This article is part of our The Z Files series.
One of my in-season duties for the site is generating weekly pitching rankings. The process is transparent, having been detailed in the space over the years. In brief, the starting point is the season-long expectation for the pitcher. This is then adjusted for park and opponent and ranked with all the other expectations.
Each offseason, the process is reviewed. Is the projection properly adjusted by quality of opponent? Do the rankings accurately reflect how the weekly expectation will affect end-of-season numbers? Are changes in the pitcher's skill set adequately captured by the rest-of-season algorithm?
The third of the above will be the focus of today's discussion. As outlined in this space, I have developed a formulaic means of altering my initial projection, concentrating on skills rather than outcomes often out of the pitcher's control. A pitcher owns his in-season skills at different rates. Each of these are regressed to initial expectations based on how rapidly they become real. It usually takes five or six starts to really move the needle.
I trust the system; it's served me well over the years. That said, in today's offensive environment, streaming pitching is more integral than ever. In addition, there's more information available, with smart individuals helping to decipher the data. As such, I decided to be more liberal this season when it comes to overriding or perhaps accelerating changes to the rest-of-season expectation. However, I made myself promise to wait three starts, and manually adjust solely in the event of something tangible
One of my in-season duties for the site is generating weekly pitching rankings. The process is transparent, having been detailed in the space over the years. In brief, the starting point is the season-long expectation for the pitcher. This is then adjusted for park and opponent and ranked with all the other expectations.
Each offseason, the process is reviewed. Is the projection properly adjusted by quality of opponent? Do the rankings accurately reflect how the weekly expectation will affect end-of-season numbers? Are changes in the pitcher's skill set adequately captured by the rest-of-season algorithm?
The third of the above will be the focus of today's discussion. As outlined in this space, I have developed a formulaic means of altering my initial projection, concentrating on skills rather than outcomes often out of the pitcher's control. A pitcher owns his in-season skills at different rates. Each of these are regressed to initial expectations based on how rapidly they become real. It usually takes five or six starts to really move the needle.
I trust the system; it's served me well over the years. That said, in today's offensive environment, streaming pitching is more integral than ever. In addition, there's more information available, with smart individuals helping to decipher the data. As such, I decided to be more liberal this season when it comes to overriding or perhaps accelerating changes to the rest-of-season expectation. However, I made myself promise to wait three starts, and manually adjust solely in the event of something tangible that's not recognized by the Excel coding.
Several pitchers have started the requisite three outings, so it's time to put some overachievers under the microscope. Here's the initial list of pitchers I'm considering tweaking for next week's pitching rankings update.
Luis Castillo, Cincinnati Reds
If I only had a bitcoin for every fantasy pundit using "one year too early" when discussing Castillo. Obviously, Castillo's .135 BABIP and 85.7 percent LOB are due a visit from the regression monster. However, a 57 percent groundball mark is encouraging in today's homer-infested climate, especially since Castillo posted a 46 percent level last year. The question is where he'll land? Castillo is missing more bats than in 2018, despite similar velocity and pitch mix. His SwStr is 16.7 percent, well above the 12.6 and 13.5 marks he recorded his first two campaigns.
Last season, Castillo logged a 23 percent K-rate, down from 27 percent his rookie year. So far, he's spun a 35 percent rate. He won't maintain the current level, but since strikeout rate is one of the fastest skills to change, I'm leaning to accelerating the process, leaving the rest as is. Increasing strikeouts give Castillo a noteworthy boost, since my research has demonstrated punchouts are the most important element of the weekly ranking. Additionally, with a higher K-rate contributing to his ERA estimators (and hence win potential), Castillo will also incur a slight bump in the ratios and win probability. I'm not yet ready to lower his expected ratios more than is affected by more whiffs, but he'll certainly be tracked.
Carlos Rodon, Chicago White Sox
To frame my initial expectations, here's how I ended his site outlook:
The early market is expressing optimism, assuming not only will Rodon avoid injury, but that he'll return to previous strikeout levels while honing his spotty control. That's a risky bet.
"That's a risky bet" was a soft way of saying, "You're a fool if you draft Rodon," as I didn't think that would make it by the editors. Who's the fool now?
