Since most of the conversation lately seem to have zigged towards the Nolan Gorman question and somewhat the Riley O’Brien question, I decided to zag in another direction. My curiosity? Of the minor leagues prospects we’ve been watching, who has the most interesting pitch shape metrics (ie. the under the hood stuff)? We seem to be far enough into the season to have built up some stats that can stand up to Small Sample Size (SSS) scrutiny. Since I do the daily down on the Farm Reports, I see the various pitcher usage and line score results every day. That has made me curious about some things that might be going on beyond the line score.
That real-time curiosity met up with a longer-term, nagging deficiency in my knowledge set. It goes like this: Every so often as prospect watcher like @KareemSSN will post an interesting tidbit on a pitcher with stuff I find really cool. He is pretty good at explaining things, but one of things that has frustrated me is I can look at a chart like this and lack the context of what is good, what is bad and what is irrelevant and I have to re-remember all that and I can’t find a reliable source for reference. So I set out to build my own reference, so when something like this pops up, I can open my reference card and interpolate if an SI spin of 2038 with an HB of 13.7 is good, bad or irrelevant. In this case, it’s not great, but very relevant to gauging a Slider’s potential effectiveness.
I’m going to start with a set of numbers similar to what is above, although I can’t help myself and add a few and delete some others. I’m going to pull all the pitch data for our Low-A and AAA pitching prospects and see who has elite level metrics in any of the categories. I will be dropping VREL, Ext and Chase and add in some expected performance measures like xwOBA, xBA, along with actual measures like K and BB rate.
My first crack at this will be to discover which Low-A pitchers have top 10th percentile metrics. This is a “who has a tool that sticks out” kind of question. For those pitchers with a notable metric, I will show a comparison not only to their league, but AAA and MLB standards for the same metric. For fun, I will also include a notable non-Cardinal prospect in the analysis (Seth Hernandez) to give some context to some of the numbers you will see.
A couple of quick notes on the data:
- The data comes from Baseball Savant (probably not surprising). The minor league side only has data for Low-A and AAA pitchers, so my research will unfortunately exclude High-A and AA pitchers. We have to wait for Liam Doyle to get to Memphis before we get to look under the hood.
- I’d love to use Chase%, but I can not find it in the exported set that comes from Savant. If anyone has any pointers, let me know.
- I arbitrarily set a cut off at 50 pitches … any pitcher with less than 50 pitches in that league is excluded. It helped make the data manageable, and also smoothed out most major league rehab pitchers. I’m not comparing prospects to veteran MLB pitchers, I’m comparing them to their peers.
- The vertical and horizontal movement ranks are non-intuitive. Whereas a low xBA is good (top 10th percentile) and a high xBA is bad (bottom 10th percentile), when it comes to direction, either extreme can be good, depending on the pitch type. For example, a high positive on the horizontal axis on a Sinker (SI) can produce a top 10th percentile, whereas a high negative on the same axis coupled with a Slider (SL) can produce a bottom 10th percentile result, which is equally good, given the pitch type.
