Diamond Plots and Diamonds In The Rough, Part 3

Building off of last week's post - where we moved the lens towards MLB farm system value, not just prospect count - let's take a look at z scores by organization and by year. Here, we'll run the same exercise as we did last week, creating a z score value (number of means above the standard deviation) but for each year, getting us 30 teams x 6 years = 180 observations of z scores. 

Critically, each z score is anchored to the season in question. That is to say, the value of farm system's hitting, pitching and total prospect count is benchmarked to the league-wide values from that year alone. I think measuring z scores within years like this would more accurately help us track population-level changes in prospecting. Normalizing within each year ultimately helps us make comparisons across years that reflect newfound understanding of valuation at a macro level. 

For instance, comparing the nominal values of SFG's 2020 hitting prospects ($191.5M) and Milwaukee's 2023 hitting prospects ($192M) is tough. While equal in present value terms, have we learned anything in the interim three years from a baseball-meta perspective that perhaps render these two present values not so equal? 

And who's to say what exactly - that's a topic for another time. For reference, though, Milwaukee's 2023 hitting prospect values z score is 0.77, whereas San Francisco's 2020 hitting prospect values z score is 0.7, making Milwaukee's slightly more valuable in the context of their respective years. 

Let's first call out a few notables from this exercise:  

1. Last week we talked about what an outlier Pittsburgh's 2024 pitching prospect value was, at more than 3 standard deviations above the mean. Well, it's even more impressive when you consider that across the 6 years, no other team had a pitching prospect value z score above 3, and there were only 9 team-seasons of pitching prospect value z scores above 2 across the entire timeframe! 
2. The nadir for an organization? The White Sox in 2022 at $61m, a full 1.9 standard deviations below the mean total system value that year. Without a single ranked player on the Fangraphs Top 100 prospects, it's hard to boast about value, but the Sox were particularly bereft amidst a class that has brought us names like Adley Rutschman, Bobby Witt Jr., Julio Rodriguez and Corbin Carroll. Don't write that 2022 Sox class off just yet, though - here comes Colson Montgomery! 
3. Finally, the most impressive run on the hitting side? Probably the 2019 - 2021 Rays, who put up three consecutive years of 2.5+ hitting prospect value z scores, coincidentally (not really) also the top 3 z scores on the hitting side across the study. Yes, Wander Franco makes up a huge chunk of that value. He was on track to live up to his generational hype, however, and this also fails to take into account other Rays success stories like Brandon Lowe, Curtis Mead, Josh Lowe, Vidal Brujan, and others. 

Full list of 180 z scores HERE in my GitHub. Anything stand out to you? Any other places you'd like to see me take the analysis? Please drop me a note in the comments! 

Next week we'll be back working with visuals more in depth, with a focus on plotting out the sum of z scores by organization across the time frame. 

Thanks for reading!

Code is HERE on my GitHub. 

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