In an albeit modest 16 innings, Rodon has fanned an eye-popping 24 batters, though he has issued a generous seven free passes. Still, whiffing three every two innings is impressive. That said, while a 14 percent SwStr is high, it doesn't portend a 33 percent K-rate. Further, Rodon's velocity is down. Maybe I'm not such a fool after all, as I'm going to let the algorithm handle Rodon organically. His strikeout rate should enjoy an uptick, but it will be based on his SwStr, not the bloated K-rate.
Marcus Stroman, Toronto Blue Jays
From a fantasy perspective, I've never been a Stroman fan. For his career, he's sported expected ERAs a tick below 4.00, which is useful. However, he's not especially dominant and doesn't work in the ideal division for streaming. Rogers Centre isn't terrible for runs, but still, the AL East isn't where I want to grab spot starters.
This season, Stroman has fanned 18 in his first 18.1 frames. While he isn't threatening the dominant range, he's edged out of pedestrian. His 11.2 percent SwStr would be a career best (yeah, I know, small sample). Stroman's velocity is unchanged, though his pitch mix is much different. Assuming it's not a classification issue, Stroman has ditched his curve and is throwing fewer sinkers while using his fastball and slider more. Sometimes this is intentional, other times it's game plan. While I'm cautiously optimistic, I see nothing to override the rest-of-season formula. If the added whiffs are real, they'll be accounted for soon enough. Unfortunately, Stroman will still face the same streaming woes.
Matt Shoemaker, Toronto Blue Jays
Shoemaker faces the same divisional foes as Stroman, so any enthusiasm is tempered. However, there are a couple of encouraging signs. Ignoring the luck-driven 0.92 ERA, Shoemaker has thrown seven stanzas in two of his three outings. Granted, it was against the Tigers and Orioles, but still, it's not like everyone is regularly tossing seven frames these days.
As is likely obvious by now, strikeout rate is the primary metric investigated. Coming into the season, the change in park from Angels Stadium (104 for strikeouts) to Rogers Centre (97) portended reduced whiffs. So far, Shoemaker's 27 percent K-rate is supported by a career-best 14.3 percent SwStr. Shoemaker's velocity is down a tick, but it's early and most pitchers gain as the season progresses. It will be with caution, but there's a good chance Shoemaker's initial projection will be massaged to soften the "on paper" drop in strikeouts.
Jordan Zimmermann, Detroit Tigers
At the First Pitch Arizona Forum last November, The Athletics' Eno Sarris presented a new command metric where Zimmermann graded favorably. Using the strict definition, command is the ability to throw the ball where you want it while control measures strikes. They're often juxtaposed. Anyway, after Eno identified Zimmermann as someone who can throw the ball where he wants it, I suggested he reconsider where that is. Jokes aside, I've been tracking Zimmermann, because unlike AL East hurlers, those toiling in the offensively-challenged AL Central will have multiple favorable matchups.
Unfortunately, despite a low 2.50 ERA, Zimmermann really hasn't changed. There's no discernible difference with his velocity or pitch mix. I'm still following Zimmermann, especially in terms of home runs allowed. If it appears he's doing a better job keeping the ball in the yard (too early to tell), his expected HR/9 will be lowered which will improve his ranking, especially against some of the punchless lineups in the AL Central.
Matthew Boyd, Detroit Tigers
Boyd has teased, then ultimately disappointed fantasy enthusiasts for the past couple of seasons. There are signs he may flip the switch for those not holding a grudge. Through three outings, he's punched out a whopping 29 in 17.1 frames. Quality of opponent had something to do with it (Blue Jays, Yankees, Indians), but again, if it were that easy, everyone would be doing it.
It's subtle, but Boyd is working a little higher in the zone, thus far inducing more swings and misses along with weak contact. I've been down this rabbit home before, but I'm leaning towards improving Boyd's initial expectation. Part of it is because he's been unlucky, sporting a high .476 BABIP and low 64.3 percent LOB.
While it may be disappointing, I'm not changing many original outlooks. Keep in mind, the sample of starters with three outings under their belt is small. Plus, if multiple drastic changes were needed, doesn't that reflect worse upon my initial projections than upon my willingness to make adjustments?