Low-A Metric Leader Board
| player_name | total_pitches | pitch_type | pitch_percent | spin_rate | Velocity | spin_rate P10 | Velocity P10 | K rate P10 | whiff rate | whiff.rate P10 | Walk Rate P10 | Vertical Break (in) | Vertical Break P10 | Horiz break (in) | Horiz break P10 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Hernandez, Seth | 371 | FF | 48.2 | 2405 | 98.4 | 4 | 1 | 6 | 28% | 3 | 2 | 17.44 | 3 | 13.88 | 1 |
| Hernandez, Seth | 371 | SL | 18.1 | 2543 | 89.0 | 3 | 1 | 1 | 71% | 1 | 5 | 3.04 | 4 | -0.19 | 1 |
| Hernandez, Seth | 371 | CH | 18.1 | 2289 | 85.0 | 1 | 5 | 1 | 71% | 1 | 7 | 9.59 | 2 | 14.55 | 5 |
| Hernandez, Seth | 371 | CU | 15.6 | 2574 | 81.4 | 6 | 2 | 1 | 73% | 1 | 5 | -9.68 | 6 | -8.62 | 5 |
| Breckheimer, Alex | 510 | CU | 11.8 | 2176 | 76.9 | 10 | 9 | 10 | 22% | 9 | 7 | -14.71 | 10 | -7.34 | 3 |
| Breckheimer, Alex | 510 | FF | 55.9 | 2334 | 93.3 | 5 | 5 | 3 | 22% | 6 | 1 | 17.71 | 3 | 10.62 | 3 |
| Crossland, Cade | 784 | CH | 31.6 | 2254 | 82.7 | 1 | 8 | 3 | 55% | 2 | 9 | 7.58 | 3 | 18.81 | 1 |
| Crossland, Cade | 784 | CU | 11.1 | 2383 | 78.1 | 8 | 8 | 1 | 57% | 1 | 1 | -13.18 | 9 | -9.99 | 7 |
| Crossland, Cade | 784 | SL | 7.4 | 2163 | 84.4 | 9 | 3 | 10 | 24% | 9 | 7 | 3.07 | 4 | 0.66 | 1 |
| Cuello, Antoni | 359 | FF | 49.3 | 2461 | 95.2 | 3 | 3 | 10 | 12% | 10 | 7 | 14.98 | 8 | 14.5 | 1 |
| Cuello, Antoni | 359 | SL | 24.5 | 2224 | 83.1 | 8 | 7 | 1 | 45% | 3 | 9 | 2.56 | 5 | 0.18 | 1 |
| Driessen, Dylan | 315 | FF | 54.6 | 2231 | 94.5 | 9 | 4 | 1 | 26% | 4 | 7 | 20.31 | 1 | 5.51 | 10 |
| Driessen, Dylan | 315 | CU | 23.5 | 2768 | 80.2 | 3 | 4 | 5 | 29% | 5 | 1 | -11.82 | 8 | -8.5 | 4 |
| Echeman, Kaden | 557 | CU | 23.5 | 2594 | 81.4 | 5 | 2 | 2 | 45% | 2 | 5 | -15.9 | 10 | -4.77 | 2 |
| Jovi Galvez | 297 | SI | 30 | 2169 | 94.4 | 8 | 3 | 3 | 28% | 2 | 9 | 14.24 | 4 | 15.14 | 3 |
| Martinez, Jack | 783 | SL | 36.9 | 2462 | 81.3 | 5 | 9 | 10 | 28% | 8 | 10 | 8.86 | 1 | -6.65 | 7 |
| Odle, Jacob | 584 | FF | 28.6 | 2432 | 97.1 | 3 | 1 | 4 | 24% | 5 | 8 | 17.58 | 3 | 8.87 | 5 |
| Odle, Jacob | 584 | CU | 18.8 | 2593 | 83.0 | 5 | 1 | 4 | 34% | 4 | 4 | -11.51 | 8 | -8.6 | 5 |
| Shelagowski, Jake | 601 | FF | 55.9 | 2235 | 95.8 | 8 | 2 | 5 | 20% | 8 | 4 | 15.68 | 7 | 14.2 | 1 |
| Shelagowski, Jake | 601 | SL | 23.5 | 2162 | 86.1 | 9 | 1 | 5 | 28% | 8 | 1 | 1.18 | 7 | -2 | 2 |
| Van Dyke, Ty | 431 | FF | 44.5 | 2290 | 92.4 | 7 | 8 | 2 | 24% | 5 | 1 | 15.67 | 7 | 13.61 | 1 |
| Van Dyke, Ty | 431 | SL | 16.7 | 2796 | 81.5 | 1 | 9 | 1 | 36% | 5 | 2 | 2.2 | 6 | -12.57 | 10 |
| Ynfante, Nelfy | 358 | SI | 38.8 | 2167 | 94.3 | 8 | 3 | 4 | 23% | 4 | 4 | 14.71 | 3 | 13.96 | 6 |
| Young, Ethan | 514 | SI | 30.2 | 2353 | 93.8 | 3 | 4 | 5 | 26% | 3 | 6 | 16.57 | 1 | 15.47 | 2 |
| Young, Ethan | 514 | CH | 20.4 | 2081 | 84.9 | 2 | 6 | 4 | 56% | 1 | 9 | 5.83 | 6 | 17.4 | 2 |
| Young, Ethan | 514 | FF | 19.1 | 2328 | 93.2 | 6 | 6 | 9 | 17% | 8 | 1 | 18.49 | 2 | 12.31 | 2 |
The above table depicts 12 Palm Beach (Low-A) pitches who have at least one pitch metric in the top 10th percentile of their league. These represent the tools the Cardinals have to work with and develop.
