With the start of the season rapidly approaching and draft szn officially in full swing, I have decided is as good of a time as any to revive my GPS Location report articles. For those of you who do not remember or may be new to RotoFanatic, the GPS Location reports are a unique breakdown of why a pitcher is or isn’t successful. The article will try to focus on the concepts that underlie all of the data you can find in the Data Monster. For a link to this data click here.
Today I am going to talk about likely one of the most heavily discussed pitchers in all of baseball this offseason, Zach Plesac. The young Indians hurler was excellent in a small 2020 sample, with a 2.28 ERA driven by big improvements in K% and BB% when comparing to his 2019 debut. FIP was a bit more skeptical seeing him as more of a mid-3 ERA type, and my ERA estimator StuffERA agreed pegging him for a 3.62. However, even despite the more tempered expectations, those numbers would signal a huge jump for Plesac. Fantasy managers seem to be buying into the newfound skills, as he has an NFBC ADP of around 80 in the last month good for pitcher 29. However, he is a rare case of a falling ADP as he was actually going much earlier in drafts (around pick 50-60) earlier in the draft season. So what drove the changes for Plesac and are they sustainable?
I find Plesac fascinating because he is a perfect example of why I find location-based research so fascinating as it appears that a large percentage of his success was driven by a big step up in command. When we look at surface stats for a guy like Plesac, we see big improvements in walk and strikeout rates diving this big 2020 breakout. For the K side of things, the jump is fueled by a massive Swinging Strike rate change, 9.5% -> 14%. Often we think of this as a sign of “Stuff” improvement but with Plesac this jump is almost entirely driven by Command improvements.
Looking at the below metrics, you can see that which the In_Whiff did improve slightly, the biggest change for Plesac was the massive improvement in xWhiff. In fact, since 2015, he is one of only 63 pitchers who threw at least 500 pitchers in back-to-back seasons to improve his xWhiff rate by more than 0.015 or (1.5% points). So as we can see, he made nearly unprecedented strides in terms of improving his ability to generate swings and misses. So what exactly drove this change?
One of the main drivers was Plesac’s command of his slider. As you can see from the charts below, he was great at locating his slider in spots that generate high expected whiff rates, especially with two-strikes. Additionally, as you can see most of the swinging strikes he did generate with breaking balls came in these high-value locations.
However, the command improvements he made we not strictly limited to the increase in xWhiff. Plesac improved in terms of expected results across all of the different individual metrics shown in the Data Monster. Overall this led to a massive improvement in his rfCommand. In 2019, he had a below-average rfCommand of -1.17, he was able to post a significantly better number in 2020 coming in at 2.57. Once again, within my sample that is a historic jump. Once again only 64 pitchers with consecutive seasons of 500 or more pitches made that kind of a jump. This then leads me to the final question related to this kind of historic success, is it sustainable?
The major question with any kind of command-related change is what exactly happens the year after such a jump. Unfortunately, due to the unprecedented nature of an improvement as significant as Plesac’s we only have 27 pitchers who made improved their xWhiff rate by over 1.5% points and continued to throw 500 pitches in the season after.
On average, these 27 pitchers saw a decline of 0.003 in their xWhiff rate compared to their middle season. So after making these large improvements, on average pitchers did fall back towards their pre-breakout results however, the regression was small. Dropping Plesac to an xWhiff of 0.125 would still find him near the 90th percentile by this metric in 2020. This should still allow him to remain immensely successful and will help to keep his strikeout rates similar to what he showed in 2020.
Similarly, only 29, pitchers who improved their rfCommand by 3 or more points went on to throw another 500 pitches in the following season. For these guys, regression was a bit more significant, with their rfCommand dropping by about 1 point off the high of the breakout season. For Plesac this would still allow him to be above average in terms of rfCommand but would take him from having 80th percentile command to the 70th percentile range. Across the board, this expected regression should pull back a bit of his overall success but should still leave him well above average across the board.
As for 2021, I am buying in on Plesac maintaining a large percentage of his gains and continuing to remain well above average as a pitcher. For fantasy purposes, he may be more of a 3.70 ERA type of pitcher with K-rates at or near a strikeout per inning and above-average walk rates. This should help him to keep his WHIP low and mitigate the damage when he does allow home runs. Overall, I think Plesac is going to be a great investment for managers who decide to draft him but expectations should definitely be tempered a bit as he is not going to take the same leap that a guy like Shane Beiber did. Overall, Zach Plesac is a fascinating study of the impact of command for a young pitcher and how it helped to elevate what may appear on the surface to be average “stuff”.