The last player to hit for a .400 batting average over a full season was Ted Wiliams (.406 in 1941). Twenty players have recorded a batting average of at least .400, with Ed Delahanty, Ty Cobb, and Rogers Hornsby having reached that milestone in three different seasons. It is extremely difficult to accomplish and hasn’t been done in 80 years.

In 60-games batting average may very well be the highest variant statistic in fantasy baseball. After all, there are so many variables that go into the end result. Hitter skill, opponent skill, ballpark, defense, luck, and weather. But on the flip side, certain variables are easier to sustain over a shorter amount of time, namely player skill & luck. 162-games is simply too long for most hitters to sustain focus and stamina the entire time. Hot streaks and cold streaks come and go, all leading to the player’s average at the end of the season. In 2020 expect to see hitters be all-in for almost every game.

The other variable is luck. This can come in many forms, but the one we will be taking a look at in this article will be BABIP (batted avg for balls in play). To be clear BABIP is not “luck-based,” as it is merely a mathematical equation. However, the variables that contribute to BABIP can be. More importantly, there are many skills that a hitter may possess that will naturally allow them to carry a higher BABIP and therefore a higher batting average.

Before we get started, know that this is simply an exercise in data analysis and fun. That being said, this article should be a useful tool in teaching you about what makes a high batting average hitter and how to look for players who can sustain one.

Batting Average 101

 

Batting average is the oldest and most universal tools to measure a hitter’s “success” at the plate. It is determined by dividing a player’s hits by his total at-bats for a number between zero (shown as .000) and one (1.000). Tell you something you don’t know right?

While batting average can be a useful tool for measuring a player’s ability at the plate quickly, it is flawed and tells you little about a player’s skill. For example, batting average doesn’t take into account a player’s ability to take walks or avoid strikeouts. It also does take into account hit type (single, double, triple, or home run).

Let’s take a look at recent batting champions to see what they have in common:

2016: Jose Altuve (.338) & DJ LeMahieu (.348)

2017: Jose Altuve (.346) & Charlie Blackmon (.331)

2018: Mookie Betts (.346) & Christian Yelich (.326)

2019: Tim Anderson (.335) & Christian Yelich (.329)

For starters, with the exception of Tim Anderson (18.1), all of the players above held a K-BB% under 11%. Plate discipline is a skill and without it you are unlikely to find yourself on base very often.

The other variable they have in common is BABIP. Only one batting champion ended the season with a BABIP under .355 (Altuve 2016 .347), while six of eight carried a mark of .368 or higher. Considering a league average BABIP sits around .300, this is something we need to investigate.

What is BABIP?

 

BABIP measures a player’s batting average based entirely on balls hit into the field of play, removing outcomes not affected by the opposing defense (mostly HR & K):

(H – HR)/(AB – K – HR + SF)

BABIP tends to be scrutinized as a statistic often due to a reputation for showcasing a player being “lucky” or “unlucky.” As stated in the previous section, the league average BABIP is .300, so if a player drifts too far above or below that threshold people seem to grow skeptical. Which is not entirely unfounded. Sometimes the hits just seem to fall in at a natural rate.

That being said, batters who have seen a high or low percentage of their balls in play drop in for hits over a period of time will see their results average out over 162-games. This is what takes most “luck” out of the equation for most years. But in 2020 we are playing 102 fewer games, so the variance will be greater.

So what SKILL based attributes contribute to a high BABIP? What can we look for in a player that allows players like the batting champions above to carry such a high BABIP? Sometimes year over year.

 

Skill Based BABIP Production

 

The following skills contribute to a player carrying a higher BABIP, thus allowing them to carry a higher batting average than your typical major league hitter:

 

Plate Discipline:

We already talked about this above, and it is very straight forward. You can’t steal first base, you need to earn it. Walks will not help in this scenario, but pitch recognition and patience will.

Striking out will send you back to the dugout, but will not impact your BABIP. It will however impact your batting average. In addition, the lack of plate discipline typically tied to a high K% is also typically tied to poor pitch selection. Poor pitch selection leads to poor contact. Poor contact leads to outs. Outs lower your batting average.

