Yesterday, I published an article on a few pitchers whose fastball velocity changed over the course of last season. And then my old buddy MGL showed up.
He’s right. I have so much on my plate right now, mainly my first book and a 2019 player previews, that I didn’t take it another step forward. Here are most of his answers.
Yesterday, I reviewed my preseason list of starting pitchers composed of guys my Pod Projected ERA was significantly better than Steamer’s forecast. They were my upside guys. Today, I’ll recap how the guys my projections considered as having ERA downside ended up performing. You might notice that this is half the size of the upside list, which likely owes to my projections being more optimistic on ERA on the whole.
Piggy backing on my research into previous season breakouts published on The Hardball Times, I identified and discussed 12 such men from 2017 as we pondered 2018 performance. Not surprisingly, I discovered that last season’s breakouts made for terrible investments. Of course, this was as a group in aggregate. It doesn’t necessarily mean that every prior season breakout will bust. But as a group, they don’t make for good draft day targets.
In addition to sharing my standard lists of potential BABIP surgers and decliners heading into the 2018 season based on my xBABIP equation, I also discussed hitters who seemingly posted repeatable BABIP marks at first glance, but a deeper dive revealed the potential for dramatic upside or downside. These were the guys whose BABIP marks were around the league average (appearing rather normal), but with xBABIP marks at least 0.030 points above or below. Let’s see how they ended up performing.
Yesterday, I reviewed the list of 11 potential BABIP surgers for 2018 I published in mid-February. Today, let’s look at my BABIP decliner list. Given my past successes with decliners vs surgers list, I’m betting this list is going to look good. Let’s see if that turns out true.
A diverse pitching arsenal can help a starter successfully navigate a lineup several times since hitters have a harder time sitting on a single pitch. I went through the 2018 starters and found four pitcher groups who are the two ends of the spectrum. Either they rely on two pitches or have a diverse arsenal.
Many articles have been written about times through the order but the Holy Grail of research articles is the one MGL wrote a few years back. In it, he quantified how much having a third pitch helps. The research holds up even now. I took the 206 starters who threw at least 30 innings and found the percentage of pitches which were fastballs and next highest thrown. Normally, the average was around 75%. Then, I divided up the pitchers into 5% increments. Next, I subtracted the ERA from an average of their ERA estimators (FIP, xFIP, kwERA, SIERA) and here the average values. Read the rest of this entry »
In mid-February, I identified and discussed 11 hitters whose xBABIP marks stood significantly above their actual BABIP marks. I dubbed the group the potential BABIP surgers for 2018. There are two important caveats to remember:
1) This equation, while the best currently out there for estimating what BABIP should have been given underlying skills, is still not great, leaving lots of room for batters skills not captured in the equation, and of course, lady luck
2) xBABIP is not predictive/forward looking/a projection. It’s backwards looking like SIERA, but it correlates with next year BABIP better than BABIP itself, which is quite meaningful.
In early February, I essentially listed hitters who have posted low fly ball pull percentages. However, I added two important additional filters to finalize the list — above average Brls/True FB and Avg FB Dist. The idea here is that they already have the raw power to hit their balls out of the park, but they just need to hit those balls more to the pull side where the fences are closer. These are the guys I considered potentially benefiting most from more pulled flies. Let’s find out whether they did indeed increase their FB Pull% and if that jump also fueled a spike in HR/FB rate.
Rob Silver, the 2016 National Fantasy Baseball Championship (NFBC) Main Event winner and high-stakes fantasy baseball extraordinaire, messaged me on Twitter a few days ago to ask a question: Which source of pitching statistics are most accurate? I’m paraphrasing. Also, I could paraphrase the question any number of ways: Which source should we be using? Which most reliably correlates with pitcher performance?
It was a question for which I had no answer. Admittedly, I use a variety of sources, none of which align with one another — something I have noticed before but about which I can do nothing but shrug and accept it as a quirk of being a sabermetrician who bears the struggle of dealing with publicly available data.
The sources cryptically mentioned above include the following:
When I hear or read about a hitter playing through an injury my interest perks up and he becomes an immediate draft target. Standard projections have no idea these players played hurt and the lower production keeps down future estimations. Savvy owners can give these players a small talent bump and reap some nice rewards. My current request to create a detailed list of hitters playing through injuries for 2019 preseason research and to test after next season.
