MLB Data Warehouse

MLB Data Warehouse

Share this post

MLB Data Warehouse
MLB Data Warehouse
Early Draft Analysis: Projection-Based Values and Fades

Early Draft Analysis: Projection-Based Values and Fades

I compare my projections with ADP data to locate the top values at each position

Jon A's avatar
Jon A
Dec 02, 2024
∙ Paid
4

Share this post

MLB Data Warehouse
MLB Data Warehouse
Early Draft Analysis: Projection-Based Values and Fades
Share


Every fall, I tell myself I won’t get into these NFBC leagues, especially not before February/March when I have all of my research actually completed.

But I cannot help myself. Besides working my full-time job, taking care of my kids, being a good husband to my wife, working out, volunteering at my church, and writing all of the other stuff for this Substack, I have absolutely nothing else to do.

So if I’m going to do it, I might as well do it well. And if I’m going to do it well, I might as well share that with the paid subscribers to this newsletter.

What I have done for this post is to compare ADP rank with projection-based rank, and that will immediately pick out values and fades for me.

I have not made the 2025 JA projections public yet because there are so many tweaks that need to be made, but I’m still leaning on the first run of them in my drafts. I’ll go position-by-position here (hitters only because I don’t like to use projections nearly as much for pitchers) and show the top values and biggest fades.

Just remember. If you use this post against me in an NFBC draft, God will be angry with you.


Catchers

Targets:

  • Hunter Goodman: He’s on the Rockies, if you didn’t know that. He plays some first base and catcher and hit 13 homers in 224 PAs last year with a 29% K% and a 13% Brl%. He’s boom-or-bust, but the Coors Field thing is nice, and he makes for a power-upside second catcher in early drafts.

  • Patrick Bailey: He’s not much of a hitter (.636 OPS last year), but he’s now a Gold Glove winner behind the dish, so he’ll be in the lineup a bunch. Playing time is huge at the catcher position.

Fades

  • Connor Wong: Eight spots separate his ADP rank and my projection rank on him. He hit .280 last year on a .347 BABIP and .230 xBA. He’s primed for batting average regression, and the 6.3% Brl% and 24% K% aren’t inspiring much hope for a big power season.

This is too good to give away entirely for free! Subscribe today to get the rest of this post and everything else I’m doing here.

This post is for paid subscribers

Already a paid subscriber? Sign in
© 2025 Jon A
Privacy ∙ Terms ∙ Collection notice
Start writingGet the app
Substack is the home for great culture

Share