2015 Pod Projections: Justin Verlander

The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X, and the process continues to evolve and improve.

After winning both the American League MVP and Cy Young awards back in 2011, Justin Verlander followed up strongly the next season, finishing second in the Cy Young voting. But in 2013, his fastball velocity slipped for a third straight year, which drove a decline in his peripherals and resulted in his highest SIERA mark since 2008. It got even worse last season, as his velocity dipped another mile per hour, his strikeout rate fell to its lowest mark since 2006, and he couldn’t strand runners at the rate he used to, while poor defense behind him added more fuel to the fire. All told, his ERA jumped above 4.00 for just the second time of his career.

At age 32 and with a seemingly clear explanation for his recent struggles in the form of the velocity loss, it’s no surprise that fantasy owners aren’t sure what to expect from Verlander this season. On average, he’s just the 46th starting pitcher off the board in NFBC leagues at pick 186, and his pick range sits between 93 and 253. That’s quite the discount for someone with his track record who may have had just one poor season. So let’s get to the projecting.

Pod Projections Index:
Jacob deGrom
Carlos Carrasco
George Springer
Yasmany Tomas
Anthony Rendon

IP: 205

Verlander has been the very definition of workhorse throughout his career, as he averaged about 238 innings from 2009 through 2012. He then threw 20 fewer innings in 2013 and saw his innings count decline again in 2014, to just 206. With question marks surrounding his performance and his age on the wrong side of 30, I decided to play it safe and project a similar innings total to last year.

K%: 20.3%

In 2014, nearly all of Verlander’s pitches generated SwStk% marks below his career average. Given his velocity loss, must assume that provides some, if not all, of the explanation for the lack of swing and miss his stuff was able to produce. I’m projecting a sort of dead cat bounce in each of his strike types, but a projected rebound that still falls short of his glory days. When plugged into my xK% equation, this is what was spit out, which I felt was reasonable.

You have to assume that at some point, his severe velocity downtrend ends. He either regains a bit back or it stabilizes, and given how successful he has been historically, you figure that he begins to learn how to pitch with lesser stuff and his strikeout rate inches back up.

BB%: 7.4%

At least Verlander’s control didn’t take a hit last year as his walk rate sat right around his career mark. Then again if you dive deeper, you learn that he actually threw the lowest rate of strikes since 2008. I’m not sure how he managed to maintain the walk rate he did, but I’m projecting some bounce back in overall strike percentage, which when plugged into my xBB% equation, results in a walk rate just about the same as last year. That suggests that he was probably fortunate to post the walk rate he did, considering he required a jump in strike percentage to land on a projected walk rate that was the same.

GB%/LD%/FB%: 40% / 20% / 40%

Literally his career average. Verlander has been amazingly consistent with his batted ball distribution rates throughout his career. There’s little reason to expect anything different this year.

HR/FB%: 8.5%

Verlander has managed to post a HR/FB rate below the league average every single year of his career. How he does it, we haven’t figured out. But he has, and it’s now been nearly 2,000 innings, so it’s clearly a skill. His career HR/FB rate sits at just 7.8%. I’m projecting a mark a bit higher though because you have to assume softer skills like home run avoidance on fly balls also deteriorate with age.

BABIP: .295

The Tigers were absolutely brutal defensively last year, finishing third to last in UZR, resulting in an aggregate pitching staff BABIP that was second highest in baseball. It was no surprise then that Verlander, who had typically posted below league average BABIP marks, ended up with the second highest BABIP of his career at .317. But, he’s a fly ball pitcher who induces pop-ups, and that’s the type who should be posting better than average BABIP marks.

The good news is that the Tigers are projected to be perfectly neutral defensively this year by our Depth Charts. It was enough to lead to a BABIP projection right at the league average, even if that represents a .20 point drop from his marks in both 2013 and 2014.

Below is my final projected pitching line, along with the other systems for comparison:

System IP W ERA WHIP K K/9 BB/9 HR/9 K% BB% BABIP LOB%
Pod 205.0 13 3.67 1.27 174 7.6 2.8 0.92 20.3% 7.4% 0.295 73.3%
Steamer 204.0 12 4.02 1.27 163 7.2 2.7 1.11 18.9% 7.0% 0.285 71.7%
ZiPS 202.3 14 3.78 1.27 183 8.1 2.7 0.80     0.315 71.5%
Fans (15) 216.0 15 3.72 1.22 186 7.8 2.7 0.83     0.298 71.9%

So given the seemingly difficult task of projecting Verlander, it’s rather shocking that Pod, ZiPS and Fans are generally in agreement about his ERA, while Pod, Steamer and ZiPS are in perfect alignment with his WHIP. Steamer’s lower strikeout rate and higher HR/9 rate is leading to the inflated ERA, despite the same WHIP.