The thirteen pitcher is a proxy – Seth Hernandez. If you’ve never heard of him, you will. He is what scouts dream of when it comes to pitch metrics:
- (FF) Four seam fastball that has top 10th percentile in velo AND horizontal movement
- (SL) Slider with top tenth percentile in whiff rate and horizontal movement
- (CH) with top tenth spin rate and whiff rate
With that primer, let’s look at Cardinal Low-A prospects:
- Alex Breckheimer has elite command with his four seamer w/ a top 10th percentile walk rate.
- Cade Crossland’s spin rate and horizontal break on his change-up (CH) are top 10th. His curve (CU) has elite whiff rate and elite horizontal break (90th percentile). This is one of those counter-intuitive ones where the large negative number is a great number. In an odd one, his slider (SL) has a really odd outlier horizontal break – it breaks into RH hitters. That will need fixing.
- Antoni Cuello has top 10th horizontal break on his FF and SL, and has a superior K rate with that slider. It is a put away pitch.
- Dylan Driessen has top 10th percentile induced vertical break on this 4-seam fastball (FF). I always get this backwards but I think this means it has “ride” or “hop” to it. He also has exceptional command over his slider (SL).
- Kaden Echemann has an even better curve (CU) that Crossland with 16” of downward break. Memories of Uncle Charlie with this one.
- Jack Martinez has unusual break on his slider. It doesn’t miss bats, and walks lots of guys, so I don’t see this 10th percentile rating as all that helpful.
- Jacob Odle carries top tenth percentile on both his FF. He had one of the hardest curves in the league, too, before he advanced to High-A.
- John Shelagowski has elite horizontal break on his FF and has elite and near-elite characteristics on his slider (SL).
- Tyler Van Dyke’s FF really rides in on RH batter, with a high K and low walk rate (the velo itself is pedestrian). He also carries very good command characteristics on his SL.
- Ethan Young carries top tenth percentile characteristics on his SI, CH and FF. Looks a little like Seth Hernandez, huh?
Performance Matters
Stuff (and the underlying metrics which show it) are one thing. Performance is another. Which pitchers (in Low-A Palm Beach) are getting the most out of their stuff? Let’s look more at performance outcomes as see how they rate.
