Less-Heralded Hitting Prospects I Like in 2024

Hey there, and welcome to the last edition of my data-driven look at some mid-tier hitting prospects I like more than the industry consensus. It feels weird, almost funereal, to start this article by mentioning that the series is ending, but that’s just how it is. This will be the fourth installment of my variably named Prospect Week contribution. In it, I use data and a big pinch of intuition to point out some hitters who I think have a good chance of sticking in the majors, even if they’re not your average Top 100 type.
In the past, I’ve done acceptably well at this; I don’t think it’d be fair to say that I’m great at it, but I’ve come up with my fair share of interesting players using this process. In looking through my past lists, I feel good about the process that led me to some guys you’ve heard of (Miguel Vargas and Ezequiel Tovar are probably my biggest hits so far, but I’ve also gotten some role players, and both Gabriel Moreno and Alejandro Kirk performed incredibly well by my model, though I didn’t end up including them in a list thanks to their pedigree) and plenty you haven’t.
What’s so hard about this project? The obvious thing is that my methods are archaic. I’m using some sorting techniques that are still reasonably current. K-nearest neighbors and multiple binary logistic regressions are still my two favorite techniques, and I think they both still do what I want them to. These approaches aren’t state of the art in statistical analysis, but they’re not particularly far from it, especially when you take into account that I’m a baseball writer instead of a data scientist. Read the rest of this entry »