Superior contact leads to hard contact. Hard contact raises your BABIP (see below).

We could look further into metrics such as O-Swing% and SwStr%, but for our purposes, this can be neatly packaged through the K-BB%.

 

Hard Contact:

There is a strong yearly correlation between a high hard contact rate and a higher BABIP. In 2019, 17 out of the top-30 players in Hard% carried a better than league average BABIP. in 2018? 19 of the top-30.

If you hit the ball hard you typically made solid contact, which also allows less time for the fielder to react. No out, higher BABIP, higher batting average. But this is just one variable of many, since you may have guessed there were many hitters with a high Hard% who carry a poor batting average.

 

Line Drive %:

This more or less is tied to the previous variable Hard%, but with an important distinction: batting average results. A line drive is by definition a ball driven on a line, which is normally accompanied by hard contact. Also one of the more obvious signs of solid hitter.

In 2019 the American League hit .692 on line drives, while the National League hit .681. Pretty cut and dry. Line drives equal a higher BABIP and batting average.

 

Fly Ball %

This variable is bit contradictory. Home runs are good, but they do not count towards a player’s BABIP (not considered batted balls since they are not in the field of play). In addition, outfield flys are often the easiest plays for a fielder to make, so for our purposes in this exercise, we will be looking to avoid hitters with a high FB%.

 

Sprint Speed

Ground balls are the WORST. In fact, the league average on batted ground balls in 2019 was .237 & .235. Yikes. No one performs well on groundballs.

BUT some are better than others. What is the best way to avoid an out on a ground ball? Beat it out for a single. Players with a higher sprint speed are able to leg out more ground balls for hits, stretching their BABIP and batting average.

This could certainly come in handy over small sample size.

 

 

The Quest for .400 Criteria

 

If we are hoping to place a bet on someone to crack .400 in a 60-game season we are going to want to set some rules for what could make them the most successful. Talent is paramount, so we will be starting with batted ball profile and plate discipline. But if history shows us anything, the way to complete this task is through BABIP based skills and BABIP based luck. Remember, we are not looking for who is most likely to win the batting title, we are looking for someone capable of pulling off a feat not reached in 80 years.

By now you have a good idea of what criteria is needed on the quest to .400, so let’s set some parameters and narrow down the field of contenders.

1.) K-BB% under 12%

 

 

2.) Line Drive% over 23%

 

 

3.) Fly Ball% under 40%

 

 

4.) Hard Contact% over 40%

 

 

5.) Sprint Speed over 27 ft/sec

 

 

The above criteria are better than league average in all areas, and those who check off the most boxes should stand the best chance at success. No player is perfect, but some are certainly better built for a sustained run of skill. Even fewer are built to put themselves in a position to be lucky.

 

The Quest for .400 Results

 

Tier 1: Christian Yelich (OF, Brewers), Bryan Reynolds (OF, Pirates)

 

The Chase For .400 – Tier 1
Name Team AVG BABIP LD% FB% Hard% K-BB% Sprint Speed xwOBACon
Bryan Reynolds Pirates 0.314 0.387 24% 30% 43% 14% 28.1 0.426
Christian Yelich Brewers 0.329 0.355 21% 36% 51% 7% 28.7 0.501

 

Christian Yelich

There is not much to say here. The reigning, defending NL Batting Champion for the last two seasons is also among the best options to hit .400 in 2020. Yelich does everything well, falling just shy of our LD% threshold for a perfect score.

A .501 xwOBAcon and 51% hard contact rate should tell you all you need to know. However, a 28.7 ft/sec sprint speed and elite K-BB of 7% gives him that extra edge to not only repeat as a three-time batting champion but flirt with .400 this year.

 

 

Christian Yelich is the favorite.

Bryan Reynolds

 

Wait, what? Bryan Reynolds?

Yes! Bryan Reynolds. The Pirates outfielder has a steady track record of not only carrying a high batting average throughout his entire career but a high BABIP. In fact, Reynolds has never batted under .300 at any stop along the way, only batting below .312 once. His career-low BABIP sits a .362, w/ a career avg above.390.

