The Ones We Missed: Javier Baez & Trevor Story
In the #2earlymock drafts run by our own Justin Mason, Javier Baez is going 17th and Trevor Story is going 20th among all hitters. The picks are quite high considering Baez was the 58th hitter taken, and Story was 65th in NFBC drafts last year. The pair didn’t have must-draft preseason hype and their suspect plate discipline limited their perceived value. Both exceeded all expectations as they came in at 6th and 7th overall this year. This was a huge miss by the industry and I’m going to see if some traits point to why some low plate discipline players break out and others don’t.
For every Baez and Story, other bad plate discipline hitters failed like Byron Buxton (.383 OPS), Chris Davis (.539 OPS), Miguel Sano (.679 OPS) and Jonathan Schoop (.682 OPS). No obvious difference stood out. While Chris Davis is old, Buxton, Sano, and Schoop should be in their primes. To find out who may break out, I decided to start with the 2018 Bad Plate Discipline Class.
I utilized the 2018 Steamer projections and limited the sample to hitters projected for at least 300 PA and a K%-BB% of 15% or more. In all, 63 hitters made the cut.
Name | PA | K%-BB% | BABIP | OPS | PA | K%-BB% | BABIP | OPS |
---|---|---|---|---|---|---|---|---|
Projected | Actual | |||||||
Matt Davidson | 508 | 27.5% | .284 | .673 | 496 | 22.8% | .313 | .738 |
Jorge Alfaro | 363.9 | 26.7% | .312 | .663 | 377 | 31.8% | .406 | .731 |
Mike Zunino | 433.5 | 23.8% | .279 | .747 | 405 | 31.1% | .268 | .669 |
Randal Grichuk | 480.9 | 23.7% | .292 | .774 | 462 | 20.6% | .282 | .803 |
Adam Engel | 431.1 | 23.1% | .287 | .607 | 463 | 24.0% | .322 | .614 |
Michael Taylor | 457.6 | 22.9% | .326 | .718 | 385 | 22.6% | .320 | .644 |
Nick Williams | 413.8 | 22.7% | .318 | .736 | 448 | 17.6% | .312 | .749 |
Carlos Gomez | 406.6 | 22.1% | .310 | .705 | 408 | 19.1% | .266 | .634 |
Chad Pinder | 400.7 | 22.0% | .313 | .699 | 333 | 18.3% | .325 | .769 |
Chris Davis | 523.6 | 21.7% | .296 | .808 | 522 | 28.9% | .237 | .539 |
Tim Anderson | 571.1 | 21.5% | .331 | .692 | 606 | 19.6% | .289 | .687 |
Bradley Zimmer | 519.9 | 21.2% | .331 | .718 | 114 | 32.5% | .367 | .611 |
Tim Beckham | 614.8 | 21.2% | .326 | .726 | 402 | 18.2% | .282 | .661 |
Trevor Story | 551.1 | 21.1% | .326 | .796 | 656 | 18.5% | .345 | .914 |
Miguel Sano | 476.5 | 21.0% | .334 | .860 | 299 | 28.1% | .286 | .679 |
Joey Gallo | 569 | 20.9% | .285 | .849 | 577 | 23.1% | .249 | .810 |
Adam Duvall | 495.2 | 20.7% | .273 | .734 | 427 | 18.7% | .237 | .639 |
Colby Rasmus | 313.4 | 20.6% | .302 | .785 | 49 | 32.7% | .200 | .426 |
Byron Buxton | 570.4 | 20.4% | .329 | .758 | 94 | 26.6% | .226 | .383 |
Paul DeJong | 513.1 | 19.7% | .311 | .769 | 490 | 17.8% | .288 | .746 |
Matt Chapman | 565.6 | 19.7% | .276 | .747 | 616 | 14.3% | .338 | .864 |
Welington Castillo | 399.2 | 19.6% | .304 | .736 | 181 | 20.4% | .322 | .710 |
Khris Davis | 599 | 19.4% | .287 | .819 | 654 | 17.7% | .261 | .874 |
Steven Souza Jr. | 344.4 | 19.2% | .322 | .779 | 272 | 17.3% | .298 | .678 |
Austin Hedges | 415.3 | 19.1% | .270 | .684 | 326 | 21.2% | .280 | .711 |
Javier Baez | 509.7 | 19.1% | .313 | .775 | 645 | 21.4% | .347 | .881 |
Justin Upton | 614.3 | 18.7% | .309 | .803 | 613 | 18.3% | .321 | .808 |
Ronald Acuna | 432.7 | 18.5% | .348 | .779 | 487 | 16.0% | .352 | .917 |
