It’s been a while, so it’s time to take another gander at starting pitcher xK% marks using my updated formula and compare those to actual strikeout rates. While strikeout rates do stabilize relatively quickly, there is still luck tied to sequencing that the formula attempts to strip away. These are the more interesting names that xK% suggests could enjoy a strikeout rate improvement the rest of the way.
Back in early March, we took a look at why pitchers work on new pitches and the ones that were doing so during Spring Training this year. Both Jensen Lewis and Josh Zeid offered their thoughts as pitchers that have gone through the process of adding a new pitch at the major league level. Martin Perez, Sean Doolittle and Jake Odorizzi gave quotes to writers in camp explaining why each was adding a new pitch in 2014.
Adding a new pitch does not guarantee success nor will it instantly improve the prospects of one’s career. The previous article cited examples of how new pitches aided Wade Davis, Kevin Correia and Ross Detwiler while it had a negative effect on Clay Buchholz.
Now that the season is three-quarters complete, we have enough of a sample size to ask the simple question: did the new pitches help?
As we continue to get closer to September, the real fun begins. While rosters haven’t expanded just yet, injuries and ineffectiveness have motivated teams to give their youngsters an opportunity. And that means a wealth of new names have been appearing in your free agent pool and will keep doing so. Let’s take a gander at three of those new names and decide if they are worth gambling on.
Like a pack of ragged animals picking through the trash bins of a poor neighborhood, us dumpster-divers come to these pages in search of the leftover scraps from the fantasy table. It’s coming to the end of the line in 2014, so let’s not waste any time looking at two deep-leaguers who could offer help in NL-only leagues.
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I’m in a big money league that has no innings cap or start limit, which makes the race for the strikeouts and wins categories a feverish one. Finding a league average starter on the waiver wire is no small task given the lower-than-normal replacement level in this particular league. Last week I considered Chase Anderson’s viability but was outbid for him by a FAAB-hoarder. This week I want to find out if J.A. Happ (2% owned) is worth adding. Read the rest of this entry »
We call it The Change, but in today’s case, we might have three instances where change looks like it’s happened… but it hasn’t. Is it possible that Carlos Carrasco, Shelby Miller and Trevor May have the same pluses and minuses they’ve always had?
In fact, that’s more likely than change. As much as we look for it.
Last week, our own math samurai Jeff Zimmerman published the results of his latest xBABIP equation for pitchers. While this is useful and ripe for analyzing, keep in mind that Jeff noted he had “not tested it with pitchers to see if the data correlates better season-to-season than regular BABIP”. So we’re still not sure how well the formula works, but it’s still interesting enough to investigate. We’ll start with those pitchers who have thrown at least 50 innings as a starter and have underperformed their xBABIP marks. This won’t be a straight biggest underperformer list, but a cherry picked one of the more interesting names.
Let’s talk. This is the last tier rankings update of the season and I wanted to take this opportunity to explain how these rankings transport from my brain to these virtual pages of typed letters. Judging by your comments on these very rankings each month, it’s clear that you take these seriously. That’s a good thing, as it confirms that what we do here is truly helping you, or at least you would like what we do to be helping you.
A couple of weeks ago, I released an updated list of hitters and their xBABIP values. After it was released I got a request for the pitcher xBABIP values. The xBABIP values are generated by using the hard hit batted ball data from Inside Edge. I have gone ahead and run the values and listed them below with some comments on a couple starting pitchers.
A few notes on the data. First, I have not tested it with pitchers to see if the data correlates better season-to-season than regular BABIP. I just applied the hitter’s formula to pitchers. Additionally, I used the league average Speed Score in the equation instead of adjusting it for each batter.