Diamond Plots and Diamonds In The Rough, Part 4

Happy holidays to all! Let's celebrate with some data visualizations. 

Last week we took a step further into the world of z scores and prospect values. Examining the 2019 - 2024 timeframe with data from Fangraphs, we looked at the relative rank of each organization's class of prospects by year via z scores. Normalizing prospect values this way then helped us make comparisons across years, adding a new angle of analysis and helping us celebrate the very best of the best (and, at times, the worst of the worst...). That full table can be found HERE on my GitHub. 

Let's take that csv into the shop for an upgrade today. First, we'll sum up each of the z scores by organization, to provide a sort of "total prospect value" across the timeframe. These "Total Prospect Z Scores" give us a window into which teams were the most successful at developing prospects from 2019 - 2024. The higher an organization's cumulative z score, the more they outperformed their peers. 

It's a beast to get into one normal, human-sized PNG, so the (beautifully formatted) table can be found HERE.  It's in descending order for better perusing. 

What stands out? Well, the Rays are a machine, the Angels are slacking, and the warning light may be flashing for recent contenders like the Astros and Phillies. 

Now, there are some limitations here. Prospects do graduate, which mean that a prospect's value is theoretical more than anything. It takes the best organizations and a lot of luck to actually turn those potential dollars into actual production. Just because a team has been a few z scores positive in the past few offseasons does not mean they've actually turned that into real-life scores - like runs on the board! 

This also means there is inherently quite a bit of overlap in each organization's sample. Every 2022 prospect class will have a lot of player overlap with the respective 2023 class, and so on and so forth. And because the value of any individual prospect likely won't fluctuate extremely wildly year-over-year, especially as prospects get close to graduation, each year's class may already be pretty well accounted for based on the previous year's class. It would be interesting long term to look at z scores on a (three year?) rolling basis to account for this dynamic, but by no means do I think this means our current exercise is a non-starter. 

It also may be more instructive to view this in graph form. Below are the total prospect z score for 2019 - 2024 laid up in alphabetical order.

This does mask year-to-year variation, but more critically, I think it shows just how populated the middle is. Most teams are somewhere in the -3 to 3 z scores range on the plot above, which means (horrible, not orthodox math inbound) that in a given year these organizations are on average within 0.5 z scores of 0. In other words, perfectly average. For a team to break out of that middle (either way) calls for a huge success or failure. 

What say you? What does this say about your favorite team or their rival? Please drop me a note in the comments! 

Next week we'll look to see if these z scores can tell us anything about MLB success. Thanks for reading!

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Code is HERE on my GitHub. 

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Notes: 

Two-way (batter and pitcher) prospects are split (0.5/0.5) between the batter and pitcher tiers for valuation purposes.


From: 

https://thef5.substack.com/p/how-to-diamond-plots-in-r

https://blogs.fangraphs.com/an-update-to-prospect-valuation/

https://blogs.fangraphs.com/putting-a-dollar-value-on-prospects-outside-the-top-100/

https://blogs.fangraphs.com/how-the-draft-and-the-trade-deadline-affected-our-farm-system-rankings/

https://www.fangraphs.com/prospects/farm-system-rankings/2024-prospect-list 



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