An Analysis of Minor League Development Paths

For years, Major League Baseball organizations and their fans have focused on their prospects. They wonder who will make it to the Majors, how productive they will be and when they can be expected to contribute at the Major League level. I attempted to answer these questions by looking at drafted players from prior years and examining their level reached by years of experience. Based on historical data, what can we expect from Minor League players going forward? I believe the data below provides useful information that shows league wide player development trends.


My population consisted of 8,748 players that were drafted and signed with their team from 2000 to 2009. I chose this period because it was one of the most recent time periods that allowed me to view almost every player’s full amount of team controllable years through the 2019 season. I then split the population into position players and pitchers according to the position listed on Baseball-Reference’s draft data.

Next, I took the level that the position player had the most plate appearances in for each season and assigned this level to the player’s corresponding year in his professional career. I did the same thing for pitchers, but I chose batters faced instead of plate appearances. I repeated this process for the first seven seasons of each player’s professional playing career.

I chose the level with the most plate appearances and batters faced instead of highest level reached because there are times throughout the season where a player may spend some time at an affiliate to fill the roster for a week or two due to an injury in the organization. Once the injured player returns, the promoted player will be sent back down to his original level. For this reason, I believe that spending most of the season at a level is a more accurate depiction of a player’s development level than choosing the highest level reached in a season. I decided to analyze the first seven seasons because that is how long a drafted player must wait until they can reach minor league free agency and the team no longer owns the player’s rights. Below is an example for 2002 draftee Denard Span to help understand the process of my methodology.

Denard Span was drafted by the Minnesota Twins in 2002 so his first professional season takes place in 2002 and his seventh season takes place in 2008. Span did not play any games in 2002 so his level is listed as DNP. DNP in this study signifies any season that a player did not play for an affiliated team in the United States. He then spent the entire 2003 season in Rookie ball. In 2004, he had 19 plate appearances in Rookie ball and 282 in A-ball, so we put an A in the Year 3 column. Span had 212 plate appearances at High-A and 304 plate appearances at the AA level in 2005 and he spent the entire 2006 season in AA as well, so we enter AA in the Year 4 and Year 5 columns. He then spent the entire 2007 season in AAA with 548 plate appearances. In 2008, Span had 184 AAA plate appearances and 411 Major League plate appearances. Therefore, we enter MLB in Year 7.

After finding the development path for each drafted player, I then found the year that each player debuted in the major leagues and calculated their WAR total for their debut season plus another six full years after their debut to simulate the amount of team control WAR. This assumption is not perfect because it does not consider a player’s actual service time and it may underrate players that were optioned back down to the minors for long periods of time. However, I believe this method is a decent facsimile for the value a player brings to an organization in his team-controlled years. Let us return to our Denard Span example. Denard Span debuted in 2008, so we sum his WAR totals from 2008 to 2014 and we find that he produced a total of 22.5 WAR in those seven seasons.

Overall WAR and Chance of Reaching the Majors

I have two goals I hope to accomplish with the tables in this article. The first is to show the average amount of WAR a player generates during his team-controlled years given his level assignment and experience. This information is color coded by quantity and is shown on the left side of each cell. Green represents a high amount of WAR and red represents a low amount of WAR. The second is to show the percentage of players in each cohort that have reached the Major Leagues at some point in their career. This figure is shown on the right side of the cell with a data bar. If a level and year combination did not have at least fifty players, I omitted them from the chart to avoid having small sample sizes misrepresent leaguewide tendencies. To find the average amount of WAR I decided to take the sum of WAR divided by the number of players that have reached the Major Leagues.

As expected, the higher the level and the less experienced a player is, the more WAR and the better chance a player has of reaching the Majors. This makes sense because if a player is performing well at their assigned level, they will be promoted to the Major Leagues quicker than the rest of the sample. The exceptions seem to be in years three and four where the average WAR is higher for players that sat out the season or played in Rookie ball than players who played in Short-season ball. This is most likely due to the small sample of players that were on a rehab assignment that eventually made their way to the Majors. Since I divided by Major Leaguers instead of total players, this allows one or two players to skew the WAR figure when very few players make the Majors in a sample.

This table gives us a good deal of information. However, we can learn more by splitting the population into different groups of draftees and analyzing the different development paths taken by drafted players.

WAR and Chance of Reaching the Majors for College Players vs. High School Players

The first difference I decided to look at was between college and high school draftees. College players are three to four years older than their high school counterparts, so it stands to reason that their development paths should be quite different.

The first thing that jumps out is that high school players take longer to reach the Majors than college players. High schoolers did not have at least 50 players reach MLB until Year 5. Meanwhile, 50 or more college players reached MLB starting in Year 3.

High school players also seem to have a more uniform start to their career than college players. The only playing level in our table for high school players is Rookie ball and the highest level in our year 2 sample is Low-A. Meanwhile, a college player’s career can range anywhere from Rookie ball to A+ in their first professional season and Rookie ball to AA in their second professional season.

I also find it interesting that high school players have a higher average WAR than college players. This could be because many of the best amateur players forgo college altogether to get a head start on their professional careers and this would create a selection bias in our data that skews toward high school players.

WAR and Chance of Reaching the Majors for Position Players vs. Pitchers

The next thing I wanted to investigate was the difference between position players and pitchers. Both groups have quite different jobs and it is possible that they could have radically different development paths.

The main difference between these two tables is the average WAR for position players at the Major League level is much higher than pitchers at the Major League level. This is probably because many drafted pitchers eventually end up in the bullpen where they are unable to accumulate as much WAR as a position player due to their limited playing time.

WAR and Chance of Reaching the Majors by Position and School Type

We have compared the differences between school type and position separately, now it is time to analyze each group of draftees by school type and position together. The four tables listed below are in this order: College Position Players, High School Position Players, College Pitchers and High School Pitchers.We should be able to use these four tables to determine which minor league players tend to have the best chance of making the Majors and how productive they will be if they do make it to the Majors. Teams may also be able to use this data to guide them in assigning players to a level for the upcoming season or even when to release a player who has not lived up to expectations but may have a higher perceived ceiling than his teammates.

Many of our observations from earlier are still true. High school players produce more WAR than their college counterparts, but they take several years longer to reach the Majors and the players that get promoted earlier in their careers produce more WAR.

The last thing I want to make clear is that these figures are all aggregates and they cannot be used to predict an individual players success. Just because a college pitcher makes it to AA in his second season, does not mean that he has a 62.61% of making the Majors or that he is expected to produce 3.7 WAR. It just means that similar players have had that amount of success in aggregate. However, I do believe that it shows realistic expectations for career development of drafted players and that it can be used to help teams make informed decisions about where to place players in their organization and create timelines for realistic windows of contention.


There are several conclusions that can be drawn from this study.

  • On average, High School amateurs that make the Majors produce more WAR than college players that make the Majors.
  • Position players produce more WAR than pitchers.
  • College players reach the Majors faster than high school players.
  • If a player reaches AAA, it is highly likely they will play in the Majors at some point. Almost every AAA cohort had at least 70% of their population make a Major League appearance.
  • The less time a player spends in the minors, the more WAR they produce.

Data Acknowledgments

All the minor league playing time data was obtained from and all the WAR figures were obtained from

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: