Yesterday, I used my xBABIP equation to identify and discuss eight hitters who appear due for a BABIP surge. Today, I’ll check in on the other side of the ledger, those whose xBABIP marks are significantly below their actuals, suggesting serious downside.
Last year, I utilized our Splits Leaderboard and incorporated shift data into my newest xBABIP equation. So with just a couple of weeks before the all-star break, let’s calculate xBABIP for all hitters and discuss eight of them whose marks are significantly higher than their actual BABIPs, suggesting dramatic upside potential.
This year, I’ve been caught up on pitching. I investigated the nuance inherent to swinging strikes, indirectly made a case for completely abandoning the sinker with this piece comparing pitch type outcomes, and (maybe) identified the keys to unlocking pitcher BABIP and HR/FB.
Here, I’ve modeled swinging strike and ground ball rates using only pitch velocity movement. Surely, this work can be improved; my quantitative tool set, while fairly robust compared to the layman, is meager compared to the professional or even hobbyist statistician. Regardless, I think it’s pretty cool, and I hope it adds to the conversation constructively.
Mostly, this serves to satiate my own curiosity. Unfortunately, it may be denser than I expected — few answers are ever quite as simple as you hope them to be, I guess.
I linked to several of my own pieces above. Dan Lependorf wrote about estimating ground ball rates in 2013 at the Hardball Times, although its conclusions have an anecdotal slant. (It thinks about velocity and movement but doesn’t take the requisite steps to bridge the logic.)
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At the beginning of the year, I revealed the latest and greatest xHR/FB rate equation for hitters. I discovered that the new Statcast metric Barrels was highly correlated with home run totals (duh), but better yet, the ratio of barrels to true fly balls (which is just fly balls minus pop-ups), was even more correlated. If Brls/True FB is an important metric for hitter HR/FB rate, then it follows that it’s also important for pitchers as it relates to their HR/FB rate allowed. So let’s compare a pitcher’s Brls/True FB rate to his HR/FB rate and see if we could find any discrepancies that would hint at improvement.
| Name | HR/True FB | Brls/True FB |
|---|---|---|
| Eduardo Rodriguez | 12.2% | 12.2% |
| Blake Snell | 12.3% | 16.4% |
| Jameson Taillon | 13.6% | 16.9% |
| CC Sabathia | 14.3% | 17.1% |
| Tanner Roark | 13.6% | 17.3% |
| Gerrit Cole | 13.0% | 17.4% |
| Jose Quintana | 16.1% | 17.7% |
| Population Average | 14.0% | 23.3% |
My population was the 92 qualified starting pitchers and that’s what the population average line is calculated from.
Eduardo Rodriguez’s HR/True FB sits below the league average, but not by much. He actually ranks fifth lowest in Brls/True FB, and out of the top 11 that includes him, he has the highest mark, outside of two Rockies pitchers. Fenway Park isn’t a home run friendly park, so can’t blame it on that. While it’s questionable whether E-Rod could actually maintain such a sterling Brls/True FB mark, his HR/True FB rate should probably be in the single digits given what has happened so far. He has maintained that strikeout rate surge he enjoyed last year and is backed by an excellent offense. He should be owned in all formats.
Man, there have been a lot of things that Blake Snell has done to truly impress me. Add his weak contact induced on fly balls to the growing list. Interestingly, he also plays half his games in a home run suppressing park, so you would think that ranking 12th in Brls/True FB would also lead to a single digit HR/True FB rate. With Snell, you’ll always be wondering if his control is going to desert him, but so far, so good. I’m a big fan.
Jameson Taillon allowed a homer in yesterday’s start, and that’s likely to change these rates. That said, he’s the third of three who sits with a HR/True FB rate above what his Brls/True FB would suggest, despite calling a pitching friendly venue home. Taillon reminds me of Gerrit Cole in that his stuff suggests much gaudier strikeout rates. It’s likely a Pirates organizational thing, but it’s silly. What Cole has done in Houston should make the team realize that pitching to contact isn’t a winning strategy.
Wow, what a transformation CC Sabathia has made! As his velocity and strikeout rate has tumbled, he has become better and better at generating soft contact. He needs to sit Felix Hernandez down and teach him how to pitch with diminished stuff. He’s the first guy on here who plays in a home run friendly venue, which certainly would push his HR/FB rate higher than his Brls/True FB. Still, he should be better than this.
