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Building A Farm: A Summary

Posted By Mark Smith On April 10, 2013 @ 9:00 am In Daily Graphings | 13 Comments

We’ve spent the past few weeks taking a look at combined rankings for each organization, going division-by-division. I wasn’t really sure what I was going to find, but my goal was to take a look at the two main overall aspects of a prospect – his talent/reasonable ceiling and his risk of getting there – and see how farm systems graded out. The traditional 1, 2, 3 ranking system is fine because we’re ultimately looking at an educated subjective process, but a simple list doesn’t show the audience where the real gaps lie and where there’s negligible difference. My hope was to begin to approach a way to see these differences, and while there is certainly room for improvement, I believe it has led to some interesting results.

Averaged Publication Lists

Team BA BPro Sic Law FG BB AVG RANK
St Louis 1 1 1 1 1 6 1.83 1
Texas 3 2 4 9 2 2 3.67 2
Seattle 2 5 2 8 7 1 4.17 3
Tampa Bay 4 8 3 3 3 9 5.00 4
Minnesota 10 4 7 2 4 5 5.33 5
Pittsburgh 7 6 5 7 6 3 5.67 6
Houston 9 9 11 4 10 4 7.83 7
San Diego 14 3 6 6 8 11 8.00 8
Chicago (NL) 12 12 10 5 5 13 9.50 9
Miami 5 11 8 16 12 15 11.17 10
Boston 6 16 9 17 17 8 12.17 11
New York (NL) 16 10 12 14 14 7 12.17 12
New York (AL) 11 14 14 10 16 12 12.83 13
Arizona 8 17 13 15 13 16 13.67 14
Kansas City 18 7 21 11 11 14 13.67 15
Cincinnati 15 15 15 12 9 19 14.17 16
Baltimore 17 20 18 13 15 10 15.50 17
Los Angeles (NL) 19 21 19 18 18 22 19.50 18
Toronto 22 13 22 24 20 17 19.67 19
Cleveland 20 19 24 19 21 18 20.17 20
Washington 13 23 25 21 19 21 20.33 21
Colorado 21 22 16 23 26 20 21.33 22
Atlanta 26 18 27 20 22 24 22.83 23
Oakland 25 25 26 22 25 23 24.33 24
Philadelphia 24 24 20 27 24 28 24.50 25
San Francisco 28 26 17 26 27 25 24.83 26
Milwaukee 23 27 23 29 29 26 26.17 27
Chicago (AL) 29 28 28 28 23 30 27.67 28
Detroit 27 29 30 25 28 27 27.67 29
Los Angeles (AL) 30 30 29 30 30 29 29.67 30

The above chart is just an averaged ranking of the publications that I used for each prospect list. The “AVG” column is there average placement on these lists, and the “RANK” column is the list method of ranking.

There don’t seem to be any real surprises as you move down the list. St. Louis was ranked first by every publication but Bullpen Banter, and it has a pretty clear advantage over Texas and Seattle, who seem to have very fairly farm systems. Moving down the list, the next three are pretty close and can probably considered interchangeable in the 4, 5, and 6 spots. There seems to be a drop off from those systems to the next 3, and it drops off again to the next 3-7 systems. Baltimore seems to be a cut-off point for the upper half of farm systems, though it’s not the exact halfway point.

The bottom half starts with five teams that are pretty close together, and the next 3 after that follow suit.  Milwaukee, Chicago (AL), and Detroit are a bit worse than the others, and the Angels come in dead last by a substantial margin. The Angels grabbed the bottom ranking on 4 of 6 lists with Chicago and Detroit getting the others.

