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Jhonny Peralta’s lackluster return

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Analyzing Peralta’s performance since returning from injury

St. Louis Cardinals v Milwaukee Brewers Photo by Mike McGinnis/Getty Images

It seemed disastrous when Peralta tore a ligament in his thumb early in Spring Training. Most fans weren’t sure that any of Aledmys Diaz, Greg Garcia, or Jedd Gyorko could be a worthy replacement. Neither did the Cardinals, as they signed Ruben Tejada in order to avoid giving time to any of those three. Of course, Aledmys Diaz took the job and ran with it, until he had his own injury.

Things haven’t been easy for Jhonny since returning. On defense he’s playing third-base, and I think that’s a good fit for him going forward. At the plate, he’s struggling:

All four of his core stats are fairly different from where they were in 2015. All except his ISO (Isolated Slugging, calculated as Slugging% minus batting average, in order to isolate for extra base hit ability) are different in a bad way. The result is a fall from a slightly above-average hitter to a solidly below-average one. His walks have shrunk and his strikeouts have increased. Let’s look at his plate discipline stats, courtesy of Pitch F/x stats shown at Fangraphs:

There’s been a change, but it hasn’t been that drastic. He’s decreased his swings out of the zone, but he’s decreased his swings in the zone by more. His contact rate and Zone% (the percentage of pitches he’s seen in the zone) are virtually unchanged. The drop in swings in the zone very well could explain the increased strikeout rate. The fact that his walks have decreased despite swinging at less pitches is odd, so I would bet on the walks increasing going forward, assuming his plate discipline profile continues.

How about Jhonny’s contact quality? He’s had too few balls in play to put too much stock in his BABIP or ISO. Lately, I have been using the Statcast data provided by BaseballSavant.com to better describe a hitter’s contact quality.

As far as balls in play, I looked at each batted ball’s combined Exit Velocity and Launch Angle, and created an average BABIP for each combination of the two. From that, I was able to build a xBABIP calculator based on the newly provided Statcast data. Here’s how Jhonny graded out in 2015 and 2016:

As the linked post above explains, angle-based xBABIP is created by taking the angle of each batted ball, and comparing it to the average BABIP of all statcast-recorded balls at that angle. Velocity-based xBABIP is done the same way, but just considering a player’s velocity. Total xBABIP takes the specific angle/velocity combination, or vector, of each batted ball. Pop-up% is also included, which is defined by Statcast as a batted ball that is hit with an angle of more than 50 degrees. Nearly all Pop-ups are outs. For more info, check out the post linked in the post above.

Peralta’s velocity has been down, but worse for his BABIP is the drop in angle-based BABIP. His pop-ups are up, and his line drives are down, and his expected BABIP is down 43 points. Worse yet, Peralta’s slow speed isn’t currently captured by my xBABIP calculation, so that .273 xBABIP is actually too optimistic. When adjusting for Peralta’s lack of speed, his current BABIP is very similar to what the Statcast averages project.

With worsening plate discipline numbers and ball in play ability, Peralta needs to make up for it with a lot of power. Let’s look at how Jhonny has performed in the stats I formulated for describing home run power:

In case you didn’t read the post linked in the paragraph above this graphic, I’ll give you a rundown of the stats presented here. HRPBB stands for Home Run possible batted balls, which are batted balls with a Launch Angle between 18 and 42, inclusive. The large majority of homers occur on balls in between those angles.

Angle-based takes the average homer per batted ball rate of each HRPBB, to illustrate how well a hitter optimizes the angle of his batted balls towards hitting homers. Velocity is the same, except using velocity of each batted ball. Total takes the specific angle/velocity combination, or vector, into consideration. Actual HR/HRPBB is how the player actually performed. I also track Home-run possible batted balls that are below 90 mph, because those almost never leave the yard.

The good news is that he is hitting for more power than he did last year. The angle-based score and the rate of hitting batted balls into home-run possible angle are both very strong, and help explain the weak Angle-based BABIP score. He’s also hitting a below average amount of HRPBB under 90 mph, though that hasn’t stopped him from being just slightly below average in his velocity-based homer production.

To get a clearer breakdown, let’s check out his angle profile, provided at BaseballSavant.com:

This explains a lot of numbers we’ve went through so far. He has a large chunk of fly balls in between 20 and 30 degrees, which is where a lot of homers happen. He hits a lot of those hard. He has large spikes at 0 and 10 degrees, which are generally good angles for hits, but he has very little in between them.

His velocity is much higher at the home run possible angles, which to me implies his swing is built around hitting for power. Those higher velocities are better represented in terms of percentage of his batted balls. That and the general tightness of his batted balls by angle also implies that he’s squaring the ball up well.

I mentioned earlier that it was good news that Peralta’s expected home run power had increased over last year. The bad news is that it’s not enough to make up for his drops in production every where else. Last week, I took the same data and code that allowed me to calculate BABIP and homers per batted ball for each angle/velocity combination and used it to calculate an xwOBA on-contact stat.

I also built a way to calculate a hitter’s wOBA in plate appearances that didn’t result in contact, as well as a way to combine the two into a xwOBA stat. So, we’re taking his expected overall production on batted balls, as well as his actual production in non-contact situations, and combining the two. Here’s how Peralta has fared in these stats, in both 2015 and 2016:

The contact quality has really has only dropped a minor amount. Last year was better for BABIP, this year has been better for power. Both have resulted in around an average expectation of contact quality. However, when considering the drop-off in non-contact wOBA, Peralta has went from an above average hitter to a below average one.

With weaker non-contact stats, I was hoping to find reason in Peralta's profile to believe his well-below average BABIP was just randomness, and that a better BABIP going forward would raise his overall production. However, it seems that Jhonny's BABIP is right where it should be. His above-average expected homer rate is higher than his actual one, but my calculation also doesn't take into consideration that he's a right-handed hitter who plays his home games at Busch. It might not be prudent then to expect better power going forward. Maybe you can blame it on the thumb, but that probably won't be full strength again until next year.

Peralta’s non-contact wOBA has plummeted 33%, but remember as we saw above, his plate discipline stats aren’t all that different. At just a fourth of a full season played so far for Peralta, his BB and K numbers still are not all that stable. He also didn’t spend much time playing this Spring, and might not have his timing down yet.

With a little regression in non-contact situations, Peralta could be more of an average hitter going forward. However, as we saw last week, Garcia and Gyorko have been no slouches at the plate this year. At the very least, this means Peralta should be getting regular rest to make sure that thumb doesn’t flare back up. A more aggressive decision might mean playing Jedd and Greg over Jhonny regularly. With Diaz out and Garcia at short, this is more of a Gyorko vs. Peralta thing, and I have to say, Gyorko does look like the better choice at the moment.