2017 Pod Projections: Kyle Hendricks
The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X 2.0, and the process continues to evolve and improve.
Who was the most surprising starting pitcher in fantasy baseball last year? The answer might just be Kyle Hendricks. We ranked him 54th among starters heading into the season and he ended up earning $29.10, fourth most among starters at the end of the year. Oh, and he finished third in the Cy Young award voting. He also posted a suppressed .250 BABIP, a LOB% above 80%, and outperformed his SIERA by the widest margin among all qualified starters. So obviously, the knee-jerk reaction would be to figure some severe regression this season. Right? Let’s find out.
IP: 188 (31 games started)
Nothing crazy here. I generally refuse to project a pitcher to reach the 200 innings pitched plateau if he has never done it before. Sure, it’s an arbitrary marker, but stamina is a skill and until I see proof of a pitcher’s ability to pitch deep into games all season long, I cannot forecast it will suddenly happen. Hendricks averaged nearly 6.3 innings per start last year, just 5.6 in 2015, and 6.2 in 2014. Naturally, those IP/GS figures ebb and flow with his ERA. I’m projecting a marginal decline to almost 6.1 IP/GS this season, because…spoiler alert — I kinda think his ERA is going to rise, which will knock him out of games a tad earlier.
K%: 21.8%
Surprise! Even with a fastball that averages just about 88 mph, he has actually posted slightly above average strikeout rates these past two years. He’s not your typical soft-tosser solely getting by thanks to elite defensive support. He generates a ton of called strikes and gets enough swinging strikes to remind us that it’s not all about command, but the quality of his stuff is quite respectable as well. That changeup, MAN, that changeup! A 23.5% SwStk% last season and 22.5% for his career. But, that’s literally his only whiff-inducing pitch. Because of his reliance on that one pitch and the real possibility its effectiveness drops off, I’m forecasting a small regression in strikeout rate.
BB%: 6.3%
Hendricks has been extremely consistent with his strike-throwing game, throwing them at an above average clip each year. However, while he has outperformed his xBB% for three straight seasons, his xBB% mark climbed at a faster pace than his actual walk rate did this past season. Outperformance could continue as xBB% isn’t perfect, but the gap cannot keep widening, so something’s gotta give. Starting from a low baseline, the right play here is to assume a slight uptick in walk rate.
GB%/LD%/FB%: 49% / 20.5% / 30.5%
Like many pitchers, Hendricks’ batted ball distribution has been quite stable, so this is essentially his career average. If he threw his sinker more at the expense of his changeup, his ground ball rate would likely rise, but his overall effectiveness would probably decline, perhaps dramatically. He probably has little upside in that GB%.
HR/FB%: 10.5%
Wrigley Field boosts home runs by a small degree, but that Hendricks hasn’t noticed, as he has actually posted a better HR/FB rate at home than in away parks, both of which are better than the league average. HR/FB rates are always difficult to project, as most do regress toward the league average after accounting for home park, but there are some who do seem to have an innate ability to suppress the long ball. I don’t know if Hendricks does, so I’m giving him partial credit by projecting a below league average mark, but still above his current career mark of 9.5%.
BABIP: .280
If you’ve read my stuff over the years, you should be well aware of my disdain for analysis that includes the terms “weak contact” and “hittable”. Rarely, if ever, are any of these terms actually supported with any data other than HR/FB rate and BABIP, which just describes what happened, not why, and still doesn’t tell us if those marks were the result of good/bad luck or an actual underlying skill or lack of one. And yet, here I am, nearly buying into this whole Hendricks inducing weak contact thing. The Cubs put a historically strong defense on the field behind them, which suppressed every pitcher’s BABIP, so seemingly everyone wanted to figure out how much credit we should actually give to the pitchers themselves, if any. All that research seemed to agree that Hendricks legitimately generated weakly hit balls on his own, which go for hits less frequently, and combined with a fantastic group of fielders, essentially deserved that low BABIP.
It’s still just one season, and in 2015, he posted a league average .296 mark. But he also did the low BABIP thing in 2014, when he posted a .271 mark, so this wasn’t totally out of nowhere. And in both those seasons, he was at or near the top of the Soft% leaderboard (he led in 2016 and would have ranked fourth in 2015 if he qualified). It’s still not enough to completely convince me, but I’m listening. So even with a batted ball distribution that would typically yield a slightly higher than average BABIP, I’m going with a below average mark…to .280. Which is low, for me. Especially for a non-veteran with many seasons of proving such BABIP suppression ability. Combine that with a Cubs defense that should be excellent again and he should be a lock to beat the league average. Of course, there has to be some element of regression assumed, so my .280 is above his .272 career mark.
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 | 188 | 15 | 3.11 | 1.13 | 167 | 8.0 | 2.3 | 0.83 | 21.8% | 6.3% | 0.280 | 75.4% |
| Steamer | 174 | 12 | 3.59 | 1.21 | 156 | 8.0 | 2.3 | 0.95 | 21.3% | 6.2% | 0.294 | 72.8% |
| Fans (26) | 194 | 16 | 3.04 | 1.10 | 178 | 8.3 | 2.1 | 0.79 | 0.290 | 76.1% | ||
| ZiPS | 182 | 13 | 3.21 | 1.11 | 157 | 7.8 | 2.0 | 0.89 | 0.286 | 74.7% |
Remember when I quickly summarized the differences between the Steamer and ZiPS pitcher projections? Steamer regresses more heavily toward the league average for the luck metrics, which is the correct move the majority of the time, but not all the time. Hendricks is a perfect example of these methodological differences between the two systems. ZiPS assumes his suppressed BABIP is a more sustainable skill and regresses up to just .286, whereas Steamer brings it all the way close to the league average at .294. A similar thing is happening with HR/9, and the gap between the two would be larger if ZiPS wasn’t projecting a lower K/9.