Putting Those Against the Averaged Grades and Risks

Team RANK Sys Gd Sys Rs 50+ 50+ Gd 50+ Rs 60+ 60+ Gd 60+ Rs
St Louis 1 51.000 2.333 20 54.250 2.550 4 66.250 1.500
Texas 2 53.417 2.833 27 54.537 2.926 6 64.167 3.000
Seattle 3 51.250 2.500 22 53.523 2.727 3 65.000 3.000
Tampa Bay 4 53.250 2.800 29 53.534 2.828 3 63.333 2.000
Minnesota 5 51.583 2.867 23 53.587 2.957 4 64.375 2.875
Pittsburgh 6 51.129 2.677 22 53.864 2.955 6 63.750 2.833
Houston 7 51.694 2.645 20 55.375 2.900 4 66.875 2.875
San Diego 8 50.500 2.633 22 52.500 2.818 2 63.750 3.000
Chicago (NL) 9 51.333 2.700 21 54.048 3.048 4 63.750 3.000
Miami 10 51.083 2.750 20 54.000 2.950 4 63.125 2.250
Boston 11 53.103 2.828 27 53.611 2.889 5 62.500 2.400
New York (NL) 12 50.530 2.788 25 52.300 3.000 3 64.167 2.167
New York (AL) 13 52.000 2.767 23 54.130 3.000 4 61.250 3.125
Arizona 14 50.152 2.727 22 52.614 2.818 2 66.250 2.000
Kansas City 15 52.667 3.100 27 53.519 3.222 4 65.625 3.250
Cincinnati 16 51.034 2.707 22 53.182 3.068 3 63.333 3.000
Baltimore 17 48.583 2.617 15 53.167 2.900 2 71.250 1.750
Los Angeles (NL) 18 50.000 2.467 19 52.895 2.842 1 62.500 3.500
Toronto 19 52.222 3.130 22 53.864 3.295 5 61.000 3.800
Cleveland 20 50.081 2.758 20 52.750 3.025 3 64.167 3.000
Washington 21 50.645 2.823 23 52.826 3.065 3 65.000 3.333
Colorado 22 49.917 2.717 22 51.932 3.023 2 62.500 3.250
Atlanta 23 50.268 2.982 20 52.375 3.025 1 60.000 2.000
Oakland 24 49.907 2.833 17 52.941 3.059 1 65.000 2.500
Philadelphia 25 50.000 2.767 19 53.158 3.000 1 60.000 3.500
San Francisco 26 49.167 2.617 18 52.222 2.750 1 62.500 3.000
Milwaukee 27 50.083 2.700 21 52.500 2.857 1 60.000 2.000
Chicago (AL) 28 47.742 2.710 14 51.071 3.071 1 60.000 3.000
Detroit 29 48.250 2.900 16 51.563 3.188 1 62.500 2.000
Los Angeles (AL) 30 47.333 2.817 16 51.094 3.188 1 62.500 3.000
Average 50.664 2.750 21.1 53.098 2.965 2.8 63.547 2.730

This is the part about which I was very curious. The publications rank the systems, but how do they look when broken down? Again, the grades and risks are only based off of two lists – Baseball America and Baseball Prospectus – but they give us a decent overall look. Just for giggles, let’s look at how each column correlates with the overall ranking from the above section.

Sys Gd Sys Rs 50+ 50+ Gd 50+ Rs 60+ 60+ Gd 60+ Rs
Correlations -0.731 0.288 -0.609 -0.758 0.507 -0.744 -0.440 0.145

When looking at the “grade” and number of prospect columns, we expect to see negative correlations because, as the ranking goes up, we expect to see lower grades and number of prospects. When looking at the “risk” columns, we expect to see positive correlations because the risk will theoretically grow as the ranking grows.

The highest correlation belongs to the 50+ grade – the averages of all 50+ grade prospects in a system. This grade looks at the quality of the prospects who are more likely to be average major-league players, and these are theoretically the most likely to make the majors in some capacity.

The next highest was a bit of a surprise to me – the number of 60+ grade prospects. What evaluators seem to be valuing is simply having these higher ceiling players in the system, and as you can see, the risk of these players doesn’t seem to matter that much as it nets the lowest correlation. Higher ceiling prospects are so valuable because they are the players around which a team can build a franchise. Some will certainly bust, but the ones that make it through the attrition can become core contributors, while the lower-ceiling prospects likely won’t have the same impact on the organization. Having more is obviously a good thing as those AT&T commercials tell me.

It is important to remember what the correlations are comparing. They are comparing what the publications seem to favor when ranking the overall farm systems, not the effectiveness of each column. Other research will need to be done into whether or not they favor the correct things, and that future research is one of the reasons I started this project. It’s a starting point. What really is more valuable between ceiling and risk? What types of systems flourish? Should a team sell out for ceiling, or is there a certain degree of risk that’s not worth taking? And do teams have a particular strategy, and how effective is it?

I don’t have the answers to these questions at the moment, but I hope that I have begun the process in a valuable way. Hopefully, more lists will begin to note the overall grade and risk of each prospect because more grades will help even out the outliers and give us a better measurement. If anyone has any comments or suggestions on how to improve this project for the future, please leave a comment.


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