Martin Maldonado | 343.7 | 18.4% | .273 | .660 | 404 | 20.3% | .280 | .627 |
Ryon Healy | 438.6 | 18.4% | .304 | .725 | 524 | 16.4% | .257 | .688 |
Paulo Orlando | 311.8 | 18.3% | .328 | .676 | 93 | 23.7% | .231 | .394 |
Ian Happ | 516.7 | 18.3% | .304 | .783 | 462 | 21.0% | .362 | .761 |
Mikie Mahtook | 379.2 | 18.1% | .319 | .727 | 250 | 18.0% | .238 | .635 |
Yoan Moncada | 583.4 | 17.9% | .317 | .719 | 650 | 23.1% | .344 | .714 |
Jason Castro | 338.5 | 17.9% | .307 | .712 | 74 | 23.0% | .216 | .495 |
James McCann | 411.4 | 17.8% | .304 | .698 | 457 | 19.7% | .282 | .581 |
Jorge Soler | 516.4 | 17.8% | .310 | .765 | 257 | 16.0% | .340 | .820 |
Tyler Flowers | 340.6 | 17.6% | .325 | .759 | 296 | 13.9% | .292 | .700 |
Jonathan Villar | 494.9 | 17.6% | .327 | .721 | 515 | 18.8% | .339 | .709 |
Jorge Bonifacio | 346.2 | 17.5% | .309 | .728 | 270 | 15.6% | .301 | .672 |
J.D. Martinez | 538.1 | 17.5% | .342 | .909 | 649 | 11.9% | .375 | 1.031 |
Trey Mancini | 566.1 | 17.4% | .329 | .782 | 636 | 17.1% | .285 | .715 |
Mark Trumbo | 370.5 | 17.3% | .285 | .787 | 358 | 17.6% | .303 | .764 |
Ian Desmond | 535.7 | 17.1% | .346 | .804 | 619 | 15.0% | .279 | .729 |
Alex Avila | 348.6 | 16.8% | .332 | .741 | 234 | 22.7% | .253 | .603 |
Robinson Chirinos | 313.7 | 16.8% | .278 | .746 | 426 | 22.3% | .304 | .757 |
Aaron Altherr | 449.9 | 16.7% | .303 | .773 | 285 | 19.3% | .247 | .628 |
Leury Garcia | 307.5 | 16.6% | .314 | .686 | 275 | 21.8% | .355 | .679 |
Corey Dickerson | 461.9 | 16.6% | .313 | .791 | 533 | 11.1% | .333 | .804 |
Jonathan Schoop | 616.2 | 16.3% | .307 | .805 | 501 | 19.2% | .261 | .682 |
Domingo Santana | 572.7 | 16.3% | .328 | .821 | 235 | 24.3% | .386 | .740 |
Kyle Schwarber | 498.6 | 16.3% | .290 | .830 | 510 | 12.2% | .288 | .823 |
Amed Rosario | 535.8 | 16.1% | .312 | .670 | 592 | 15.2% | .310 | .676 |
Scott Schebler | 464.9 | 16.0% | .280 | .776 | 430 | 14.0% | .301 | .777 |
C.J. Cron | 431.2 | 15.9% | .288 | .754 | 560 | 19.3% | .293 | .816 |
Aaron Judge | 614 | 15.9% | .318 | .886 | 498 | 15.3% | .368 | .919 |
Rougned Odor | 569.2 | 15.7% | .278 | .782 | 535 | 15.7% | .305 | .751 |
Eric Thames | 507.6 | 15.7% | .304 | .834 | 278 | 24.5% | .284 | .783 |
Alex Gordon | 510.2 | 15.6% | .299 | .712 | 568 | 13.0% | .299 | .694 |
Nick Castellanos | 596.3 | 15.4% | .318 | .807 | 678 | 15.0% | .361 | .854 |
Scooter Gennett | 489.8 | 15.3% | .302 | .736 | 638 | 13.0% | .358 | .847 |
Yolmer Sanchez | 473.7 | 15.3% | .299 | .682 | 662 | 13.4% | .300 | .678 |
Salvador Perez | 506.3 | 15.1% | .283 | .763 | 544 | 16.7% | .245 | .713 |
Eddie Rosario | 572.2 | 15.0% | .313 | .784 | 592 | 12.5% | .316 | .803 |
Second, I divided the players up into three groups. One was those who improved by 50 points of OPS, those who worsened by 50 points, and those in-between. Then, I cut-and-diced the data and in the end, I found the following variables the most important:
Category | K% Diff | BB% Diff | BABIP Diff | Age |
---|---|---|---|---|
Improve | -1.0% | 0.6% | .029 | 26.3 |
Same | 0.1% | 0.2% | .010 | 26.8 |
Worsened | 2.6% | -0.4% | -.043 | 28.4 |
The first and easiest factor to check is the age. I started with the above age values and split the age groups by 27 and younger and over 27 I got a drop of .008 for the young hitters and the older hitters down by .016. After adjusting the values, I found 30-years-old to be the key age.
