In the prior article, we identified three distinct “batted-ball” components of offense:

- BABIP (the familiar “hits per balls-in-play” which does not encompass home runs);
- 2b3b / Bttd, which is doubles & triples per all batted balls (which does encompass home runs) ; and
- HR / Bttd, which is homers per all batted balls.

Which we then morphed into “batted ball” versions of the two components of OPS:

- BACON (“batting average on contact” or ‘hits per batted ball”); and
- BtISO (“batted-ball ISO” or ISO based solely on batted balls).

We will apply these measuring sticks to our database of 537 qualified MLB hitters with at least 1,500 career plate appearances since 2002 (when batted-ball data is first available). All of which accounts for almost 1.9 million cumulative PAs.

First up for analysis is ground balls. What is the relationship between ground balls and BABIP? Here’s the chart:

So, we see a mild positive relationship between ground balls and “hits-in-play” (non-HR hits). The “goodness-of-fit” (R-squared) of 0.13 indicates that there might be something meaningful here, but that we don’t have very much of the picture in focus [remember that R-squared approaches a “perfect fit” at 1.0].

Let’s move on to the rest of the picture, then.

***

Here’s our non-HR extra-base hits.

We can certainly see, as we might expect, a general negative relationship between ground-ball rate and doubles + triples, but the effect is fairly mild. Thus, the explanatory power (R-squared of 0.1) remains pretty weak.

***

Finally, homers.

While it’s not completely implausible that hitters who hit a lot of homers might also hit a lot of ground balls, reality does seem to comport with the more intuitive notion that hitters who launch the ball in the air more often will have more of those balls clear the fence.

Put another way, guys who tend to hit the ball on the ground hit fewer homers.

And our “model” — more ground balls means fewer home runs — has some explanatory power (R-squared of 0.3).

***

Therefore, **while GB% seems to boost BABIP, it does so only with singles**, which makes sense. Fly balls that don’t clear the fence are pretty likely to get caught. But ground balls usually have a chance to sneak through. Just not for extra bases.

So how does it all net out?

For all hits off all batted balls, we have our cleverly-named BACON (hits per batted-balls):

Clearly you couldn’t draw it up much more neutral than that.

In that data set there is essentially no relationship between the rate of ground balls and the rate of hits. The “explanatory power” (R-squared) is virtually zero.

So in terms of “getting a hit” vs. “batted-ball out” (the “on-base” portion of batted-ball offense) … GB% is a non-factor.

That’s not an earth-shattering conclusion, and really the most important thing our analysis of ground balls reveals is that ground-ball rate for hitters seems to have no meaningful impact at all on whether the hitter gets a hit or makes an out.

This neutrality, however, comes about because the mild positive impact on singles makes up for the significant negative impact on extra-base hits.

If we look at the “slugging” component of our “batted-ball OPS” — which we have designated as “BtISO” (batted-ball ISO), we see that ground balls are clearly negative in that aspect:

Therefore, in the totality of “batted-ball offense”:

- Ground balls are
**neutral**in terms of**reaching base**

- Ground balls are
**negative**in terms of**producing offense**

Here’s part 4.

HR/Bttd chart x-axis should be labeled GB%

Maybe I meant Bound Gralls? Thanks, Bat I’ll fix it!