Why There's Reason to Be Skeptical About Yoan Moncada

Is Yoan Moncada actually good? 

What a loaded question. On the surface, the former No. 1 overall prospect finally broke out in a big way last year at the age of 24. He slashed .315/.367/.548 with 25 home runs and a 141 wRC+ over 559 plate appearances. He was worth 5.7 WAR, making him the league's 16th-most valuable position player. There's no doubt about it -- Yoan Moncada had a good year. 

But is he actually good? There's certainly a distinction here. Over the offseason, I've seen some try to make the argument that he's better than Kris Bryant. And I've seen others try to put him in a similar class as Mike Trout, Cody Bellinger, and Francisco Lindor. Yes, Moncada's 2019 gave him that much helium, though perhaps that's really only been among White Sox fans. ​And while I'm all for defending your favorite team, I'm not sold on Moncada specifically.

​The short explanation is BABIP. Moncada's .406 mark in 2019 was the highest single-season BABIP since Rod Carew's .408 in 1977. That should scream "He got really lucky!" to you. Because Moncada, indeed, got really lucky. 

But how lucky? That's a more difficult question, especially because Moncada was a high BABIP guy to begin with. Over his first 901 plate appearances in the majors, from 2016 through 2018, Moncada's .343 BABIP put him in the top eight percent of players in the league. That indicates that Moncada is the type of player who can sustain a BABIP well above the league-average, which hovers around .300 every year. 

The argument that Moncada can sustain a higher BABIP than most has legs, but I caution those in using this as the sole reason why we can expect him to hit just as well in the future. That's why it's important to understand where Moncada's .400 BABIP came from and use that to develop a realistic expectation for upcoming performance. Baseball analysis is never as simple as one number. 

Normally, when a player breaks out, most analysts can point to two numbers as the jumping-off point (no pun intended): launch angle and groundball rate. Players who increase their average launch angle, decreasing their groundball rate in the process, tend to do well. Moncada, though, decreased his launch angle and increased his groundball rate, both indicators of regression, not improvement. Moncada's average launch angle fell from 15.1 degrees in 2018 to 12.0 in 2019, and his groundball rate increased from 37% to 42%. That's not what you want. 

But Moncada was the one case where that didn't matter. Almost inexplicably, he hit .382/.382/.421 on groundballs last year, good for a 118 wRC+. That wRC+ was nearly 100 points better than the league's (26). Moncada was the only player in baseball to post a 100 wRC+ on grounders. 

Spoiler: that's not sustainable. While some may argue that his high exit velocity on groundballs could've been the reason for that success, there's almost no correlation between average groundball exit velocity and groundball results. The purple dot is Moncada:

So the argument that because Moncada hits the ball hard, leading to sustainable success, probably isn't a good one. Hitting the ball hard overall is good, but hitting the ball hard on the ground doesn't make a huge difference. Major league infielders are good at defense. 

​Others may make the argument that Moncada's speed does create a sustainable BABIP. I do concede that it is true that speed influences BABIP, but perhaps by not as much as you might think. Here's a plot of players with at least 300 plate appearances in 2019, evaluating the relationship between sprint speed and BABIP:

There's a relationship, but it's not strong.

​Of course, it is also important to consider where Moncada fits into this. While he may have the perception of being fast, his 27.8 feet per second sprint speed only put him in the 66th percentile among players with at least 10 opportunities. Moncada may be faster than I'll ever be, but he's certainly no burner by major league standards. 

​Lastly, while I glossed over launch angle earlier in this article, it's important to understand where exactly Moncada's batted balls are coming from. Average launch angle is one metric to evaluate, but a distribution is better. Why? Think about it this way: If a player put two batted balls into play, one at 60 degrees and one at 0 degrees, his average launch angle is 30 degrees. That is not an average that is representative of the data, though of course, it does even out with larger batted ball samples. Even still, there can be bimodal distributions or skewed distributions all the like. I wrote a little bit about this over at FanGraphs when discussing Vladimir Guerrero Jr., and I think a deeper dive into Moncada's batted ball distribution will be helpful as well. 

First, let's think about successful outcomes as a function of launch angle:

Batted balls between 0 and 30 degrees are pretty clearly the sweet spot, though more context is always helpful. 

The MLB-average wOBA in 2019 was .320. A hitter can be expected to produce at least the MLB-average wOBA when putting the ball in play between -2 and 36 degrees. (There are some exceptions here, like below -75 degrees, but that mostly comes in the form of bunt singles.) Moncada was in that range on 58% of his batted balls last season, which, again, means nothing to you without more context. That's pretty significantly above league-average (52%) and only a touch below Mike Trout (60%). In fact, among the 281 players with at least 100 batted balls, Moncada's decent-launch-angle rate put him in the 89th percentile. 

That certainly works in Moncada's favor, but working against his sustainability is the production he had outside of that range. Going back to my earlier point about his success on groundballs, Moncada posted a .232 wOBA on batted balls hits with a launch angle of -2 degrees or below, the fifth-highest mark in baseball. And though one could attempt to make the argument that he hit the ball harder or got out of the box faster than his peers, leading to this success, I don't think that holds up. 

Moncada also benefitted from potential good luck on batted balls hit above 36 degrees. His .124 wOBA on those events ranked 39th out of 175 hitters with 300 batted ball events, and his 24-point difference between his wOBA and xwOBA on those outcomes ranked 49th.

Moncada got lucky everywhere, and he somehow managed to avoid intra-season regression, which led to his inflated perception during the offseason. When the luck inevitably runs out, I worry about how far his production may fall.

It's always fun to bring in Mike Trout as the gold standard, so let's use him as a case study for Moncada. Trout, who maintained a .358 BABIP from 2012 through 2018, saw some of the worst batted ball luck of his career last year, putting up a .298 mark. But he managed to post a 180 wRC+ if only due to his outstanding plate discipline and increase in power. As a player, you're isolated from batted ball luck if you're constantly putting the ball over the fence, and Trout homered 45 times last season despite only registering 600 plate appearances. He also walked 18% of the time and struck out just 20%. Ultimately, while his .291 batting average seemed uncharacteristic, he set a career-high in slugging and actually posted an OBP above his career-average to that point.

Moncada would need to overhaul his 2019 game in order to see similar results. Unlike Trout, who gets on base nearly one-in-five times without having to swing the bat, Moncada is extremely dependent on batted ball luck because he puts the ball in play quite often. He walked in just 7% of plate appearances last year, striking out in nearly 28%. While putting the ball in play often can work as a successful strategy for offensive production (Yuli Gurriel is a great example), it won't work if you're striking out as often as Moncada. 

To demonstrate this, I exported each player-season of at least 300 plate appearances since 2010. There was a correlation between BABIP and wOBA, with an r-squared of .26. But for the 31 players who I deemed similar to Moncada -- a walk rate between 6.2% and 8.2% and a strikeout-plus-walk-rate between 34.7% and 36.7% -- that r-squared jumped to .40. Players like Moncada are 54% more dependent on batted ball luck than the population on total production, precisely because of a poor walk-to-strikeout ratio.

When you take all of this into account, it's easy to see why I'm not convinced about Moncada going forward. He had a great season in 2019. But is he a great player? The jury is still out.