| player_name | pitch_type | pitch_percent | xwoba | K Rate | BB Rate | HardHit% | xwOBA P10 | Hard Hit Rate P10 | K rate P10 | Walk Rate P10 |
|---|---|---|---|---|---|---|---|---|---|---|
| Breckheimer, Alex | FF | 55.9 | 0.23 | 28 | 5.3 | 39.58 | 2 | 5 | 3 | 1 |
| Breckheimer, Alex | CU | 11.8 | 0.27 | 10 | 10 | 14.29 | 7 | 2 | 10 | 7 |
| Crossland, Cade | CH | 31.6 | 0.24 | 42.4 | 18.2 | 19.23 | 5 | 4 | 3 | 9 |
| Crossland, Cade | CU | 11.1 | 0.08 | 77.8 | 0 | 25 | 1 | 5 | 1 | 1 |
| Crossland, Cade | SL | 7.4 | 0.57 | 8.3 | 8.3 | 37.5 | 10 | 7 | 10 | 7 |
| Cuello, Antoni | FF | 49.3 | 0.35 | 7.9 | 18.4 | 44.44 | 7 | 8 | 10 | 7 |
| Cuello, Antoni | SL | 24.5 | 0.2 | 54.5 | 13.6 | 0 | 3 | 1 | 1 | 9 |
| Driessen, Dylan | FF | 54.6 | 0.26 | 40 | 20 | 28.57 | 2 | 2 | 1 | 7 |
| Driessen, Dylan | CU | 23.5 | 0.3 | 41.2 | 0 | 60 | 7 | 10 | 5 | 1 |
| Echeman, Kaden | FF | 53.1 | 0.34 | 19.8 | 23.5 | 37.78 | 6 | 4 | 6 | 8 |
| Echeman, Kaden | CU | 23.5 | 0.25 | 58.1 | 6.5 | 30 | 6 | 5 | 2 | 5 |
| Martinez, Jack | SL | 36.9 | 0.26 | 14.6 | 16.7 | 21.21 | 6 | 2 | 10 | 10 |
| Martinez, Jack | FF | 30.8 | 0.27 | 34.9 | 14.3 | 27.59 | 2 | 1 | 2 | 5 |
| Odle, Jacob | FF | 28.6 | 0.32 | 25.6 | 23.3 | 40.91 | 5 | 6 | 4 | 8 |
| Odle, Jacob | CU | 18.8 | 0.15 | 48.3 | 3.4 | 61.54 | 3 | 10 | 4 | 4 |
| Shelagowski, Jake | SL | 23.5 | 0.16 | 34.6 | 0 | 35.29 | 2 | 6 | 5 | 1 |
| Shelagowski, Jake | CU | 12.5 | 0.36 | 23.8 | 14.3 | 18.18 | 9 | 3 | 8 | 9 |
| Van Dyke, Ty | FF | 44.5 | 0.2 | 31 | 5.2 | 33.33 | 1 | 2 | 2 | 1 |
| Van Dyke, Ty | SL | 16.7 | 0.08 | 54.5 | 0 | 0 | 1 | 1 | 1 | 2 |
| Ynfante, Nelfy | SI | 38.8 | 0.22 | 18.8 | 9.4 | 26.09 | 1 | 2 | 4 | 4 |
| Young, Ethan | SI | 30.2 | 0.34 | 18.2 | 13.6 | 43.33 | 7 | 8 | 5 | 6 |
| Young, Ethan | CH | 20.4 | 0.15 | 41.7 | 16.7 | 0 | 1 | 1 | 4 | 9 |
| Young, Ethan | FF | 19.1 | 0.31 | 8.7 | 4.3 | 57.89 | 4 | 10 | 9 | 1 |
| Young, Ethan | CU | 11.9 | 0.15 | 60 | 10 | 0 | 2 | 1 | 2 | 7 |
In the above table, you will see many of the same names and pitches, this time with how those pitches are performing in real games. There are few new names, as some guys without top 10th percentile stuff are still getting top tenth percentile results, such as Nelfy Ynfante, who really limits hard contact without any top tier stuff.
Some notes:
- Crossland’s change and curve perform well. Sure enough, that odd slider does not.
- Odle’s FF seems to perform a bit worse that the metrics suggest it should.
- Van Dyke’s command sets him apart.
- Jack Martinez seems to get more out of his FF that the metrics suggest he should.
- Ethan Young, with 4 pitches on this chart, should become a name to remember. How many low-A pitchers do you remember that already have 4 average or better offerings?
