Insights on BABIP

BABIP is a measure of batting average when the ball is put in play on the baseball field. Before talking about the details, let’s look at one quote and two reasons BABIP is useful.

“The pitcher has limited control over what happens once the ball is put in play. This was discovered 20 years by Voros McCracken. The hitter has more control than the pitcher.” —Jack Sommers

Because pitchers don’t have control (except when they participate in fielding the ball in play), BABIP can be a tool that indicates when a pitcher’s hits allowed were more or less than expected over the long term.

Hitters have significant control of BABIP. It is one of several measures that, when considered together, indicate the strength of a batters’ hit tool. Let’s look at it.

BABIP reflects performance based on each batters’ “hit tool” skill.

Keith Law and Eno Sarris wrote about the 5 tools of baseball. In general, they defined hit tool as a high rate of quality contact without a high strikeout rate. Players with top hit tools have high BABIPs, as well as meeting standards in other measures.

Let’s look at whether any 2020 Diamondback hitters showed a top level hit tool. That determination will require three steps:

• Pick six gold-standard players from the Law & Sarris article (Mike Trout, Freddie Freeman, Alex Bregman, Anthony Rendon, Miguel Cabrera, and Joe Mauer).
• For those six players find the minimum measures for high rate of quality contact (BABIP, hard hit %, and barrel %), and maximum strikeouts (K%).
• For 2020, see which Diamondbacks met the minimums, and which Diamondbacks met all but one measure (and came close on that measure).

The fantastic news is that Christian Walker hits like the elite gold-standard players, exceeding all the minimums, with strikeout percent less than the maximum. He had the best hit tool on the team.

Photo by John McCoy/Getty Images

More good news is that three Diamondbacks came close to the gold standard.

• David Peralta fell short on hard hits (36.3% vs 36.7%). That was very close. In 2020, David Peralta’s BABIP ranked 20th in the Majors (160 min PA). That is remarkable because the previous season, no Diamondback was in the top 50.
• Ketel Marte fell short on barrels (3.7% vs 3.9%). That was very close and optimistically he will achieve the gold standard next season. His strikeout rate (10.8%) is outstanding.
• Nick Ahmed fell short on hard hits (33.3% vs 36.7%). Because Ahmed’s excellent defense at shortstop is valued highly, his great hitting is like icing on the cake.

League-wide, does BABIP change each month of the season?

Ben Lindbergh wrote that in the last 25 seasons, the League-wide average BABIP had never dipped below .283 in any stretch of 18 games until the first 18 games of the 2020 season.

Based on data from 2002 to 2019, his chart showed monthly average BABIP starting each season at .293, peaking at .300 in July and August, and falling to .298 in September/October.

With data from Stathead (Baseball Reference), I calculated league-wide BABIP by month for the last 10 years (2010 through 2019). Amazingly, the monthly averages are the same as for the last 18 years, except for August is .299 instead of .300 and September is .297 instead of .298. An important observation is that the standard deviation is fairly constant at around .020 for each month’s data. That tells me two things:

• The change from month to month is much less than a half of a standard deviation. Nevertheless, it is very interesting that each month’s BABIP stays so constant. It’s worthy of investigation.
• The dip in the first 18 games of the 2020 season from .293 to .276 can be thought of as a dip of 0.81 standard deviations, which is expected to happen 21 of 100 times by chance.

Let’s look at BABIP by month for 2020 (albeit that July was less than a whole month).

• July, .277 BABIP, .034 standard deviation.
• August, .292 BABIP, .021 standard deviation.
• September, .295 BABIP, .023 standard deviation.

It appears that BABIP is within the bounds of statistical variation. Nevertheless, the 2020 season will lower the 10-year average of BABIP.

League-wide, what causes changes in BABIP?

A change in batting strategy could change BABIP. For example, BABIP could be lowered if sacrifice flies become more common. Another example would be if batters swung for the fences at the cost of increased strikeouts. The homers would lower BABIP (by replacing hits by homers) while the strikeouts would raise BABIP (by increasing the percentage of strikeouts for at-bats).

Better fielding would lower BABIP. Three factors to consider.

• Less noisy crowds (for example when no fans are allowed, or when only 50% of stadium capacity is allowed) can help fielders by reducing potential distractions.
• Shifts (infield and outfield) seem to be increasing every year. Effective shifts lower BABIP.
• Minor changes (within the specs) to baseball manufacturing can have a significant impact on BABIP. For example, seam height changes will change how far the ball travels. Tangotiger tweeted a chart that shows how wOBA changes as a function of distance the ball travels.

The trend of reduced innings by starters could reduce BABIP. By reducing or eliminating the third time through the order by the starting pitcher, hitters will miss the chance to adjust to achieve a successful at-bat.

Pitchers cannot control BABIP.

“There is little if any difference among major-league pitchers in their ability to prevent hits on balls hit in the field of play.” — Voros McCracken

He had many reasons for his statement. Two follow:

• “The pitchers who are the best at preventing hits on balls in play one year are often the worst at it the next.”
• “The range of career rates of hits per balls in play for pitchers with a significant number of innings is about the same as the range you would expect from random chance.”

The formula for BABIP includes hits (H), homers (HR), at-bats (AB), strikeouts (K), and sacrifice flies (SF).

Formula from MLB.com glossary.