How Rick Porcello Can Take a Big Step Forward

Rick Porcello is one of those guys whose ERA estimators (xFIP, SIERA) are always lower than his actual ERA. Prior to 2013, no one really cared because his estimators were basically 4.00 or higher. But last year his estimators fell dramatically; his xFIP was 3.19 and his SIERA was 3.39 while his ERA was 4.32. This presents a couple of questions. First, what caused the drop in xFIP/SIERA? Is it sustainable? If so, is it possible his ERA follows the same downward trend that his estimators did?

The first question, what caused the drop in his xFIP/SIERA, is pretty easy to answer. SIERA is primarily calculated with strikeout rate, walk rate and ground ball rate. xFIP is primarily calculated with the three true outcomes, strikeouts, walks and home runs. Porcello’s walk rate and ground ball rate have been consistently above average. In the last four years the league average walk rate ranged from 7.4% to 8%, and Porcello’s walk rate in that span was 5.7%. The league average ground ball rate ranged from 44.4% to 45.1%, and Porcello’s ground ball rate was 52.5%. It was his paltry strikeout rate that was holding his estimators back. From 2010-2012, the league average strikeout rate ranged from 17.6% to 18.7%, and Porcello’s strikeout rate was only 13%. But Porcello’s strikeout rate spiked up to 19.3% last year, and his ground ball and walk rates remained above average.

So is his improved strikeout rate, and by extension are his ERA estimators, sustainable? If so, I would expect to see something like a change in his pitch mix or a spike in velocity. And I’d also like to see his strikeout rate improve, or at least remain above average, later in the year.

As it turns out, two out of three ain’t bad. His fastball velocity was very close to his career average and was down a bit from 2012. But he changed up his pitch mix and didn’t see his strikeout rate decline as the year wore on.

The pitch Porcello uses most frequently is his sinker. That’s obviously a big part of why his ground ball rate has always been above average. But the sinker isn’t usually a big swing and miss pitch, and that was true for Porcello as his sinker generated the fewest whiffs per swing of any of his pitches from 2010-2013. So it’s no surprise that he had his best strikeout rate last year when his sinker percentage dropped 12% from the year before and was the lowest sinker percentage of his career.

About half of that 12% drop went to his four seamer, and the other half went to his breaking pitches (he throws both a slider and a curve) and his changeup. To put it in terms of raw numbers, he threw 317 fewer sinkers and 159 more breaking and offspeed pitches. This is huge for his strikeout rate because his whiff per swing rate on breaking/offspeed pitches was more than double his whiff per swing rate on sinkers. If I’m doing my math right, this shift in pitch mix helped Porcello generate over 30 more whiffs than he had in 2012 while throwing roughly the same number of pitches. It’s also nice to see that Porcello was able to maintain his excellent ground ball rate despite throwing fewer sinkers.

As mentioned, Porcello was able to maintain the increased strikeout rate through the end of the year. He had a 26% K% in two months of the year, and one of those months was September. And aside from the first month of the season, he didn’t have a monthly K% lower than 15.5%. As long as he keeps using his ‘other’ stuff and the sinker less, Porcello should be able to maintain his now league average strikeout rate.

All of that is good and well, but it doesn’t mean a whole lot if all it means is that his xFIP and SIERA will remain low while his ERA continues to hover around 4.00. In order to figure out whether his ERA can get in line with his estimators, we should talk about what typically causes guys like Porcello to perennially have an ERA that’s higher than their estimators. From what I’ve gleaned over the years, these are the most common reasons for a habitually ugly ERA-estimator differential:

  • They get hit too hard. Generating weak contact is a skill, and some guys just don’t have it. Signs of this well be a high line drive rate, high ISO allowed and high BABIP.
  • They struggle from the stretch. This one is fairly easy to spot. You can usually see if this is an issue by looking at a guy’s strikeout and walk rates with and without men on base. A high strand rate is also a sign of stretch struggles.
  • Bad defense. We’ll get into it a bit more, but Miguel Cabrera moving off third base has to be a good thing.

Generating weak contact has been an issue for Porcello. His career BABIP is .312, while the league average BABIP for starters since 2009 is about .295. His career line drive rate is pretty close to league average, but he’s been giving up line drives at higher rate the last two years. But his 21.1% LD% last year was acceptable.

