The Trade Deadline: Breaking Down the Data (Part II)

Part I: The Data on Prospects

In the first part of this series, I laid out the data. Before I start to analyze it, some things need to be understood.

  1. This is not a scientific study. One data sample was used. In a real study, several samples (prospect lists) would be used. The data is limited, so the data is biased and flawed. This is just a snapshot to understanding, and not to be seen as truth.
  2. The classifications of star, All-Star, wash out, etc. were measured subjectively by me. In a real study, it would be measured objectively using some measure such as wins above replacement.

With all of that said, it’s time to look at the data.

 

STAR

A-S

AVG

-AVG

WASH

Top 25

24%

24%

16%

16%

20%

Top 50

16%

20%

16%

24%

20%

Top 110

9.1%

12.7%

20.9%

33.6%

19.1%

Top 26-50

8%

16%

16%

32%

20%

Top 51-110

3.3%

6.6%

25%

41.6%

18.3%

This is the data, laid out on a chart of percentages. Players were ranked into five categories (plus one other category for players I didn’t feel comfortable ranking, which is why the percentages won’t add up correctly) based on their performance to date, so future potential doesn’t matter. Each cell breaks down the percentage of that type of player found in each part of the data set.

The Top 25

Obviously every team wants their prospects to be in the top 25 of baseball, but what does it really mean to be in that group? According to this sample, it means a lot.

Players in the top 25 have a 64% chance of being an average regular or better and a 48% chance of being an All-Star. That’s basically a 2/3 chance to get a regular and a 50% chance to get a All-Star! This makes it easy to see why players in the top group are so coveted.

With that being said, one third of players still wind up as bench players or worse, with 20% seeing extremely limited or no time in the major leagues.

The Top 50

Things start to break down after the top 25. The chance of finding a star drops by 8% and finding an All-Star by 4%. Below average players are found 8% more often. Average and wash out players are found just as often in the top 25 though.

But if we break it down by just the next 25 (prospects 26-50), it gets ugly fast. Only 8% of players ranked in the group become stars and 40% of prospects become regulars at the major league level. That’s down by 16% for stars and 24% for regulars!

That 24% found their way to the below average pool, which doubled in size.

The Top 110

This is where things go into free fall. Only 9% of the players in the top 110 prospects become stars and 43% become every day players. Below average players are found extensively now, as one out of every three prospects on the list becomes one.

Things look even worse when you take the top 50 out of the equation. Only 3% of players become stars, and 10% overall become above-average regulars, dropping by more than half from the pool of 26-50, and 38% from the top 25.

One out of four from the bottom of the list become starters while 41%  are below average. The chances of getting a below average player or worse go from 36% in the top 25 to 60% in the bottom 60, a 50% uptick.

Confirmation(?)

More data is needed for this study to have true merit, clearly. But we can take a glimpse at other top prospects lists to see if the trends seem to match what happened in this 2007 list.

Looking at Baseball America’s archives of top 100 lists, I chose the 2003-5 lists as quick samples. In those three lists, 37 stars were found, making up 12.3% of the lists. Of those 37, 20 were in the top 25, making up 54.1% of the stars. Seven (or 21.6%) were found in the next 25 players (26-50). The remaining 24.3% were found in the bottom 50, or to break it down more evenly, 16% in the pool from 51-75 and 8% from the last quarter of the list.

This breaks down to the following percentages:

26.6% chance to find a star in the top 25.
9.3% chance to find a star in the pool from 26-50.
6% chance to find a star in the pool from 51-100.

This is fairly consistent with what the data found in 2007. What does it all mean? That’s for next time.

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