Reynolds holds a fantastic 24% line drive rate and manageable 30% fly-ball rate, all while hitting the ball with authority (43% Hard Contact). All of this is backed up by a stellar .296 xBA and .426 xwOBAcon. Feel free to doubt the man, but he holds almost all of the tools needed to crack this thing open, including a solid 28.1 ft/sec Sprint Speed.

The only thing keeping Reynolds from being the ONLY perfect candidate (by our cherry-picked standards) is his K rate. But even though his K-BB% (14%) was higher than we would like, his SwStr% and O-Swing% (swings outside of the strike zone) were within the MLB average.

A 60-game schedule that includes seven games at Cincinnati should help the cause. but overall his line drive approach should allow him to take advantage of large ballparks as well. Bryan Reynolds may very well be one of the best bets to hit .400 this season.

 

 

Remember: We are looking for candidates to hit .400, not win the batting title. There is a difference.

 

Tier 2: Cody Bellinger (OF, Dodgers), Mike Trout (OF, Angels)

 

The Chase For .400 – Tier 2
Name Team AVG BABIP LD% FB% Hard% K-BB% Sprint Speed xwOBACon
Cody Bellinger Dodgers 0.305 0.302 26% 42% 49% 2% 28.8 0.486
Mike Trout Angels 0.291 0.298 27% 49% 44% 2% 29.2 0.534

 

Cody Bellinger

Some may be surprised that Cody did not make it into Tier One. The simple answer is that he simply hits too many fly balls.

The batting title upside is certainly there, along with the ability to lead the league in home runs. Cody Bellinger is an MVP for a reason. But the elevation level he tends to live in does not bode well for a high BABIP which could result in a few costly outs. In 60-games that is enough to bump even an elite talent like Bellinger out of the top tier.

 

 

However, Bellinger absolutely smokes the ball, carrying a 25% line drive rate and 49% hard contact rate. Fly balls or not, Cody is going to be on base quite a bit. Just look at his microscopic K-BB% (2%). Those factors combined with his near-elite speed (28.8 ft/sec) make Bellinger a top candidate to hit .400

 

Mike Trout

We are obviously not factoring in any kind of “opt-out” or missed playing time into this scenario. We are assuming a healthy Mike Trout that is playing all 60-games.

His dance card reads about the same as Cody Bellinger. Too many fly balls (49%). IF you are going to be putting over half of your batted balls into the outfield, that is going to severely limit your BABIP potential.

Nevertheless, Mike Trout is one of a kind. He excels in every area of the game and will be a top candidate to takedown .400 in a shortened season.

 

Tier 3:

Austin Meadows (OF, Rays), Jose Altuve (2B, Astros), Luis Arraez (2B, Twins), Mookie Betts (OF, Dodgers), Tim Anderson (SS, White Sox)

 

The Chase For .400 – Tier 3
Name Team AVG BABIP LD% FB% Hard% K-BB% Sprint Speed xwOBACon
Austin Meadows Rays 0.291 0.331 23% 43% 45% 13% 28.1 0.450
Jose Altuve Astros 0.298 0.303 18% 33% 41% 8% 28.6 0.383
Luis Arraez Twins 0.334 0.355 29% 29% 35% −2% 26.9 0.326
Mookie Betts Red Sox 0.295 0.309 25% 44% 43% 1% 27.9 0.437
Tim Anderson White Sox 0.335 0.399 24% 28% 32% 18% 28.7 0.403

 

Austin Meadows

Meadows was able to make very hard contact last season. However, most of his work was done by pulling the baseball. In fact, Meadows hit 17 of his HR in the final 50 games. Not surprisingly, he pulled the ball 14% more during this power stretch.

This approach led to a 43% fly-ball rate, which for our purposes is not ideal. However, Meadows also carried just a 34.1% ground ball rate, which is fantastic. All of Meadows’ hard contact (45%) came through line drives (23%) and fly balls, this along with a 28.1 ft/sec spring speed allowed Meadows to carry a .331 BABIP.

