Strategy for Finding Hitter Value Through Playing Time

Looking at those who gained the most in end-of-season rank from ADP is always an interesting exercise. Now it all seems so obvious, but to wind the clock back to March, these names were most likely afterthoughts as we prepared draft plans. In an attempt to find a way to get ahead for next year, I pored over metrics to see what cheat code I could find. Alas, there is no perfect formula for predicting the next Jake Bauers or Jordan Walker, but I think some useful methods can at least give us an idea of who might be next season’s breakout.
This is not a piece for player recommendations, but I hope to provide a method to help identify potential value with your own player projections for next year. From a group of 183 hitters who improved their production rank from their ADP, I wanted to try to extrapolate what the biggest contributors to those gains were, and how we can use that information for our draft strategy as we look to identify value.
Firstly, to set up the field, the 100 biggest risers gained at least 48 spots, and 55 of them gained 100 or more, with 56 of the 100 going undrafted. So this group of 100-plus gains is most interesting; Tatis moving from 11 ADP to rank 6 isn’t that useful to us, and similarly, Connor Wong moving from undrafted to rank 279 isn’t particularly helpful either.
Of the 100 largest gainers, 67 had 100+ PA in 2025, and 33 had under 100 PA, 21 of them with no 2025 MLB data.
This PA sweet spot we will be targeting will range from 100-400 PA. A minimum of 100 plate appearances might not seem like a lot, but it can begin to give us a pretty reasonable indication of next year’s potential while also still providing value in that these players may have missed time, had late call-ups, and thus will have a lower ADP. Any higher than 400, and the PA volume is more likely to be reflected in the ADP.
From my digging, it seems a combination of finding reduced plate appearances from the previous season with a solid, even slightly below average, xwOBA in that sample is a pretty simple method that can point us toward a gainer.
Of the 55 hitters who gained 100+ spots on their ADP, 41 had either 400 or fewer PA or no MLB data in 2025.
Fourteen of those 41 had no 2025 MLB data, and seven had fewer than 100 PA, so I set them aside. That leaves 20 hitters with between 100 and 400 PA. Their xwOBA held or rose: the group moved from .289 in 2025 to .322 in 2026, and 14 of the 20 finished at .314 (league-average) or better.
| 2025 PA group | # | 2025 xwOBA | 2026 xwOBA | median 2025 PA | median 2026 PA | median Gain |
|---|---|---|---|---|---|---|
| No 2025 MLB data | 14 | – | .331 | – | 555 | 185 |
| 1-99 | 7 | .295 | .318 | 59 | 448 | 121 |
| 100-400 | 20 | .289 | .322 | 298 | 525 | 158 |
| 401+ | 14 | .319 | .327 | 494 | 603 | 140 |
Gain is ADP rank minus 2026 production rank. Undrafted hitters are treated as ADP rank 288.
Most of the 20 hitters in the 100–400 PA group were below the .314 league-average xwOBA in 2025 (14 of 20), but their collective xwOBA improved from .289 to .322 in 2026. All were ranked 189th or worse and went on to a median of 525 PA.
xwOBA and Playing Time
To see whether a small sample of xwOBA is worth trusting, I compared each hitter’s 2025 xwOBA with his 2026 xwOBA among hitters with 300+ PA in 2026. When the 2025 sample was 100 to 299 PA (36 hitters), the average absolute difference between the two seasons was .033. When it was 300+ PA (194 hitters), the gap was .021. Although the smaller sample is less precise, the difference between seasons was not dramatically larger, suggesting that 100–299 PA can still provide a useful indication of a hitter’s underlying offensive ability.
Again, to reiterate, these are just the numbers from hitters that were able to gain on their production rank. Of those 20 hitters, 12 finished within .030 of their 2025 xwOBA and 8 were up by more than .030 (Gelof +.104, Karros +.076, Mead +.067, Bleday +.064, Walker +.062, Duran +.053, Massey +.042, McCarthy +.035). The 14 with more than 400 PA barely moved (.319 to .327, 11 within .030), consistent with the stabilizing nature of a large sample. Hitters with above-average xwOBA and large sample sizes have an ADP to reflect just that. Top-50 picks had a median .347 xwOBA and 651 PA in 2025, against .305 and 396 PA for picks 201 and later.