Obviously, the Fans are the most bullish (when aren’t they?!), but surprisingly, I’m second lowest for ERA. When I finished projecting Hendricks’ peripherals, I was shocked, and to be honest, embarrassed, that the ERA my spreadsheet spit out was 3.11. I fully expected something in the mid-to-high 3.00 range. In fact, he was even one of my “Pan” choices in this year’s Fantasy Baseball Guide preseason magazine! Oops. This is what actually running projections accomplishes. You realize you kinda like someone you never expected to.
So far in the two drafts I have participated in, Hendricks has unsurprisingly been undervalued using my dollar values. I wasn’t the one to draft him in either league though, but it just goes to show you that no one wants to be that guy rostering the pitcher everyone knows is going to regress dramatically after a career year. The thing is, even after serious regression, he’s still a darn good pitcher.
Mike Podhorzer is the founder of ProjectingX IQ, an advanced fantasy baseball analytics platform that transforms projection data and in-season performance signals into actionable intelligence. He is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.
Mike, as the high man on Strasburg, what do you foresee in 2017?
This is a Hendricks post!
I think I’m always higher on Strasburg simply because of how my ERA is calculated. Based on his underlying skills, he should be posting higher LOB% marks. I don’t have my projections in front of me though, but I’m thinking that’s one of the reasons for the more bullish stance. Otherwise, same old, same old.
I’m kind of surprised, that a guy that loves numbers enough to build his own freakin’ projection system, doesn’t trust them enough to draft an undervalued player because he doesn’t wanna be “that guy”!
Isn’t “gaining an edge” the reason you do the projections? And you just give that edge back?
Hendricks’ FIP is good, and steady as a rock. He doesn’t seem like a big injury risk. He pitches for a great team. Not many starting pitchers can say that. Is he going to finish 3rd in the Cy voting again? Probably not. But I don’t see any reason to hesitate to draft him. Especially if its below your calculated price.
Ha, that’s not really it. I already drafted my “ace” at that point and my draft strategy is one where I then wait many rounds to draft my next guy. I’d rather an undervalued hitter than undervalued pitcher, so it just didn’t make sense for me to pair him with another starter I already drafted. I would never, ever draft two starters in the first five rounds.
Mike, I’ve got the No. 2 pick in my keeper league draft. Need to choose between Donaldson and Springer for max value over the next four years. Seven scoring categories are the typical 5 plus obp and slg. Springer is younger and will qualify at CF (important), but is moving to a new position. Donaldson is objectively better, but on the wrong side of 30 and could be on a different team next year. What do you think?
I think you always, always go with the player that will better help you win this year. You mentioned Springer qualifying at CF as mattering, so it sounds like your league format is unique. It’s impossible to answer a valuation question in a unique league without knowing all the specifics! And even if I do, I still wouldn’t know values without calculating them. Maybe the auction calculator could help.
I’d add that if you’re expecting serious jumps in Springer’s value in his age 27-30 seasons he’s going to need something to change; either in his batted ball profile (which might necessitate a lineup slot change) or his K-rates. I’ve been meaning to see if there are examples of players who meaningfully change their K rates after say age 26/27. My gut says no, not meaningfully, but I have no data to support it. For these reasons I’m typically the most bearish on Springer than anyone I know. I also fully appreciate my opinion may mean nothing to you 🙂 But there’s also a nice piece here on FG from December titled something like “Has George Springer hit his ceiling?”. Maybe give that a read and see if it helps spark some opinions?
Two of the three questions so far are about other players. Talk about no respect for Kyle Hendricks!
“Hendricks averaged nearly 6.3 innings per start last year, just 5.6 in 2015, and 6.2 in 2014. Naturally, those IP/GS figures ebb and flow with his ERA. I’m projecting a marginal decline to almost 6.1 IP/GS this season, because…spoiler alert — I kinda think his ERA is going to rise, which will knock him out of games a tad earlier.”
Hmmmm … IIRC, at the beginning of last season Maddon had a pretty quick hook for Hendricks, trying to limit his exposure to the third time through the lineup. It took Maddon a while to realize that Hendricks was having a great year and he should let him pitch deeper. Hendricks’s pre/post ASG splits bear this out: Before the break, Hendricks averaged 6.04 IP per start; after the break, 6.52.
Barring injury, I’ll take the over on 6.1.
I want to keep him for a very reasonable $$ but I just cant do it. Much more likely he sinks to a ranked ~~40th SP than repeats his top 10
Any reason that you do not account for quality-of-contact-allowed and batted ball distribution (pull/center/opp) in the analysis?
I get that there is an arbitrary nature to contact-management unless you get into the specific on pitch type, batted ball type and batted ball placement. You would need to take each ball in play as a separate case and determine if the supposed weak contact is real or not.
As far as I know, fans cannot see what percentage of pulled balls had “soft” contact ratings but I would assume this would provide good data for projections on how sustainable his contact-management “skills” are, correct?
Quality of contact was discussed in the BABIP section. There has been precious little research on batted ball direction distribution, how repeatable a skill it is, and what it means, so I’ve never looked at it as part of my pitcher analysis. It’s meaningful for hitters though and shows up in both xHR/FB and xBABIP.
I feel like I should mention that the entire Cubs rotation posted sub-.260 BABIPs, including such contact non-managers as Jason Hammel and John Lackey. Even Lester had a previous career BABIP of within like .010 of .300. The team BABIP was .255 so the relievers had similar BABIPs to the rotation.
So while I think it;s reasonable to project .280 for Hendicks, I also think it’s reasonable for the entire team, despite the fact that he leads in soft contact and other such things. I don’t think he’ll standout from his teammates BABIP wise.