The most encouraging number is his ISO allowed. He’s been above league average among qualified starters in each of the last two years, and he was 27th among starters in ISO allowed last year (.125). But the best part is that his ISO allowed against right-handers was much, much better in the later months last year. After a rough April where he had a .244 ISO allowed to right-handed hitters and an average May (.134), Porcello really limited the damage by righties in the last four months. His ISO allowed to righties was never higher than .086 from June on, and his average monthly ISO allowed to righties during that span was .061. Just to give you a little context, the best ISO allowed for any qualified starter last year was .073.

Admittedly, the damage he allowed early in the year counts, and it’s only fair to point out that despite making similar improvements against lefties in the middle months of the year, he got lit up by them in September. But there’s some significant evidence that Porcello is making improvements in limiting hard contact.

The stretch is also something with which Porcello has struggled. For his career, he has a 10.8% K%-BB% with the bases empty (from the windup) and a 4.4% K%-BB% with men on base (from the stretch). I like to look at strikeout and walk rates for this split because it’s something very much within the pitcher’s control and can be an indicator of mechanical issues from the stretch. The good news is that Porcello’s K%-BB% has been steadily improving each year both from the stretch and the windup.

porcello stretch

We’ve seen that there is at least some evidence that Porcello could induce more weak contact and pitch better from the stretch, but there is even more evidence that he’s going to benefit from an improved infield defense. Below is a chart showing the runs above or below average (DEF) for the Tigers who played the most at each infield spot last year and the Oliver projected DEF for the Tigers most likely to play the most innings at each infield spot this year. There should be improved defense at every spot on the infield.

tigers infield

Now it’s time to summarize and tell you what to watch for next year.

Porcello’s ERA estimators improved so much because his strikeout rate improved significantly. He got it up to league average without seeing his above average walk and ground ball rates decline at all. And he struck out more batters because he stopped throwing the pitch that he got the lowest percentage of whiffs on so much (his sinker). Instead he started throwing his high whiff rate pitches a lot more (slider, curve, change). Is the improved strikeout rate sustainable? Presumably, as long as he sticks with the new pitch mix.

His ERA will only get down to his estimators if he he induces more weak contact, improves from the stretch and gets better defense. The defense he’ll get, but how do you know if he’s getting more weak contact and pitching better from the stretch? For the weak contact, check brooksbaseball.net. On Porcello’s played card, you can track his ISO allowed from the ‘usage and outcomes’ tab. You can also track his pitch mix there. Here on Fangraphs, the splits tab is the best way to keep track of Porcello’s numbers from the windup (bases empty) and from the stretch (men on base).

To put a fantasy slant coda on this, I’ve always been a sucker for drafting these pitchers with low ERA estimators. I loved Ricky Nolasco for years but had long since given up by the time he got it together last year. For the last three years I expected Zack Greinke to bounce back to his sub-3.00 ERA ways. Joe Blanton and Justin Masterson have caught my eye before. So I just want to fully disclose that I have a bias towards these guys.

But I do genuinely think Porcello is primed to take a step forward. Maintaining this more successful pitch mix is something that is completely within his control. The defense is assuredly going to be better. Those factors alone should help push his ERA below 4.00 even if not all the way down to where his estimators might be. But there’s also evidence that he can induce more weak contact and continue to make gains from the stretch. If that happens, he could potentially be a huge value.

My guess is that he’ll be drafted just inside the top 70 starters, but I think he’s a borderline top 50 starter. Last year Jhoulys Chacin had this roto line: 3.47 ERA, 1.26 WHIP, 126 K, 14 W. That was good for the 55th best starter on ESPN’s player rater. That line seems like something close to what I project for Porcello with the ERA being a little higher and with 20 or so more strikeouts. He’ll be a good flyer later in drafts, and you’ll take him late enough that it won’t hurt to cut him if I turn out to be wrong.

Big thanks to BrooksBaseball.net for a lot of the data.

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You can find more of Brett's work on TheFantasyFix.com or follow him on Twitter @TheRealTAL.

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gump
Guest
gump

> SIERA is primarily calculated with strikeout rate, walk rate and ground ball rate. xFIP is primarily calculated with the three true outcomes, strikeouts, walks and home runs.

Err, no? Your SIERA def is actually xFIP, and your xFIP def is actually FIP… SIERA *i guess* could be said to only have K rate, BB rate, and GBs but it’s a bit more complicated than xFIP in that regard.

Detroit Michael
Guest
Detroit Michael

xFIP, unlike FIP, is based on flyballs on contact, not actual number of homers.