during his cost controlled years, I found when every player exceeded their rookie status and added the next five years of WAR to their total. If the player had previous major league experience prior to the season they lost their rookie status, I included those numbers as well. For a player’s minor league plate appearances total, I included all of their plate appearances from the start of their professional career up to and including the year they lost their rookie status.
I then broke up the data by player groups. I split up the data by players who attended college, American born players that did not attend college and international born players that did not attend college. Throughout the rest of this article, I will simply refer to these groups as college players, high school players and international players.
Next, I partitioned the data by minor league plate appearances. I decided to split the plate appearances into groups of 500. I chose this amount of plate appearances, because it is a nice proxy for a full season of production and it splits the data into a fairly even distribution of players among the groups.
I’ll start by giving a simple overview of total player production over their cost controlled years. The table below shows the median WAR for each grouping. I decided to use median instead of average throughout this article, because the WAR measurement is right skewed instead of normally distributed.
Median WAR for All Players
As you can see in the table above, college players need the least amount of plate appearances to produce a high level of WAR, but there is a sharp decline in production when a college player amasses over 2500 plate appearances. It makes sense that this player group is the quickest to develop, because they have had several more years of amateur competition to help hone their skills for professional baseball. This should create a smoother transition period for these players and reduce the amount of plate appearances needed to become a valued member of the major league club.
High School Observations
Unlike their college counterparts, American high school players take an extra 500 plate appearances before they reach their peak value of 15.4 WAR. However, high school players also have a wider range of success than either college or international players. High school players also produce more than the other two groups of players. This result may seem counter-intuitive, since it is commonly accepted that high school players are riskier prospects than college players. It is important to remember that this process does not account for all of the high school prospects that never receive an at bat in the majors. We therefore create a selection bias where we only look at the players that were good enough to make it to the majors in the first place. This means that if a high school player is good enough to make it to the majors; he’s probably going to be a productive major leaguer.
The international player group offers the least amount of production. I believe there are several factors that contribute to this result. One of the main factors could be that many of these players have not played as much organized baseball as their counterparts. I also think that there could potentially be a language barrier issue that makes it more difficult for an organization to teach foreign players as opposed to their English speaking teammates. Of course that conclusion is just pure speculation on my part, but I believe that it is a reasonable assumption to make.
Total Player Summary
As the table above shows, the longer a prospect is in the minor leagues, the less chance they have of making an impact in the major leagues. This makes sense, because if a prospect is outperforming everyone in the minor leagues, they will be called up much sooner to help the major league club than everyone else. This leads me to believe that this table may not be the most informative for every minor leaguer. Perhaps, if we segment the data between Baseball America’s top 100 prospects and every other prospect, we will get a more accurate depiction of minor league development. It is essential to remember that the more we split the data, the less accurate our individual values may be. Therefore, we should not take the numerical value of WAR for each grouping too seriously. It is more important to take an overall view of the values in the tables below before drawing any conclusions about player development.
Median WAR for Top 100 Prospects
Top 100 Prospects Summary
Yet again, we see that college players develop the quickest and that high school players take a little longer to develop. College players also have a quick drop in production after 1000 plate appearances, but they still yield the highest production of the three groups. International prospects are a bit of a mystery here. There does not seem to be a pattern in their production. I assume this is because there are major differences in baseball development between South American prospects, Japanese prospects and Canadian prospects, and any other nation’s prospects you can think of. In the future I may revisit this issue, but for now I’ll have to make do with what I have.
Median WAR for Non-Top 100 Prospects
Non-Top 100 Prospects Summary
As expected, we see a dramatic drop in overall WAR across the board. This means that Baseball America is usually correct when identifying the most impactful future major league players. Kudos to you Baseball America. We also observe that these groups of players develop a bit more slowly than their more heralded prospects. These college players continue to peak early, but they are still 500 plate appearances in development behind the top prospects. High school players take even longer to develop now with a peak of 2.8 WAR in the 2001-2500 plate appearances group as opposed to 15.4 WAR in the 1001-1500 plate appearances group for the top high school prospects. International players are much more consistent in this table than the previous one. Unfortunately, they also have the worst total median WAR of 0.1.
So let’s do a quick recap. Usually the less time a player spends in the minors, the more productive they will be in the majors. High school prospects offer the most production, while international prospects offer the least production and college prospects fall somewhere in-between. We also observed that college prospects develop the quickest, high school prospects develop a little slower and international prospects are a bit of a mixed bag. I attributed this to simply combining all foreign born players into one group instead of by nation or continent. I hope this article has been informative and that it provides some guidance on when teams should consider calling up their most prized assets.