Tanner Roark quietly does his thing, putting up solid ERA marks, despite mediocre underlying skills. But this year he’s really squashing fly ball contact quality. His appearance returns us to the list of pitchers playing in pitcher’s parks. Bizarre.
Speak of the devil, I had forgotten that Gerrit Cole made the list when I mentioned him in the Taillon blurb. If there was anything else we could point to in order to describe his dominance.
Jose Quintana easily owns the highest HR/True FB rate on this list, which has conspired to push his ERA above 4.00. Issues with the longball only exacerbates his sudden struggle with control. Interestingly, he never had issues in Chicago, another friendly home run park, and Wrigley Field isn’t nearly as bad. I would still never own a pitcher with such a weak SwStk%, as I don’t believe in his low-to-mid 20% strikeout rate, but at the very least, Quintana’s HR/True FB should decline.
Yesterday, I used my xHR/FB rate equation to identify and discuss eight hitters whose marks suggest an imminent surge in their actual HR/FB rates. Today, let’s check in on seven fantasy relevant hitters on the other side of the coin — those whose xHR/FB rates are well below their actual marks, suggesting near-term downside.
It’s been a while since I calculated my xHR/FB rate equation and compared its results to each hitter’s actual marks. So let’s discuss eight names, plus two bonus names, with HR/FB rates that fall most short of their xHR/FB rate marks. While there are no guarantees in life, especially baseball, there’s a strong chance that each one of these hitters raises their HR/FB rates the rest of the season, assuming they can maintain the underlying skills driving the marks.
I’m going to blame Mark Melancon. I started out yesterday with the hope of writing about him. The article was selfish because I took a chance on Hunter Strickland before he was named the closer and my gamble paid off. With Melancon back, I wanted to see if his reduced velocity cutter would still be useful. And that was as far as I got with the article.
I was sick of thinking about fantasy baseball. The problem is that when your livelihood requires continuous fantasy baseball content, this sickness can’t last. I tried to move onto another topic with no luck. After a few unproductive hours, mainly wasted on Twitter discussing valuing player risk, I just gave up. The dog days of summer hit me head on and I lost.
This event usually occurs me a couple times during the summer with content and demands coming at me constantly. I approach them two ways. Either I just power on and produce 20-grade material or beg my bosses for a break. As this article demonstrates, I am going with the first approach.
Yesterday, I mentioned some hitters’ ownership rates. I planned on referencing this previous article which applies ownership rates for different leagues sizes and host website. Then, I noticed it was from 2010. It’s time for an update.
Sadly, there will little-to-no analysis today. I’m dumping data after spending too much time scouring several websites for the needed information. I was tempted to submit his article with just the graph but I better add some “words” so it’s an “article”.
Simply, I collected the top 550 ownership rates from four major sites, ESPN, Yahoo, CBS, and Fantrax. With these values, I created this graph.
Earlier this week, I found most of Tanaka’s struggles occur with men-on-base. What I didn’t know if these differences were predictive or due for regression. After diving into the numbers, struggles with men on base aren’t exactly predictive except for those with extreme windups.
The narrative concept behind this study is that a pitcher has a windup talent level and a throwing from the stretch talent level. I’ve always thought Daniel Mengden’s great windup would keep hitters off guard.
He loses all the deception from the stretch. My theory has been borne out with a career 4.99 FIP with runners on base and 3.42 FIP with the bases empty. Joey Lucchesi is another pitcher with a unique windup and he has a 3.40 FIP with no runners on base but it jumps to 5.14 with runners on. The windup advantage for these two pitchers is an obvious item to point to when explaining their stats.
Masahiro Tanaka decided to create more questions than answers in my life. I just released my first 2018 pERA run and Tanaka’s pitches and control point to a 2.88 ERA but he’s posting one nearly two points higher at 4.95. I dove into his stats hoping to find a simple answer, instead, I found someone struggling out of the stretch while throwing harder. While it explains his struggles, I am not sure any of it matters. At least not yet.
The first item I checked for with ERA and estimators diverge is a high BABIP which was only at .243, about 30 points lower than his career average (.276). Nope, not BABIP.