He even has solid hitting splits:

VS LHP: .275/.316/.521

VS RHP .298/.384/.576

Overall, he strikes out a little too much and his overall approach may hinder his chances of going for .400 this year. But he has the tools to make it happen.

 

Jose Altuve

The 2016 and 2017 batting champion decided to go completely pull happy in 2019, raising his Pull% to an even 50 percent. This allowed his hard contact to climb to a career-best 40.8%. However, this adjustment away from his typical approach also led to a career-worst line drive rate of 17.6%.

Altuve’s xwOBAcon fell below our expectations for a top candidate, but it was still above the league average.

The bottom line with Altuve is that we know what he is capable of but what we saw last year was kind of a total deviation from that. If he continues down this path for sell-out. power, Altuve will not stand a chance of taking this thing down. But he still has the capability.

 

Luis Arraez

Arraez has a swinging strike rate of 2.8% (league average is 11.1%). That is insane. In fact, his K-BB% is a negative two percent. Add in a 93.3% contact rate (yes, 93.3) and you have a payer that should jump right to the top of this list.

There is only one issue. He hits the ball like he is trying to quietly wake it up from a nap.

Arraez makes for a fantastic candidate to win the batting title, but he lacks the BABIP skill to make a run at .400

 

Mookie Betts

I kinda wanted to see Mookie in Tier Two due to all of the motivation he has this season. Free agency is coming and it could be a laser show in Los Angeles.

Unfortunately, the same as his teammate Cody Bellinger and cross-town rival Mike Trout, Mookie simply hits too many fly balls. He also heads away from the AL East into some of the tougher parks in the majors to be a fly ball hitter.

Overall Mookie is one of the more intriguing contenders to hit .400 if he gets on a hot streak and very possibly deserves to be in the second tier.

 

Tim Anderson

Anderson seems to have his share of doubters in the baseball community. But the fact of the matter is the same reason he was able to win the batting title in 2019 is the same reason he can hit .400 in 2020.

Timmy checks almost all of the major boxes in our criteria for this quest. High LD%, low FB%, plus Sprint Speed, and a .403 xwOBAcon. His biggest issue is the strikeouts. It’s tough to give that many free outs to the opposition without putting the ball in play.

That being said if Anderson were able to carry a higher hard contact % (32%), he would be a REAL contender to make something magical happen.

2019 monthly batting avg splits:

Mar/Apr – .375

Aug – .364

Sept/Oct – .374

 

 

Tier 4:

Alex Bregman (3B, Astros), Alex Verdugo (OF, Red Sox), Anthony Rendon (3B, Angels), Lorenzo Cain (OF, Brewers), Whit Merrifield (2B/OF, Royals)

 

The Chase For .400 – Tier 4
Name Team AVG BABIP LD% FB% Hard% K-BB% Sprint Speed xwOBACon
Alex Bregman Astros 0.296 0.281 23% 46% 45% −5% 27.4 0.360
Alex Verdugo Dodgers 0.294 0.309 23% 29% 44% 6% 27.3 0.353
Anthony Rendon Nationals 0.319 0.323 21% 46% 45% 1% 26.7 0.445
Lorenzo Cain Brewers 0.260 0.301 26% 24% 37% 9% 27.8 0.362
Whit Merrifield Royals 0.302 0.350 29% 34% 38% 11% 28.6 0.369

 

Alex Bregman

Bregman is someone who smartly takes advantage of his home surrounding in Houston. No, I am not talking about trash cans. I am talking about park factors, Bregman carries a 46% fly-ball rate and one of the shortest avg HR distances in the majors.

Minute Maid Field has allowed Bregman to take advantage of a short porch in left field while being one of the best all-around players in the game. His aggressive power approach led to a .282 BABIP (.289 in 2018), which is hard to overlook when accompanied by a .360 xwOBAcon.

Bregman is a fantastic player, but .400 is likely out of his reach despite the tools he possesses.