| Name | 2025 PA | 2025 xwOBA | 2026 PA | 2026 xwOBA | Gain |
|---|---|---|---|---|---|
| Jake Bauers | 218 | .356 | 578 | .371 | 256 |
| Liam Hicks | 385 | .315 | 554 | .319 | 238 |
| Ezequiel Duran | 218 | .247 | 597 | .300 | 225 |
| Brayan Rocchio | 378 | .295 | 592 | .294 | 207 |
| Zack Gelof | 100 | .219 | 435 | .323 | 204 |
| Jordan Walker | 395 | .278 | 667 | .340 | 181 |
| Javier Sanoja | 337 | .282 | 490 | .295 | 179 |
| Jake McCarthy | 219 | .286 | 596 | .321 | 166 |
| Heriberto Hernández | 292 | .331 | 505 | .348 | 162 |
| Mauricio Dubón | 394 | .278 | 619 | .306 | 159 |
| Kody Clemens | 382 | .331 | 583 | .334 | 158 |
| Casey Schmitt | 346 | .328 | 409 | .355 | 153 |
| Ildemaro Vargas | 120 | .287 | 486 | .298 | 130 |
| JJ Bleday | 342 | .276 | 545 | .340 | 128 |
| Joc Pederson | 304 | .316 | 432 | .344 | 125 |
| Kyle Karros | 155 | .258 | 475 | .334 | 122 |
| Cole Young | 254 | .297 | 638 | .316 | 109 |
| Jacob Young | 353 | .297 | 471 | .314 | 106 |
| Michael Massey | 276 | .265 | 452 | .307 | 106 |
| Curtis Mead | 260 | .291 | 329 | .358 | 104 |
Putting to the Test
Trying to find value in smaller PA samples seems to be the play. The pool of 198 hitters with 100-400 PA: 43 of them reached more than 400 PA in 2026, just 22%. Among those 198, 21 of the 58 hitters at .314 or better in 2025 (36%) reached more than 400 PA, against 22 of the 140 below it (16%). So there is some skill in predicting where plate appearances will go in any following season, but predict correctly and there is a ton of value to be found.
A retrospective exercise is also worthwhile. Applying this exercise to the crop of low-PA hitters from last year would have resulted in the following.
| 2026 outcome | # | 2025 xwOBA | 2026 xwOBA | Median Gain |
|---|---|---|---|---|
| Reached 401+ PA | 21 | .331 | .327 | +61 |
| Stayed 100-400 PA | 30 | .328 | .299 | -117 |
| Under 100 PA | 13 | – | – | – |
Of the 64 hitters who met the same criteria in 2025 (100 to 400 PA and a league-average xwOBA or better), 21 reached more than 400 PA in 2026, or one in three. Those 21 held their xwOBA (.331 in 2025 and .327 in 2026), while the 30 who stayed between 100 and 400 PA slipped from .328 to .299.
So, as a potential draft strategy, we can look to utilize this, as we look for hitters with perhaps depreciated value; that value, first and foremost, can come in the simplest stat of all: plate appearances. Across the 323 hitters with MLB data in both seasons, the change in PA tracked rank gain much more closely (.63) than the change in xwOBA (.39).
Applying to 2027
Looking forward to 2027, this is where, as managers, our own reading and evaluation come into play. Below I will include a table of all hitters (including Judge and Smith for holistic reasons) that finished with 100-400 PA in 2026 and above league-average xwOBA. Some names are going to stand out immediately more than others, but I think there are plenty of options that will have appealing ADPs come draft season. I also included wRC+ and OPS to provide some additional context from the 2026 season.
| Name | Team | PA | xwOBA | wRC+ | OPS |
|---|---|---|---|---|---|
| Aaron Judge | NYY | 285 | .396 | 140 | .871 |
| Will Smith | LAD | 276 | .389 | 118 | .781 |
| Eduardo Valencia | DET | 138 | .372 | 182 | 1.015 |
| Griffin Conine | MIA | 323 | .369 | 133 | .846 |
| Carlos Correa | HOU | 141 | .364 | 124 | .787 |
| Curtis Mead | 2 Tms | 329 | .358 | 133 | .851 |
| Mickey Gasper | BOS | 225 | .353 | 130 | .823 |
| Blaze Alexander | BAL | 289 | .351 | 121 | .772 |
| Rafael Flores Jr. | PIT | 163 | .350 | 130 | .858 |
| Leo Bernal | STL | 102 | .347 | 124 | .807 |
| Jhonny Pereda | SEA | 101 | .345 | 123 | .755 |
| Ryan Jeffers | MIN | 368 | .344 | 128 | .814 |
| Andrés Chaparro | WSN | 228 | .344 | 141 | .885 |
| Lars Nootbaar | 2 Tms | 334 | .343 | 102 | .721 |
| Luke Raley | SEA | 287 | .342 | 106 | .723 |
| Spencer Steer | CIN | 384 | .342 | 103 | .739 |
| Roman Anthony | BOS | 242 | .341 | 106 | .735 |
| Nelson Velázquez | 2 Tms | 113 | .339 | 80 | .663 |
| Edouard Julien | COL | 276 | .338 | 66 | .615 |
| Endy Rodríguez | PIT | 159 | .338 | 132 | .840 |
