Last Wednesday I took a look at the pitchers who have generated the most weak contact this year. Today I want to take a look at the other side of the coin and examine the guys getting hit the hardest. Let me start by saying I haven’t updated the data since I calculated it last Tuesday. Calculating the relevant data takes a whole lot of time, and I doubt it’s changed all that much after one turn through the rotation.

The reason the data takes so long to calculate is because I’m calculating sOPS+ for batted balls. You could find each pitcher’s sOPS+ on their b-ref page, but that takes walks into consideration, and walks obviously have nothing to do with batted ball quality. I have taken each pitcher’s sOPS+ for each specific batted ball type, factored in how often a pitcher generates each batted ball type and calculated their sOPS+ just on balls that are put into play.

If you’re unfamiliar with sOPS+, it is just the OPS allowed by each pitcher relative to league average. It’s similar to wRC+ or ERA-. In this case, numbers below 100 are better than average while those above 100 are worse.

The idea is that this is supposed to tell us more about the quality of the hits a pitcher is giving up. In this way the stat is much more relevant than something like BABIP because BABIP gives all hits equal weight. I like this stat for the same reason Michael Salfino likes ISO allowed. BABIP includes singles, which are the most common outcome and doesn’t even consider home runs. But sOPS+ considers all hit types and weights them. This means sOPS+ is much more likely to tell us if a pitcher has been ‘lucky’ than BABIP is. If you see a pitcher whose ERA is much lower than ERA estimators, sOPS+ will give you a much better indication of whether the pitcher is due to regress than BABIP will.

That said, here are the qualified starters with the worst sOPS+ so far this year. Read the rest of this entry »

We looked at pitcher mixes over the last month in order to see who’s made the biggest changes to their arsenals. First up were the pitchers that had gone to the slider more often.

Now let’s look at the pitchers that are throwing more changeups over the last month than they did earlier in the season. The changeup has none of the negative health ramifications of the slider, so in this case the question is: sure, you’re throwing it more, but is it a good pitch? And, also, why they might have made the change.

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We know that fastball velocity tends to increase as the season progresses. We all generally panic in April when our favorite sleeper’s velocity is down a mile per hour from last year, but usually by the end of the month, his velocity has returned and you’re able to sleep well at night again. But when we see a downtrend in velocity during the season, it’s a troubling sign. And the velocity charts on these three pitchers are concerning.

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On Monday I touched on Tony Blengino’s presentation on contact management that he gave this past weekend at Saber Seminar in Boston. Tony measured the pitchers who were best able to manage contact by looking at HITf/x data, data to which us normal people have no access. But I theorized that something like sOPS+ (like ERA- but with OPS allowed) could be a replacement for the HITf/x data. I thought that sOPS+ might be able to tell us which guys are better at inducing weak contact and thus which guys can have an ERA that beats their ERA estimators.

When I say “tell us” I should clarify that could mean two different things. It’s the classic explanatory versus predictive problem. Yes, sOPS+ can explain why a pitcher’s ERA is lower than his ERA estimators in a given season, but, as it turns out, it can’t tell us whether he’ll be able to do so the next season. I spent some time last night looking at whether sOPS+ in year one correlated well with the gap between ERA and SIERA in year two. The answer is no. While the correlation was stronger than it was between ISO allowed (another weak contact indicator) and the ERA-SIERA gap, it was still far too small to be meaningful.

It’s obvious that things like sOPS+ and ISO allowed don’t stabilize quickly. And that should not come as a surprise given that we know certain batted ball data takes a long time to stabilize. That doesn’t mean it’s not a skill. It simply means you can’t look at any pitcher’s sOPS+ or ISO allowed in the offseason and rely on it too much in projecting them for the next season. But when I say you can’t look at “any” pitcher, I mean you can’t just look at any old pitcher. I do think there are some you can look at. Read the rest of this entry »

With the season winding down, let’s take a look at the National League starting pitcher tiers. September is near, and that brings the promise of prospect call-ups once rosters expand. While one or two September call-ups could make a difference down the stretch, the rookies who may decide your league have likely already been in the majors for a while now. Where do they rank among the top players at the position? Let’s find out.

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It’s been about a month since the All-Star break, so our leaderboard splits can allow me to look at a pitcher over the last month and compare them to their first half numbers. Yes, arbitrary endpoints. But! Strikeout rate stabilizes in about a month, so at least it’s not the worst arbitrary endpoints ever chosen.

I took a look at the pitching mixes for qualified pitchers over the last month, and then compared those mixes to the first half. Let’s highlight the biggest movers in the major pitch types, starting with sliders today.

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If you’re a returning customer to the DLWW, then you know the drill: we’re here to talk about the barnacles that crawl at the bottom of the ship’s keel, the biofouling whose consideration is merited, by and large, by the dearth of available options in the deepest of formats. Such are the circumstances that invite us to take a look at whether the following two hurlers offer any SP help in NL-only leagues.
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Yesterday, I used my updated xK% formula to identify several pitchers who potentially have some strikeout rate upside. Today I will check on with the pitchers on the other side of the list — those whose xK% marks are most below their actual strikeout rates. These are some of the more interesting names.

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This week’s Change is about a missing changeup. Mike Minor’s changeup, to be specific. It’s half the pitch it used to be, and as a lefty facing many righties, that’s a big problem. Sure, the curve/cutter combo could be enough for Minor to continue being a major league starter, but as he’s in the midst of a bout of homeritis (that has plagued him on and off in his career), it’s worth asking about that changeup in the context of his current results.

Is it the change that changed how we feel about Mike Minor?

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This past weekend I had the pleasure of attending SaberSeminar in Boston. This is the second consecutive year I have been able to go, and I would highly recommend that you attend in future years if at all possible.

There were many great presentations, but one in particular stood out to me because of the potential relevance to fantasy baseball. Our very own Tony Blengino gave a spectacular presentation on the best and worst pitchers in the history of baseball at contact management (aka inducing weak contact). As far as I can tell, Tony took the HITf/x data, to which us normal people don’t have access, and calculated how each pitcher performed when allowing the various batted ball types. He then combined the performance on various batted ball types and scaled to 100 like we do here with things like ERA- and wRC+. I’m positive I’m simultaneously butchering the methodology while leaving significant portions of it out. Forgive me. For a little more insight, read Blengino’s recent posts on limiting hard contact for AL pitchers and NL pitchers.

This got me all fired up to get back home and see if I could calculate something like what Tony came up with so that we could use this as a fantasy tool. I was thinking this could be a new mechanism by which we could determine a player’s ability to induce weak contact. That’s a drum that Michael Salfino has long been beating by looking at ISO allowed. Salfino has rightly pointed out that hit quality (measured by ISO allowed) is more meaningful than the hit itself (measured by BABIP). Read the rest of this entry »