Written by: Justin Choi (@justinochoi)
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Before reading this article, head on to FanGraphs and take a look at Pedro Baez’s numbers. What do you see?
Maybe you see a reliever who’s been consistently reliable for the Dodgers since 2015, his first full season. Among all relievers who’ve thrown a minimum of 250 innings since that year, Baez’s ERA of 3.06 ranks 25th of 61. When your competition consists of elite closers like Craig Kimbrel and Kenley Jansen, that’s pretty impressive. And in 2019, Baez had his best season yet, maintaining a 3.52 FIP throughout 69.2 innings en route to 1.3 fWAR.
But maybe you see a reliever who’s walking a tightrope, dangerously outperforming his peripherals. By FIP (3.55), Baez is now 34th on the same leaderboard. That’s not a huge downgrade, but we are heading into just ‘okay pitcher’ territory.
How about xFIP (4.10)? At this point, Baez looks terrible – he’s now 52nd, two spots behind the ever-wild Fernando Rodney. Of course, assessing a pitcher’s value through xFIP is misleading, as the metric includes expected outcomes, not actual ones. But such a high xFIP is a sign of something worse: regression.
Baez had a great 2019, but his xFIP of 4.82 is an eyesore. A pitcher’s xFIP being higher than his FIP is common, but by more than one? My hunch was that it’s rare, so I calculated the xFIP-FIP differential of relievers who pitched at least 50 innings in 2019:
Of the 149 pitchers on my Excel sheet, only 7 had a differential greater than one… and Pedro Baez is 3rd. Ouch. That’s what happens when a fly ball pitcher has a HR/FB rate of just 7.2%. Here’s the thing, though. This actually isn’t a problem for Baez – because his home run rate suppression is a result of skill, not luck.
Let me elaborate.
xFIP, or expected fielding independent pitching, is built upon the premise that pitchers have more control over how many fly balls they allow – way more than home runs. So an expected home run total is derived by multiplying a pitcher’s fly balls by the league HR/FB rate, and this replaces the regular home run component of FIP.
After years of collecting data, we concluded that xFIP is a more reliable predictor of a pitcher’s future ERA than FIP or just ERA is. It’s not perfect, but it gets the job done.
A flaw with xFIP, however, is that not all fly balls are created equal. Given the same exit velocity, a ball hit 30 degrees has a much higher chance of becoming a home run than one hit 40 degrees. SIERA makes up for this by taking a pitcher’s batted ball data into consideration, but explaining its intricacies would take many, many words.
We can simplify the process by analyzing Pedro Baez, the man who defies xFIP.
First, here’s a different leaderboard, one that ranks the average launch angles of fly balls allowed by pitchers last year with min. 50 BBE. Again, I’ll only be showing the Top 5:
This time, Baez being on the top of a leaderboard is a very good thing. We tend to associate hard hit balls with an increase in xwOBA and thus more expected home runs allowed, but data on Baseball Savant shows that suppressing launch angle is almost as important:
On the Launch Angle-xwOBA scatterplot, Baez is actually beneath the line of best fit. This is because his average exit velocity on fly balls, 90.6 mph, is also superb. It’s why Madison Bumgarner and Jeff Samardzija (92.6 and 92.5 mph, respectively) are victims of allowing too many fly balls while Pedro Baez can remain relatively unscathed.
To get a better understanding of the extent to which Baez suppresses his launch angles, I graphed the distribution of his fly balls, eliminating any ambiguity caused by looking at average launch angle:
Admittedly, Baez is allowing a good amount of fly balls in the dangerous 24 to 35 degree range; his median launch angle is 37.4 as a result, 1.7 degrees lower than the mean. That might mean more home runs next year. But consider this. 45.3% of Baez’s fly balls have a launch angle greater than or equal to 39 degrees. And from 2015 to 2018, balls meeting that criterion turned into home runs less than 1% of the time! The remaining 99%? A whole lot of outs mixed in with a couple of bloop singles.
That means when Pedro Baez allows a fly ball, it’s a guaranteed out nearly half the time. Remember, this is without even taking exit velocity into account, which is damn impressive. Only one of his home runs last year had a launch angle greater than 39 degrees, and of course it was hit by Ji-Man Choi:
So how is Baez such a fly ball genius? Let’s examine his repertoire, which consists of three pitches: a four-seam fastball, changeup, and slider. The changeup and slider are your run-of-the-mill, reliever offspeed offerings, but within the fastball lies the answer to our question. I want you to look at where Baez locates his fastballs. Notice anything strange?
Yeah, those aren’t regular high fastballs. It’s almost like they belong to a different strike zone! What’s interesting is that Baez didn’t always throw this high up. In 2015, the location chart of his fastball resembled that of any other pitcher. But over the years he’s been throwing higher and higher and higher, finally reaching the stratosphere it seems:
In an article, Alex Chamberlain of FanGraphs discovered a strong correlation (r-squared = 0.96) between the vertical location of fastballs and the average launch angle at which they were hit. The relationship isn’t perfectly linear, however, as there are fluctuations in the observed launch angles. Still, this is significant, as we know that certain launch angles allow a higher/lower wOBA on contact. As Chamberlain elaborates: “it is an opportunity, not a certainty – a game of probability that a pitcher plays to incur a specific launch angle.”
Pedro Baez, therefore, must have realized what kind game he was playing as he gained experience pitching in the Major Leagues. He observed that hitters were more likely to mishit when he threw his fastballs up and decided to, well, do that more often. This, combined with an elite SwStr% of 18.5% on his fastballs last year, made Baez a force to be reckoned with.
This article so far has been full of Pedro-praise, but there is one red flag to be wary of: a career-low BABIP of .213 last year. Regression of BABIP towards the mean is now a sabermetric cliche, and doesn’t apply to every hitter/pitcher, but one that’s this low is a legitimate point of concern. It will bounce back up and result in Baez allowing more runs; that’s a given. The question is: by how much?
Here’s a theory I have. Because of the lifeless contact Baez induces with his sky-high fastballs, the regression towards the mean this year might not be as strong. Most projection systems expect him to have a BABIP north of .280, but I have a sneaky suspicion that it will hover around .250 instead.
Speaking of projection systems, they also expect a low-4 ERA! That seems way too harsh. The only projection I can agree on is the 3.75 ERA provided by ATC, and even that’s erring on the conservative side.
As I am not a complex algorithm, I’m incapable of spitting out an exact ERA with confidence. But based on the research presented thus far, I can say this – if Baez continues his approach, the inevitable regression will not be that severe. There’s a good chance that he continues to be a solid contributor to the Dodgers, a fact deserving of your interest. Or, you know, he could allow home run after home run, but we’re near Opening Day and high hopes are more than welcome. It’s going to be a strange season filled with strange happenings. What better time to bet on the unique skills of Pedro Baez?
Follow P365 KBO and MLB Analyst Justin Choi on Twitter! @justinochoi
Follow us on Twitter! @Prospects365
All statistics are from Baseball Savant and FanGraphs
Featured image courtesy of photographer Gary A. Vasquez of USA Today Sports