A week ago, I identified the starting pitchers whose xK% marks were most above their actual strikeout rates. The swinging strike component is the most significant in my xK% equation, so let’s take a look at which pitchers have enjoyed the biggest surge in their S/Str (Baseball-Reference metric) this season. The 2015 numbers do not include yesterday’s starts.
It’s tier update time! I’m notoriously stubborn when it comes to changing my opinion of a player and three or four starts is far too small a sample to convince me to make any real dramatic adjustments. However, there are some scenarios in which I will reconsider — a change in fastball velocity, a change in pitch mix, an injury, or perhaps the pitcher’s defensive support performing better or worse than expected. That’s really about it. I care little for actual results at this point unless there’s a significant change in results not explained by the aforementioned factors. Like, if Mark Buehrle was suddenly striking out more than a batter per inning. My xK% equation is fantastic in small sample sizes since it’s based on per-pitch metrics and not innings or batters faced. But still, the underlying components themselves could quickly change.
As a reminder, the tiers are named after the best characters from the FXX show, Man Seeking Woman.
As usual, injuries create opportunity for others. That’s the theme yet again in this week’s edition of the deep league waiver wire.
Yesterday, I took the first look of the 2015 season at starting pitcher’s xK%. I began with the potential surgers, those pitchers whose expected strikeout rates were most above their actual marks. Today will be the opposite side of the coin. These pitchers have posted strikeout rates significantly above what their mix of strike percentage, swinging, called and foul strike rates suggest. They could be in for strikeout rate collapses if they don’t improve those peripherals.
As we near the end of the month, our samples remain far too small to perform any serious analysis on. But, that’s really only true when we’re using plate appearances or innings pitched as our denominator. My xK% equation is based on per-pitch metrics, which stabilize much more quickly than anything based on innings. No, I don’t know the actual stabilization point, but since a pitcher has thrown more pitches than he has innings pitched, that’s what’s going to happen.
So let’s take a look at those starting pitchers whose xK% marks are most above their actual strikeout rates. These are the guys with significant upside who should enjoy a strikeout rate surge in the near future.
The buy low and sell high strategy has been a favorite one of fantasy leaguers for as long as fantasy sports has existed, I would imagine. Unfortunately, it’s nearly dead given the wealth of freely available information and the deeper knowledge we now possess about how to evaluate player performance. Nearly dead, not completely dead. To buy low or sell high on a player, you need a story, a narrative that essentially offers up confirmation bias and makes the owner you’re dealing with feel all fuzzy inside when agreeing to the trade.
Cursing at the injury Gods already? Yeah you are. Let’s see what your free agent pool might offer in your deep league.
The second of last week’s challenges asked you to prove that a low BABIP means that the pitcher induced weak contact. I’m tired of reading that Pitcher X has a .220 BABIP and so that means he has “kept hitters off-balance”, “induced weak contact” or that “hitters have a difficult time squaring him up”. The opposite is equally as annoying, reading that Pitcher Y, sporting a .330 BABIP, is “hittable”. With no evidence ever presented to support such a conclusion aside from the BABIP itself (and perhaps, if we’re lucky, a mention of the batted ball distribution allowed), the claims are meaningless.
All of those descriptions may very well be true, but we still have no real proof of it for any specific pitcher, so it’s all just conjecture. That has no place in fantasy analysis when these statements are made as if they were facts. It’s misleading to the reader and a real disservice.
I’ll climb down from my high horse now and get to discussing the comments.
Last week, I issued a challenge. If you’re the type to call a pitcher who sports an inflated HR/FB rate “homer-prone”, I asked you to prove that this was not merely bad luck, but skill-related (or a lack of skill). I have been writing about fantasy baseball for 7+ years now and nothing bothers me more than when a definitive claim is made with no supporting evidence. There is a difference between “Pitcher X is homer-prone” and “Pitcher X has been homer-prone”. The former suggests an inherent lack of skill in keeping fly balls in the park, while the latter makes no such commentary on the pitcher’s home run avoidance skills, but merely describes what has happened.
Since it’s clear that we really don’t know for sure what leads to home run suppression skills or a lack thereof, at this point, only the aforementioned latter description seems appropriate in my mind. So Brandon McCarthy’s early struggles with gopheritis, which has carried over from last year’s issues, was what motivated me to challenge you, as I figured the homer-prone label would start popping up everywhere.
Yesterday, I issued my first challenge. Sparked by Brandon McCarthy’s bizarre outing on Monday, I asked you to prove that his HR/FB rate was not bad luck. The challenge led to some great discussion, which is exactly what I had hoped it would do.
Now it’s time to move on to the second, and likely final, challenge. It’s a topic that I am more interested in and has been debated ad nauseam. Of course, I’m talking about pitcher BABIP. We have been taught that pitchers will tend to regress toward the league average, which has sat around .295 in recent years, as hitters actually possess the majority of control over how often balls in play falls for hits. So early on, we eventually came to accept this.
