## FanPost

Last time we looked at the impact of plate discipline has on offensive performance. The more interesting analysis for me is correlation of offensive performance with batted-ball profile.

As a hitting coach, I see a lot parents and other coaches trying to get their players to "hit down on the ball." I argue (like Ted Williams) that the pitch is coming in on a downward plane, so hitters should swing slightly elevated to hit line drives. And that swinging level or down results in mostly ground balls, which are also boring. (Funny, people teach pitchers to pitch for ground balls and teach hitters to hit ground balls.)

Now armed with my linear regression script, we can see how boring ground balls really are.

I ran the model against batted-ball profile on 698 hitters from 2000 until 2013 (batted-ball stats aren't available before 2000). I ran the batted-ball stats for correlation against every offensive category. Below is the data. (I am not uploading all the plots this time, that took forever.)

A little background. Linear regression shows how strong a set of data can be represented by a straight-line. For the data below, I show two values: the r2 and coefficient. The r2 value corresponds to how well a line represents the data. Zero is a terrible fit, one is a perfect fit. The coefficient is the slope of the line, as in y = mx+b. The coefficient is the slope, or m. For example, say a set of data has an r2 value of .8 and a coefficient of 10. That means the data is well represented by a line (.8) and has a strong dependence on the variable (10).

 OPS OPS HR% HR% AVG AVG BB% BB% Rsq Coeff Rsq Coeff Rsq Coeff Rsq Coeff GB-to-FB-Ratio 0.094065 -0.05194 0.308305 -0.01937 0.04887 0.010076 0.051596 -0.01386 LD% 0.005324 0.277745 0.041161 -0.15903 0.101949 0.327101 0.005681 0.103367 GB% 0.104136 -0.40825 0.307193 -0.1444 0.039723 0.067862 0.06957 -0.12022 FB% 0.085048 0.361148 0.369909 0.155104 0.089652 -0.0998 0.054495 0.104155 IFFB% 0.046446 -0.43964 0.003648 0.025373 0.134763 -0.20155 0.031213 -0.12985 HRFB 0.562866 1.145518 0.857717 0.291203 0.014512 0.049503 0.165213 0.2236 IFH% 0.023305 -0.55918 0.039125 -0.1492 0.001166 0.033662 0.059357 -0.32152 BUH% 0.006245 0.02868 0.000006 0.00019 0.003756 0.005987 0.007902 0.011624
 K% K% BB_K BB_K OBP OBP Rsq Coeff Rsq Coeff Rsq Coeff GB-to-FB-Ratio 0.083258 -0.03291 0.001222 0.016797 0.000518 -0.00138 LD% 0.027956 -0.42865 0.037403 2.088448 0.06781 0.355428 GB% 0.081557 -0.24334 0.000016 0.014335 0.004071 -0.02894 FB% 0.111502 0.278518 0.004493 -0.2355 0.000518 -0.0101 IFFB% 0.008211 -0.1245 0.005689 -0.4365 0.123552 -0.25712 HRFB 0.316445 0.578505 0.011457 -0.46366 0.149709 0.211844 IFH% 0.001949 0.10891 0.05342 -2.40179 0.018988 -0.18099 BUH% 0.000448 0.005173 0.003017 0.056554 0.01019 0.013137
 SLG SLG BABIP BABIP wRC+ wRC+ Rsq Coeff Rsq Coeff Rsq Coeff GB-to-FB-Ratio 0.164622 -0.05056 0.107105 0.015745 0.060403 -10.715 LD% 0.000751 -0.07674 0.130932 0.391281 0.004293 64.20394 GB% 0.166032 -0.37929 0.091111 0.108484 0.067135 -84.3853 FB% 0.165905 0.371132 0.171021 -0.14549 0.053711 73.88425 IFFB% 0.014797 -0.18258 0.352376 -0.34402 0.086181 -154.169 HRFB 0.690838 0.933759 0.0231 0.065927 0.495859 276.7879 IFH% 0.019699 -0.37827 0.039002 0.205507 0.012609 -105.884 BUH% 0.003379 0.015523 0.010708 0.010669 0.014816 11.37261

Now I will take a stab at breaking down each category.

OPS

A couple things to note here. Homerun-to-flyball ratio is a GREAT predictor of OPS. Everything else pales in comparison. Interestingly LD% shows basically no correlation. GB% has a decent correlation and with a negative impact. Stop telling kids to hit groundballs!

HR

Again some really good matches. Obviously HR-FB. Hitting flyballs helps. Hitting groundballs hurts. GB-to-FB is a good correlation, but it has not impact. For that matter, GB-to-FB doesn't have much effect on anything. I move to have GB-to-FB ratio removed from stat sheets.

AVG

This one isn't so bad. We get a pretty good relationship between LD% and AVG, with a decent coefficient (remember AVG is less than 1). Maybe there is something to hitting line drives. Not much correlation to ground balls. The cure to a low AVG isn't groundballs. We also start to see where IFFB are really, really bad. (BJ Upton, he of the .177 AVG, has an IFFB% of 22%. Yikes!)

Walks

Best correlation is with HR-to-FB. I am guessing Barry Bonds played a part in this.

Strikeouts

Again best correlation is with HR-to-FB with a pretty big impact. This is the "swing hard just in case you hit it" group.

BB/K ratio

Despite the strong correlations with walks and strikeouts, we see none in the ratio of the two. Supports the theory of two types of sluggers - Barry Bonds type and Chris Davis type.

OBP

Two pretty good fits with HR-FB and IFFB. HR-FB good, IFFB bad. Really bad.

SLG

HR-FB is a huge indicator of SLG, crazy I know. FB and GB have almost exact same correlation and magnitude of coefficient. FB helps, GB hurts.

BABIP

Oh man, does IFFB suck. Basically anything in the air for too long is bad. LD rate is a descent fit with a pretty strong coefficient. As a side note, Cespedes' LD% is down and his FB% is up from 2012, which seems to suggest his BABIP will be lower and that is not just victim of bad luck. Another interesting item is that infield-hit % plays basically zero role in BABIP. One thing that is a little puzzling to me is that GB% helps BABIP, but not AVG. Although both have a marginal r2 so maybe there is nothing to it.

wRC+

HR-FB!! Big time! IFFB continues to be really bad.

Conclusion

I think what we can take away from this is we want HR-FB, and don't really care that much about anything else (talking to you Josh Reddick). IFFBs are horrible and GBs are pretty crappy as well. If you have your kid swinging down on the ball to get backspin and groundballs, stop it (IFFB have the most backspin, by the way). If you want to hit for AVG, aim for line drives. If you want to SLG, go for the FB and avoid GB. GB hurts HR/FB, the king of batted-ball profile.

All hail HR/FB!!

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