The hitters who are 30 and younger had their production drop by only 3 OPS points while it dropped 38 points for those over 30. The statement is true about teaching an old dog new tricks. Additionally, these old dog’s value drop because their projected BABIP dropped from .299 to an actual value of .287. Age may be a smoking gun.
Going back to the 2018 trends table, it’s time to see if the BABIP and plate discipline numbers stick. BABIP goes first.
OPS Change | Proj Y1 BABIP | Y1 BABIP | Y2 BABIP |
---|---|---|---|
Improved | .303 | .327 | .301 |
Same | .300 | .301 | .293 |
Worsened | .305 | .273 | .298 |
The previous season’s projected BABIP does a great job of estimating that year’s BABIP. Believe the projection on BABIP instead of the previous season’s values.
One player group to target may be these bad plate discipline hitters with underperforming BABIPs. Bad previous season results may be anchoring their value down going into drafts.
Now for the plate discipline.
OPS | Proj Y1 K%-BB% | Y1 K%-BB% | Y2 K%-BB% |
---|---|---|---|
Improved | .175 | .167 | .175 |
Same | .180 | .188 | .190 |
Worsened | .175 | .198 | .208 |
For the hitters who improved, they saw their plate discipline stick while those who saw a drop normally saw the drop continue.
While the plate discipline and BABIP bounced back to the previous level, the overall OPS did not completely.
OPS | Proj Y1 OPS | Y1 OPS | Y2 OPS |
---|---|---|---|
Improved | .740 | .844 | .768 |
Same | .727 | .730 | .718 |
Worsened | .738 | .620 | .685 |
Since BABIP wasn’t providing the rebound, I need to find out why the change stuck. The answer was power.
OPS | Proj Y1 ISO | Y1 ISO | Y2 ISO |
---|---|---|---|
Improved | .180 | .229 | .199 |
Same | .176 | .179 | .176 |
Worsened | .178 | .129 | .166 |
The preceding ramblings point to three factors which may lead a poor plate discipline hitter breaking out: age, power increase, and plate discipline improvement.
To test these variables, I took three regular seasons of data and one projected season of data. With the projected season (Y3), I found those hitters who with a K%-BB% projected for over 15% and age. Then I looked at the two previous seasons to see if the hitter’s plate discipline and/or power improved. The key was to find if any breakouts or breakdowns could be predicted before the season.
Here are the differences in actual and projected OPS in Y3.
Variables OPS Change
Plate and Age -.004
Power & Age -.008
All three -.009
Age -.012
Plate -.015
Power -.016
One of three -.018
Power & Plate -.021
None of three -.045
It might sound cruel (or obvious) but just stay away from over 30-year-old hitters with declining power and plate discipline. Additionally, not one subgroup improves. They just decline less.
With strikeout rates jumping from 18.5% when the projections started to 22.3% this past season, hitters with poor plate discipline will struggle more. While power is up also, it’s not able to offset the increase strikeouts from these hack happy free swingers. If an owner must roster someone from this group, ensure they are the younger hitters who at least saw an improvement in their power or plate discipline the previous season.
Now, back to the two breakouts, Trevor Story and Javier Baez. With Story, nothing stood out but his age with his previous season ISO dropping from .296 to .219 and his K%-BB% going from 39.7% to 43.3%.
Baez also met the age requirement, but he saw his ISO jump from .150 to .264 while his plate discipline took a hit from 27.3% to 34.2%. He at least met two of the categories.
Looking forward to next season, both meet the improved power and plate discipline requirements while still being under 30 but still having some plate discipline issues compared to the rest of the league. They should keep some of the improvements but understand their BABIP will likely regress back to their 2018 projections of .313 for Baez and .326 for Story.
I’ll come back and examine some hitters who the preceding study applies to once projections become available. The findings aren’t 100% clear and trustworthy but they provide some framework for finding the potential breakouts but even more, they help to find those hitters to stay away from. I feel like I may be missing some key factor tying everything together, but I’ll have to mull on it for a while. Next, I’m off to find the keys for the Max Muncy breakouts.
Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.
Thank you for bolding the most actionable parts of the article. These K-rates are getting out of hand.