We tend to talk about hitting leaderboards as though they answer a simple question. Who has been the best hitter?
It is not quite that simple. A hitter can produce enormous value through power, another through reaching base, another through a combination of contact and baserunning. Rate statistics can identify extraordinary performance while overlooking playing time. Counting statistics reward accumulation but can obscure efficiency. WAR goes even further, mixing offense with defense and positional value.
For this study, I wanted to ask a narrower question: Who has actually produced the most offensive value in Major League Baseball so far in 2026?
I used my September 5 FanGraphs downloads, containing 142 hitters and a wide range of traditional, advanced, Statcast, baserunning, and value statistics. The results reveal a clear No. 1. They also reveal something more interesting underneath.
Measuring offensive production
The primary statistic for the study is FanGraphs Offense. In the data, it has a particularly useful decomposition:
\mathrm{Offense}_i = \mathrm{Batting}_i + \mathrm{BaseRunning}_iThat makes it attractive for this question.
Defense is absent. Positional adjustment is absent. We are measuring what a player has contributed when his team is at the plate or when he is running the bases.
WAR is still useful, but it answers a different question. Here I wanted to isolate offense.
The initial leaderboard is striking.
Yordan Alvarez leads baseball with 52.31 offensive runs above average. Pete Crow-Armstrong is very close behind at 49.45.
Then comes a cliff.
James Wood is third at 33.68, followed by Shohei Ohtani at 32.85 and Randy Arozarena at 30.61. The difference between Alvarez and Crow-Armstrong is only 2.86 runs. The difference between Crow-Armstrong and Wood is nearly 15.8 runs.
So, at least by this measure, 2026 has developed a clear top tier of two.
Alvarez and Crow-Armstrong arrived there differently
The decomposition is useful because Alvarez and Crow-Armstrong have not constructed their offensive value in the same way.
For Alvarez:
\mathrm{Offense}_{\mathrm{Alvarez}} = 57.01 - 4.70 = 52.31His bat has been so productive that he can lose almost five runs through baserunning and still lead everyone.
Crow-Armstrong presents almost the opposite profile:
\mathrm{Offense}_{\mathrm{CrowArmstrong}} = 43.77 + 5.68 = 49.45His batting contribution is excellent, but his legs add another 5.68 runs.
That distinction can be seen clearly when batting and baserunning are separated.
Alvarez is sitting far to the right because of his extraordinary batting value, but below zero in baserunning. Crow-Armstrong combines one of baseball’s best bats with strongly positive running value.
James Wood and Ohtani fall somewhere between those extremes.
There is no single recipe.
Rate production tells almost the same story
A natural objection to using total offensive runs is that playing time matters. A player can accumulate more value simply because he has received more plate appearances.
That is where wRC+ becomes useful.
Across the 142 hitters in the dataset, FanGraphs Offense and wRC+ have a correlation of approximately:
r = 0.970A simple regression gives:
\widehat{\mathrm{Offense}}_i = -60.98 + 0.618 \left( \mathrm{wRC}^{+}_i \right)with:
R^2 = 0.941
That is an exceptionally tight relationship.
It should not be interpreted as independent validation, since Offense and wRC+ are built from related offensive information. What it does show is that differences in playing time and baserunning have not radically reordered the best hitters. The strongest rate producers are generally producing the most total offensive value as well.
And once again, Alvarez sits at the top.
His 180.5 wRC+ is the best in the dataset. Crow-Armstrong follows at 157.6, while Willson Contreras, James Wood, Bryce Harper, Randy Arozarena, Junior Caminero, and Ohtani form the next group.
An approximately 181 wRC+ means that Alvarez has created runs at roughly 81 percent above league average, after the adjustments built into wRC+.
That is a remarkable offensive season.
But what should have happened?
Observed production is only half of the story.
Statcast gives us another way to look at these hitters. Instead of merely asking what happened, xwOBA asks what we would expect from the quality of the contact, along with the other inputs incorporated into the statistic.
I calculated the difference as:
\Delta \mathrm{wOBA}_i = \mathrm{wOBA}_i - \mathrm{xwOBA}_iA positive value means the player’s actual wOBA has exceeded his xwOBA. A negative value indicates that his expected production is higher than his observed production.
The comparison changes the story.
Alvarez has a .4289 wOBA, which is already the best in the sample.
His xwOBA is .4496.
\Delta \mathrm{wOBA}_{\mathrm{Alvarez}} = 0.4289 - 0.4496 = -0.0207In other words, the underlying contact data do not suggest that Alvarez has been getting lucky.
They suggest the opposite.
His offensive production has actually fallen about 21 points of wOBA below what Statcast would expect from the underlying events.
Crow-Armstrong provides a fascinating contrast.
\Delta \mathrm{wOBA}_{\mathrm{CrowArmstrong}} = 0.4013 - 0.3684 = 0.0329His actual wOBA has exceeded his xwOBA by roughly 33 points.
That does not invalidate what he has accomplished. Runs that have already scored still count. It does suggest, however, that Alvarez’s underlying offensive performance is considerably stronger than the small difference between their total Offense numbers might initially imply.