 

Alex Verdugo

Verdugo does not hit many FB and he had a near top-25 LD% (29%). However, he is middle of the road in Exit Velocity (58th%). This seems like a mistake, which upon further inspection, kind of is. Verdugo’s FB/LD EV was 93.1 mph, good enough to eclipse Nolan Arenado and Gleyber Torres.

The bad news is that Verdugo’s avg EV was held down by ground balls, in which he hit 48.7% of the time. Do not bother checking his minor league stats to see if it is a trend, it is. Verdugo hits A LOT of ground balls. Remember earlier when we were discussing sprint speed? The league average on batted ground balls in 2019 was .237 & .235. Not good.

The thing that separates Verdugo is contact skills:

SwStr: 6.6%

Contact: 85.2%

Swing: 44.6%

O-Swing: 31.1%

Z-Swing: 62.2%

O-Contact: 72.1%

Z-Contact: 93.7%

Not only does Verdugo limit his SwStr% to almost half the league avg, but he makes contact at an incredible rate. His O-Swing% (swings outside of K zone) is middle of the road, as are all of his swing rates. Which is amazing considering his 13% K rate.

It’s very possible that Verdugo could one day be one of the premier “top of the order” contact hitters in MLB.

 

Anthony Rendon

We all know what Anthony Rendon can do, so I will not waste a lot of time here. He is a fantastic player but just missed in both our parameter for LD% and FB%, all while being just a bit too slow (26.7 ft/sec). Rendon is a good choice, but not a top choice.

 

Lorenzo Cain

Despite coming off the worst year of his career, Lorenzo Cain still produced many skills necessary to hit .400. At this point in his career, we are going to see a major bounceback right now, or we are not going to see one at all. Hard contact will be the main obstacle for the veteran outfielder.

 

Whit Merrifield

Merrifield actually has the same shortcomings as Lorenzo Cain. He possesses a nice LD% profile while limiting excessive fly balls. Whit just lacks the kind of hard contact we would be looking for, even though he has more than enough speed to generate some BABIP magic on the basepath. The tools are there, but an aging Merrifield is likely on his way down, not up.

 

Tier 5:

DJ LeMahieu (2B, Yankees), JD Martinez (OF/DH Red Sox), Jeff McNeil (3B, Mets), Michael Brantley (OF/DH, Astros), Nolan Arenado (3B, Rockies)

 

The Chase For .400 – Tier 5
Name Team AVG BABIP LD% FB% Hard% K-BB% Sprint Speed xwOBACon
DJ LeMahieu Yankees 0.327 0.349 24% 26% 40% 7% 26.7 0.417
J.D. Martinez Red Sox 0.304 0.342 22% 35% 46% 10% 26.7 0.481
Jeff McNeil Mets 0.318 0.337 22% 35% 38% 7% 27.2 0.373
Michael Brantley Astros 0.311 0.320 24% 31% 42% 2% 26.4 0.373
Nolan Arenado Rockies 0.315 0.312 19% 45% 43% 5% 25.9 0.370

 

Most of the hitters in Tier 5 are incredibly talented and could all make a run at .400. But each has their own flaws. LeMahieu, Martinez, Brantley, and Arenado were all a touch slow in Sprint Speed, while Brantley and Arenado also came up short in xwOBAcon.

DJ LaMahieu

LeMahieu shows up strong in the Statcast data, His Hard Contact was 5.2% above his career-high w/ a 3 yr decrease in Weak Contact. Add in the fact that his.322 Expected Batting Average (xBA): xBA measures the likelihood that a batted ball will become a hit. Each batted ball is assigned an xBA based on how often comparable balls — in terms of exit velocity, launch angle and, on certain types of batted balls, Sprint Speed — have become hits since Statcast was implemented Major League wide in 2015. By comparing expected numbers to real-world outcomes over a period of time, it can be possible to identify which hitters (or pitchers) are over- or under-performing their demonstrated skill.”>xBA (top 1%) matches up w/ his .327 avg and you have yourself a contender.