| Dalton Rushing | LAD | 253 | .336 | 117 | .788 |
| Gary Sánchez | MIL | 275 | .336 | 117 | .771 |
| Randal Grichuk | 2 Tms | 280 | .335 | 139 | .880 |
| Drew Gilbert | SFG | 393 | .334 | 104 | .724 |
| Brady House | WSN | 355 | .333 | 94 | .710 |
| Michael Conforto | CHC | 314 | .332 | 119 | .800 |
| Esmerlyn Valdez | PIT | 287 | .332 | 130 | .855 |
| Christian Encarnacion-Strand | BAL | 213 | .332 | 133 | .838 |
| Andrew Vaughn | MIL | 331 | .329 | 134 | .834 |
| Victor Mesa Jr. | TBR | 262 | .329 | 128 | .825 |
| Jahmai Jones | 2 Tms | 181 | .328 | 88 | .667 |
| Edmundo Sosa | PHI | 250 | .328 | 89 | .712 |
| Spencer Jones | NYY | 289 | .328 | 106 | .742 |
| Ryan Vilade | TBR | 278 | .327 | 108 | .750 |
| Luis Campusano | SDP | 248 | .327 | 127 | .795 |
| Braden Montgomery | CHW | 365 | .325 | 89 | .662 |
| Justin Foscue | TEX | 247 | .325 | 130 | .816 |
| Donovan Walton | 2 Tms | 268 | .322 | 124 | .806 |
| Luis Robert Jr. | 2 Tms | 230 | .321 | 97 | .707 |
| Kyle Teel | CHW | 144 | .321 | 103 | .697 |
| Jesús Sánchez | 2 Tms | 315 | .321 | 99 | .713 |
| Jared Young 제러드 | NYM | 342 | .321 | 111 | .759 |
| Samuel Basallo | BAL | 399 | .318 | 95 | .696 |
| Masataka Yoshida | BOS | 297 | .318 | 108 | .746 |
| Maikel Garcia | KCR | 344 | .318 | 99 | .715 |
| Blaze Jordan | STL | 199 | .317 | 79 | .658 |
| Ben Malgeri | DET | 140 | .317 | 118 | .767 |
| Konnor Griffin | PIT | 339 | .316 | 98 | .728 |
| Turner Hill | SFG | 124 | .316 | 77 | .621 |
| Cole Carrigg | COL | 372 | .316 | 110 | .818 |
| Cooper Pratt | MIL | 266 | .315 | 102 | .718 |
| Colton Cowser | BAL | 392 | .315 | 98 | .687 |
| Tim Tawa | ARI | 351 | .315 | 89 | .689 |
| John Rave | KCR | 161 | .315 | 105 | .744 |
| Brendan Donovan | SEA | 159 | .314 | 131 | .780 |
| Leo Jiménez | MIA | 194 | .314 | 65 | .565 |
| Wade Meckler | LAA | 337 | .314 | 120 | .760 |
| Dustin Harris | 3 Tms | 152 | .314 | 109 | .737 |
| Jordan Lawlar | ARI | 136 | .314 | 114 | .778 |
| Max Clark | DET | 206 | .314 | 115 | .766 |
Predicting these breakouts is not easy. Andrew Vaughn was deservedly the projected breakout bat out of the Brewers lineup pre-2026. So for Jake Bauers to come out as the biggest gainer of the year following Vaughn’s injury shows how great he really was. But the underlying signs were there if he was afforded the playing time.
In 2025, he was able to increase his bat speed by almost 3 mph, and his plate discipline also improved significantly. Following the shift to the team’s hitting approach, he traded some pulled fly balls for more contact inside the zone, going more ground-ball heavy to all areas of the park. For this to be effective, he also drastically improved his contact, increasing his overall effectiveness as a hitter.
His whiff rate on pitches in the zone fell substantially and kept falling through the season. This resulted in a career year. He posted a .356 xwOBA over 218 PA in 2025 while undrafted, then .371 over 578 PA in 2026, helping many a team to a fantasy championship. He will now get a massive payday as a result.
All this to say, a lot goes into a breakout behind the scenes for a player to warrant extra at-bats, or be in position for an opportunity when it arises. But looking under the hood, the signs are there.
But from this list, I think there will be names that we can at least keep an eye on throughout the winter. Especially in the younger bats, where they will have increased value in any deeper or dynasty formats. The likes of Valencia, Bernal, Flores, and Jones, to name just a few, could all have increased roles in 2027 and will have low ADP even if they showed us something in 2026. Deeper player-focused dives will come in the future.
These groups are small, and the conversion rate as a whole group is low, but with some research, common sense, and projection, there is a ton of value to be found in the back end of drafts following a pretty simple strategy.
Jack Martin is a contributor for RotoGraphs and previously covered the Seattle Mariners for Last Word On Sports. Follow him on Twitter @_jackmrtn.
I suspect if you added age and injury to your methodology you could predict playing time increases more consistently. Fun list though