James Wood might be the most frightening hitter behind Alvarez
Wood ranks third in total Offense at 33.68 runs, but that ranking almost understates what is happening.
His xwOBA is .4183, second only to Alvarez.
His barrel rate is 20.6 percent, the highest in the dataset. His hard-hit rate is 58.1 percent, also the highest.
Then there is his walk rate: 16.7 percent.
That is an unusual combination. Wood is not simply crushing baseballs. He is also refusing pitches frequently enough to force pitchers into the strike zone.
His main weakness remains strikeouts. His K% is 28.6 percent, which is high. Yet when he connects, the quality of contact is extraordinary.
The upper-right portion of Figure 5 is where we want to look. That region combines high barrel frequency with high expected offensive production.
Wood is there.
So is Alvarez, although Alvarez achieves his even higher xwOBA without matching Wood’s astonishing barrel percentage. Ohtani also occupies the elite region, while Pete Alonso combines tremendous hard contact with a .3946 xwOBA.
These are different offensive machines producing similar outcomes.
Bobby Witt Jr. is an important counterexample
Bobby Witt Jr. does not appear among the very top total offensive producers. His Offense value is 20.88, which ranks 21st in the dataset, and his wRC+ is 121.5.
Yet his xwOBA is .3820.
His actual wOBA is only .3488.
\Delta \mathrm{wOBA}_{\mathrm{Witt}} = 0.3488 - 0.3820 = -0.0332That is one of the largest negative gaps in the entire sample.
Witt has also contributed 7.36 baserunning runs, third best among these hitters. His overall WAR is 6.31, second only to Crow-Armstrong in the dataset.
This is precisely why the definition of “best” matters.
If we ask who has produced the most offense, Witt is not at the very top. If we ask who has played the most valuable all-around baseball, the answer changes substantially. If we ask whose contact suggests better offensive results than he has received, Witt suddenly becomes extremely interesting.
One leaderboard cannot answer all three questions.
A standardized look at offensive styles
To compare very different statistics on a common scale, I standardized six measures across the full 142-player sample.
For player and metric :
z_{i,m} = \frac{ x_{i,m} - \overline{x}_m }{ s_m }For strikeout rate, I reversed the sign so that positive values always represent the favorable direction:
z^{*}_{i,\mathrm{K\%}} = - z_{i,\mathrm{K\%}}The resulting profiles are shown below.
The contrast is useful.
Alvarez is approximately 3.5 standard deviations above the sample mean in wRC+ and almost 3.8 standard deviations above average in xwOBA. There is no obvious weakness at the plate. His major negative component comes from baserunning.
Crow-Armstrong’s profile is more balanced between hitting and running. His ISO is exceptional, and his baserunning value is roughly two standard deviations above the sample mean, but his xwOBA is much less extreme than his actual offensive results.
Wood has perhaps the most intriguing shape of all. His xwOBA, power, and walk rate are spectacular, while his strikeout rate pulls strongly in the opposite direction.
Bryce Harper shows yet another profile. He combines elite plate discipline with strong expected production, but negative baserunning reduces his total contribution.
Four hitters survive almost every test
One way to avoid becoming overly dependent on a particular metric is simply to ask which players remain near the top regardless of how we look.
Only four hitters rank in the top 10 in Offense, wRC+, and xwOBA:
| Player | Offense Rank | wRC+ Rank | xwOBA Rank |
|---|---|---|---|
| Yordan Alvarez | 1 | 1 | 1 |
| James Wood | 3 | 4 | 2 |
| Shohei Ohtani | 4 | 8 | 3 |
| Bryce Harper | 8 | 5 | 5 |
That is a formidable group.
But even within this smaller group, Alvarez separates himself. He is not merely first by one convenient statistic. He is first in total Offense, first in wRC+, first in wOBA, and first in xwOBA.
He also leads this dataset in WPA and RE24.
Different approaches keep returning the same name.
So who has been the best offensive player?
Through September 5, I think the answer is Yordan Alvarez, and the case is unusually strong.
Pete Crow-Armstrong has been close in actual total offensive value and has added considerably more on the bases. His season is extraordinary. But once expected production is introduced, the small gap between them begins to look larger. Alvarez’s .450 xwOBA suggests that the quality of his offensive performance may be even better than the already spectacular results indicate.
James Wood deserves special attention as well. If the question changes from “Who has produced the most?” to “Whose underlying offensive profile frightens me most going forward?”, Wood becomes a serious candidate. A 20.6 percent barrel rate, 58.1 percent hard-hit rate, .418 xwOBA, and 16.7 percent walk rate is an extraordinary collection of traits.
Ohtani and Harper complete what might reasonably be called the most robust elite group in the data.
The larger lesson, however, is about measurement itself. Statistics do not merely rank players. Different statistics ask different questions.
Offense tells us how much was produced. wRC+ tells us how efficiently it was produced. xwOBA tells us what the underlying contact suggests should have been produced. Baserunning shows us how value can be created after the ball leaves the bat.
When all of those measurements point toward the same player, the conclusion becomes difficult to avoid.
So far in 2026, Yordan Alvarez has been baseball’s most impressive offensive producer. That is a fact.