The issue is ground balls (discussed in the tweet below):

 

Crazy right? In fact, Lemahieu hovered near the 55% mark for most of his career. This was survivable at Coors when he was able to generate a .388 BABIP (Batting Average on Balls in Play): The rate at which the batter gets a hit when he puts the ball in play, calculated as (H-HR)/(AB-K-HR+SF).”>BABIP, but how did he manage success in NY (.349 BABIP (Batting Average on Balls in Play): The rate at which the batter gets a hit when he puts the ball in play, calculated as (H-HR)/(AB-K-HR+SF).”>BABIP)? One would think leaving COL w/ that BABIP (Batting Average on Balls in Play): The rate at which the batter gets a hit when he puts the ball in play, calculated as (H-HR)/(AB-K-HR+SF).”>BABIP would spell doom.

The simple answer is that DJ is just plain hitting the ball harder. This doesn’t dismiss concerns, but it helps to explain them. The MVP candidate has the tools to be a contender in the quest for .400

 

JD Martinez

Martinez is a near-elite option to contend for a batting title, but his Sprint Speed: A measurement of a player’s top running speed, expressed in “feet per second in a player’s fastest one-second window.” This can be delivered on individual plays or as a season average, found by finding all qualified runs (currently defined as anything two bases or more, excluding homers) and averaging the top half of those. In 2017, Buxton led the Majors with a Sprint Speed of 30.2 ft/sec, while the Major League average was 27 ft/sec.”>sprint speed and strikeout rate put him just out of the upper tiers. The man can hit, and it should not be a surprise if he made something special happen in 60-games.

 

Jeff McNeil

Jeff McNeil seems to be slightly disrespected in this process, but he just falls short of having elite BABIP (Batting Average on Balls in Play): The rate at which the batter gets a hit when he puts the ball in play, calculated as (H-HR)/(AB-K-HR+SF).”>BABIP skills we are looking for. He is a very cerebral hitter who is capable of achieving a .400 average over 60-games, but his recent attempts to pull and elevate the ball out his chances into question.

In July Jeff McNeil made a timing adjustment in order to increase HR/XBH in the most efficient way possible, attacking fastballs. In the 2nd half, McNeil destroyed fastballs.

vs 4-seam FB (wOBAcon/expected weighted On Base Average takes wOBA and adds in Statcast data — specifically, “exit velocity, launch angle and, on certain types of batted balls, Sprint Speed.” xwOBAcon is a very specific derivation: it is the expected Weighted On Base Average of just the contact, so it excludes walks and hit by pitches, but still uses Statcast data on the contact.”>xwOBAcon):

1st Half – .307/.309

2nd Half – .518/.475

The adjustment allowed him to reach the Barrels: A batted ball with the perfect combination of exit velocity and launch angle, or the most high-value batted balls. (A barrel has a minimum Expected Batting Average of .500 and Expected Slugging Percentage of 1.500.)”>barrel to the ball (Increased Barrels: A batted ball with the perfect combination of exit velocity and launch angle, or the most high-value batted balls. (A barrel has a minimum Expected Batting Average of .500 and Expected Slugging Percentage of 1.500.)”>barrels on FB 7.9%), but came with a drop in batting average. Although the timing adjustment allowed McNeil to attack fastballs, it also hindered his ability to square up breaking pitches Before the break he was batting .318 w/ a 52.6 LD% against breaking balls Since then, he dropped to .197 w/ a 24.5 LD%. So like we discussed above, McNeil can be the high BABIP (Batting Average on Balls in Play): The rate at which the batter gets a hit when he puts the ball in play, calculated as (H-HR)/(AB-K-HR+SF).”>BABIP line-drive hitter we saw in the 1st half, but we are likely to see his pull heavy power approach hurt his chances at the milestone.

This seems like another great time to remember that we are not looking for a batting champion, we are looking for someone to bat .400. They will need every tool in the bag to pull this off and even those names above (superstars) may lack what is necessary to reach that plateau.