We’re projecting a pretty big range for strikeout rate, which is surprising for an established veteran. But Verlander is obviously a special case. It’s very interesting to see that the two computer systems are the ones at each end of the range. That’s certainly worth exploring as each system must be weighting things differently.

Dan Szymborski and Jared Cross, you are hereby invited to share your thoughts on Verlander’s strikeout rate projection in the comments! Actually upon further inspection, it appears that Steamer’s K/9 is being suppressed by the low BABIP forecast, while ZiPS is being inflated by the .315 BABIP. Without being able to do the math to be sure, I wonder if that’s the entirety of the explanation.

I should also remind you what I included in my 2015 LABR draft recap when discussing my Verlander selection:

At this point last year, Verlander was a month removed from core muscle surgery. He was not only unable to throw, he was just starting to get back into his normal conditioning and weight training regimen.

As he would discover later, the core muscle issues adversely impacted his right shoulder, which in turn forced him to alter his throwing motion which ultimately led to the second-worst season of his career in 2014.

That’s all in the past now. Verlander has put on 20 pounds of muscle and he’s back to his normal throwing regimen…

My projection didn’t account for the possibility that he is healthier and more prepared now than last season. So that provides further upside if the above wasn’t just typical spring training noise. Even if he just improves his strikeout rate a bit, all he really needs is some better batted ball luck, which itself will assist him in stranding more base runners. As my LABR selection suggests, I think he is being criminally undervalued with the potential to be an absolute bargain. There’s not a whole lot of better risk/reward options given his current cost.





Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.

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TheTinDoor
9 years ago

What do you make of his 2013 season? 3.46 ERA/1.31 WHIP (3.28/3.67 FIP/xFIP) with 23.5% k%.

If he bounces back from 2014, does he still have the upside for getting to his pre-2013 production, or is that a good approximation for his ceiling?

For my 13-team mixed league (NFBC-style rosters), his 2015 POD projections put him at a $1 player, and even the Fans is just $3. If he replicates 2013, that’s a $6 pitcher by my valuation.

Does he have strong upside beyond that?

TheTinDoor
9 years ago
Reply to  Mike Podhorzer

3.7 & 1.27 are both significantly below average for the 13-team pool, and the k-rate is a negative contributor too (Z-score method)

TheTinDoor
9 years ago
Reply to  Mike Podhorzer

Now you’ve got me double-checking historical stats to see if my projected pool is too low on average….

ERA of 3.72 would have ranked ~60th last year
WHIP of 1.27 would have ranked ~50th
K% of 20.3% would have ranked 37th

In a 13-team league, project 78 starters taken, that combination is down near the bottom

TheTinDoor
9 years ago
Reply to  Mike Podhorzer

yes, K/9 – should have mentioned that.

Z-score method compares a player to the Average and StDev of the pool (draftable players), not to the replacement player

TheTinDoor
9 years ago
Reply to  Mike Podhorzer

That’s the standard method for calculating any standard (z) score.

As an example, Trout’s projected at 110 runs, average for my player pool is 72, StDev is 12.2. The calculation is (110 – 72)/12.2 = 3.44. Do this for each category, sum, and do a $ per Z calculation.

Half of the pool comes in at negative values, of course, since they’re being compared to the mean instead of replacement. You just have to adjust so the last guy per position is valued at $1.

I like comparing to mean instead of replacement. We know that an outfielder who only scores 60 runs is a net drag on that category, even if 60 runs is better than the undrafted players would produce.

TheTinDoor
9 years ago
Reply to  Mike Podhorzer

Not sure on the math component. The z-score is a common statistical method used to describe individual points in a data set, but how applicable it is to fantasy baseball distributions is another question.

I personally find the average player more intuitive, especially on the low end. I want to know how big of a drain Billy Hamilton’s 5 projected HRs are. I can see the other side too (even those 5 HR’s have some value), but for practical purposes, I think it works well.