You are here
Home > Analysis > St. Louis Cardinals: The Jhonny Peralta “Injured Thumb” Narrative Needs To Stop

St. Louis Cardinals: The Jhonny Peralta “Injured Thumb” Narrative Needs To Stop

St. Louis Cardinals Jhonny Peralta

While the World Baseball Classic is providing us an early, exciting taste of competitive baseball, the headlines keep flowing out of Spring Training. A few of the earliest St. Louis Cardinals storylines have died down: we’re over Matt Adams weight loss, and even he is apparently over his new stance. Yet, one story that persists is the Jhonny Peralta bounce-back bid.

Every time the camera turns to Jhonny and in seemingly every article that bares his name, we are told that he’s going to be better this season than he was in 2016. Specifically, we are told he was held back by lingering effects from his thumb injury suffered last March and “is in a different place physically than he has been.” It’s easy enough to accept that conclusion, especially since Peralta re-injured the thumb in July after returning.

We keep hearing that this type of injury needs time, and are prompted to remember Yadier Molina‘s struggles after suffering a similar injury back in 2014. Prior to that injury, Molina was slashing .284/.339/.398 worth a 107 wRC+  in 331 plate appearances. After returning, he hit .275/.315/.333 in 111 plate appearances for an 84 wRC+. The next season was more of the same: Yadi would hit only .270/.310/.350 in 2015, worth an 80 wRC+.

The driver behind that decline in production was a sharp drop in batted ball authority. While we don’t have Statcast data for 2014, we can look at Hard% to get an idea of a player’s contact quality. Prior to the injury, Molina was posting a 34.6% Hard%; after returning, that dropped to 18.9%. The dip continued in 2015, as Molina made hard contact at only a 25.3% rate. The dropoff is obvious when looking at the chart below:

Obviously, the injury affected Molina for an extended period of time. The injury occurred in game 83, right before the huge drop to about 10%. In 2015, Molina only had one brief stretch where he made hard contact at a rate above the three year average.

If the thumb injury impacted Peralta in the same way as Molina, we’d expected to see the same patterns when looking at Peralta’s Hard% graph. Yet, we don’t.

Over the past three seasons, Peralta’s Hard% trend has been like clockwork. He starts every year by making contact at an above average rate. He then hits a slump just before the All-Star Break and just after the trade deadline before rebounding down the stretch. Surely, he’s subject to extreme slumps, but they’re relatively short lived. The pattern in 2016 was no different, and Peralta’s graph does not resemble Molina’s at all.

The signs that the thumb injury negatively impacted Peralta in 2016 come from the traditional “baseball card” statistics to measure results (which are subject to luck, random variation, and volatility) and what Peralta himself says (which is impacted by his baseball card stats).

What really matters is contact quality and approach at the plate. If you hit the ball hard consistently, baseball card results will come around. Breaking it down further and comparing Peralta’s batted ball and plate discipline statistics, there was almost literally no difference between his contact quality or approach from 2015 to 2016.

In 2016, he produced an average exit velocity of 87.9 MPH on 221 batted balls. He averaged exactly 87.9 MPH on 83 batted balls prior to re-injuring his thumb in July and he averaged exactly 87.9 MPH on 138 batted balls after returning. In 2015, when “fully healthy,” he averaged 88.7 MPH on 425 batted balls. You could argue that, maybe, his thumb injury caused that 0.8 MPH. Of course, it could also be age or random variation. Whatever the case, a 0.8 MPH difference on average exit velocity only accounts for .006 of the change in wOBA.

Looking at 2016 launch angles, Jhonny Peralta averaged 16.7 degrees before July 18th and 12.8 degrees afterward. For the season, he averaged 14.3 degrees, compared to 13.5 degrees in 2015. Again, not much difference – in fact, the increased launch angle would suggest a .002 increase in wOBA.

In other words, the authority with which Peralta hit balls in 2016 compared to 2015 accounted for none of the variation in his wOBA and other offensive stats, because he hit the ball almost the exact same way.

But the injured thumb had to affect him somehow, right? Maybe it impacted his approach at the plate. Did he start early to compensate for a weaker swing and end up hacking at harder-to-hit pitches? Nope; at least, not according to his plate discipline statistics.

St. Louis Cardinals Jhonny Peralta

Last year, pitchers attacked Jhonny Peralta in the strike zone at the same rate as they did in 2015. Peralta, in turn, showed more patience and made contact at a higher rate. As I illustrated above, the quality of that contact was the same as it was in 2015. So why did his OPS drop by 30 points and his wRC+ fall from 104 to 90?

Well, apparently luck. But the explanation isn’t quite that easy.

I calculated expected hitting stats for Jhonny Peralta in 2016 using batted ball data and plate discipline statistics. For batted balls, I used the exit velocity, launch angle, and an improved estimated horizontal spray angle model to calculate the probability that a given batted ball resulted in a single, double, triple, home run, or out. For untracked batted balls, I used the untracked league average probabilities. I then applied non-pitcher league average rates to estimate intentional walks, HBPs, and sacrifices. For expected strikeouts and walks, I ran a series of regressions to determine which plate discipline variables were significant predictors, and used those to estimate an xK% and xBB%. The result:

St. Louis Cardinals Jhonny Peralta

Jhonny Peralta significantly underperformed the expectations, and the difference in isolated slugging and walk rate are the biggest drivers behind that underperformance. An .824 OPS would have tied for the second best of his career and his best as a St. Louis Cardinal.

I don’t currently have a way to account for speed in my calculations. However, I have found that slower players are more likely to underperform their xStats. Peralta has been a below average baserunner by Base-running Runs (BsR) and Speed Score (Spd) for his career, so that .824 mark is probably a little high. Yet, there’s plenty of room to discount his xwOBA and still have a season that looked much better than he had.

Jhonny Peralta didn’t hit poorly because he was impacted by his thumb. Really, he didn’t hit poorly at all. All that’s required for Peralta to bounce back is better luck. Of course, at age 35, he’ll also have a battle with Father Time. If he produces at the level he did in 2015, he’s a slightly above league average hitter. If he produces near his expected 2016 level, he might be a middle of the order bat.

The fans and those covering the St. Louis Cardinals have all bought in to the Jhonny Peralta injury narrative. That narrative has very limited basis in facts beyond that, yes, Peralta did injure his thumb. The narrative is popular because it’s easy to understand, and because luck and regression are abstract concepts. Perhaps most importantly, it makes fans feel better about the third base situation.

But the batted ball and plate discipline numbers don’t support that story. Those numbers show a hitter who was above average at generating strong contact. They show a patient, professional approach at the plate. We need to stop worrying about the strength of his left thumb and just start hoping that his bad luck from last year evens itself out in 2017.

Similar Articles
Top
Please wait...

Subscribe to our newsletter

Want to be notified when our article is published? Enter your email address and name below to be the first to know.