 

Michael Brantley

Brantley is another great option if you were placing a bet on who could win the batting title this season. His high contact, low strikeout approach is perfect for it. However, he lacks a certain level of authority when striking the ball, shown by his 29% Barrels: A batted ball with the perfect combination of exit velocity and launch angle, or the most high-value batted balls. (A barrel has a minimum Expected Batting Average of .500 and Expected Slugging Percentage of 1.500.)”>barrel rate and 41% exit velocity. Add in a Sprint Speed: A measurement of a player’s top running speed, expressed in “feet per second in a player’s fastest one-second window.” This can be delivered on individual plays or as a season average, found by finding all qualified runs (currently defined as anything two bases or more, excluding homers) and averaging the top half of those. In 2017, Buxton led the Majors with a Sprint Speed of 30.2 ft/sec, while the Major League average was 27 ft/sec.”>sprint speed also hanging in the 41% (26.4 ft/sec) and you cut down on those extra BABIP (Batting Average on Balls in Play): The rate at which the batter gets a hit when he puts the ball in play, calculated as (H-HR)/(AB-K-HR+SF).”>BABIP driven chances to hit .400

 

Nolan Arenado

In fact, Nolan Arenado was the most surprising person on this list in terms of not finishing higher. A lower LD%, and 45% fly-ball rate took him out of the running without even factoring in his 25.9 ft/sec Sprint Speed: A measurement of a player’s top running speed, expressed in “feet per second in a player’s fastest one-second window.” This can be delivered on individual plays or as a season average, found by finding all qualified runs (currently defined as anything two bases or more, excluding homers) and averaging the top half of those. In 2017, Buxton led the Majors with a Sprint Speed of 30.2 ft/sec, while the Major League average was 27 ft/sec.”>sprint speed. Even though his home ballpark will give him a boost in BABIP (Batting Average on Balls in Play): The rate at which the batter gets a hit when he puts the ball in play, calculated as (H-HR)/(AB-K-HR+SF).”>BABIP driven luck, he has an unfavorable schedule this season and comes up short across the board in our criteria for the .400

 

Interesting Outliers:

Domingo Santana (OF, Indians), Justin Turner (3B, Dodgers), Miguel Cabrera (1B/DH, Tigers), Trevor Story (SS, Rockies), Yoan Moncado (3B, White Sox)

 

 

The Chase For .400 – Interesting Outliers
Name Team AVG BABIP LD% FB% Hard% K-BB% Sprint Speed xwOBACon
Domingo Santana Mariners 0.253 0.347 27% 31% 43% 22% 26.7 0.483
Justin Turner Dodgers 0.290 0.304 26% 40% 50% 7% 26.1 0.410
Miguel Cabrera Tigers 0.282 0.336 24% 32% 44% 11% 23.5 0.381
Trevor Story Rockies 0.294 0.361 24% 42% 44% 18% 29.2 0.425
Yoan Moncada White Sox 0.315 0.406 23% 35% 40% 20% 27.8 0.478

 

All of the above players popped up several times in my research for this article, so I felt the need to acknowledge them briefly at the end.

Justin Turner

By most accounts, Justin Turner should have landed on the list. He is one of the best hitters in baseball that no one talks about and could be very dangerous if healthy over 60-games. But he is one incredibly slow dude (along with Miguel Cabrera)

Trevor Story & Yoan Moncada

Both very talented. Both strikeout way too much.

Moncada has all of the tools to carry a high BABIP, just as he did last season. But it’s tough to imagine making a run at something like. Although Moncada did dramatically improve his approach, especially in terms of pitch selection, last season.

Trevor Story has Coors Field as a BABIP crutch, which is nice. But in addition to a poor K%, he elevated the ball more than we would like to see for this exercise.

If someone is going to make a run at .400 at Coors field it is going to be Arenado, or maybe even Blackmon.

 

Domingo Santana

No one is saying Domingo Santana can hit .400, so stop it. He holds a 22% K-BB rate and one of the worst K% in all of baseball. That being said Santana checks off A LOT of the other boxes in a strong fashion.

His O-Swing% is actually well below league average despite a higher SwStr%. Santana’s main issue is not pitch selection, but contact. But the thing is, he did hold an xwOBAcon of .483, which is respectable. I can’t help but think what a change of scenery from Seattle to Cleveland and a little bit of good luck could bring Domingo in 2020.