Summary
So I’m ending this just with Low-A pitchers. Round 2 will include AAA pitchers, in similar format, depending on how commenters react to this first go. This hopefully provides you with some names to watch for, some reasons to watch for them and some explanation about why these guys keep getting used in priority situations.
Closing
Oh, yeah. Remember that cheat sheet I keep looking for to remember what is a really good pitch metric…like for when someone tell us so-and-so’s sinker (SI) breaks arm side 18”. Is that good? Is it elite? Below is an MLB chart and indeed, anything above 17.9” is top tenth percentile. This is for all pitchers in the MLB in 2026.
| pitch_type | OBA | xBA | Hardhit | Top Spin Rate | Bottom Spin Rate | Whiff Rate | K Rate | Walk Rate | Top Vertical | Bottom Vertical | Top Horiz | Bottom Horiz | Velo |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| FF | 0.253 | 0.166 | 31.3 | 2485 | 2135 | 13% | 34.5 | 5.6 | 18.5 | 12.9 | 11.9 | 3.6 | 91.8 |
| SI | 0.261 | 0.211 | 26.5 | 2382 | 2018 | 6% | 20.0 | 2.4 | 13.0 | 2.2 | 17.9 | 13.2 | 90.8 |
| SL | 0.187 | 0.147 | 19.3 | 2699 | 2174 | 20% | 43.3 | 0.0 | 5.7 | -3.5 | -1.0 | -8.0 | 83.2 |
| CH | 0.196 | 0.161 | 17.2 | 2123 | 1313 | 20% | 36.0 | 0.0 | 9.1 | -0.9 | 17.5 | 11.1 | 81.8 |
| ST | 0.176 | 0.132 | 18.0 | 2873 | 2268 | 21% | 43.6 | 0.0 | 5.6 | -3.7 | -10.0 | -17.4 | 78.9 |
| FC | 0.263 | 0.190 | 22.5 | 2623 | 2155 | 14% | 24.3 | 0.0 | 12.0 | 4.5 | 0.6 | -4.8 | 86.8 |
| CU | 0.187 | 0.134 | 17.6 | 2879 | 2266 | 19% | 48.2 | 0.0 | -5.2 | -15.8 | -3.6 | -14.2 | 75.0 |
| FS | 0.195 | 0.149 | 16.7 | 1709 | 971 | 18% | 46.4 | 0.0 | 6.8 | -0.7 | 15.1 | 8.0 | 82.7 |
| KC | 0.200 | 0.151 | 26.3 | 2794 | 2278 | 19% | 41.3 | 0.4 | -4.2 | -14.7 | -2.0 | -13.2 | 78.3 |
| SV | 0.245 | 0.207 | 22.8 | 2856 | 2215 | 23% | 33.0 | 0.0 | -2.2 | -7.6 | -5.6 | -17.2 | 80.1 |
| FO | 0.241 | 0.174 | 27.7 | 1073 | 649 | 33% | 34.9 | 3.6 | 0.2 | -2.5 | 10.5 | 4.1 | 82.9 |
| KN | 0.264 | 0.232 | 40.9 | 299 | 299 | 21% | 29.4 | 5.9 | -1.9 | -1.9 | 1.6 | 1.6 | 80.5 |
One interesting thing I think I see in this data. There really doesn’t seem to be a lot a difference in top tenth pitch metrics (spin rate, horizontal break, etc.) between Low-A and MLB. Is that a reasonable look? That tells me that location, command and sequencing is what they learn coming up the ladder, but the raw materials are pretty much in place in Low-A. Valid observation?
Long-term, I might spiff this up by blanking out more irrelevant columns. For example, percentile rank is not crucial for velocity on a Knuckle Curve. For most breaking/off speed pitches, the offset from the FF/SI is more crucial, as well as the spin direction (which isn’t in the data set, as far as I can tell).
Links
Here is a link to the underlying spreadsheet with top decile performance across the Florida State League (low-a).
