Time to update the pitching ranks, as we’ve received more information and depth charts are starting to sort themselves out.

There are velocity changes to report. Jeff Samardzija hasn’t averaged 93 in a start yet, so that’s not good. Scott Kazmir is under 90 for a couple starts now, also not good — but it turns out those were cutters! So maybe he’s fine. Doug Fister is up! Around 90. Jacob deGrom was down to 92 in the last start, but was fine the one before, so that’s less worrisome. Garrett Richards is up! He was always up. So is Dylan Bundy though. He probably doesn’t have a starting role, though. Cody Anderson is up and now he looks like Matt Harvey. Adam Conley is up and I still like him, now a little more.

There are injuries of course! The Dodgers have most of them, but even the guys coming up behind are injured, and the group at the back isn’t very exciting to begin with. Matt Cain’s injury might push him back enough to give Chris Heston a shot to start the season at least. Or maybe not. Surely there will be a few more before spring ends.

And then there are depth chart movements that have already been made. Trevor May is a reliever. Erik Johnson was sent down. Brandon Maurer is a reliever, meaning Colin Rea and Drew Pomeranz and Brandon Morrow are fighting for two spots.

Throw them all in the blender and update your ranks. Eno’s Ranks, 2.0.

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I’ve been batting over .300 on bold predictions for a while, and I’ve also been getting crap for not being bold enough. So, in the honor of So So Def, I’ll stop slacking on my pimping, and I’ll turn it up.

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Another AL-LABR draft is the books, and after finishing top half in 2014, and then at the very bottom in 2015, I figured I should change my strategy a bit going into this year’s draft. In some ways, I built the same team I always do for the League of Alternate Baseball Reality — I hate dollar players, and hate spending for the most expensive players, and I dive for the middle — but my preparation was different. You can’t completely change your stripes, in the end. You can only hope to tweak em.

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After all of our focus on injury rates due to sliders and curves, which were good efforts but produced small results, it’s interesting to consider sinker usage as a possible marker for injury. Bill James did so, famously, a while back. He thought that ground-ball pitchers were only good for a short while, and then injured.

The response was swift from the saber metric crowd. Bill Petti couldn’t find an effect. Russell Carlton looked into injury prediction and found the following as important to shoulders. You’ll notice that ground ball rate is not included.

“First, shoulder injuries. In order of strength of prediction, the best predictors of whether or not you will have a shoulder injury in the coming year are whether you had a shoulder injury last year, how many pitches you threw last year, whether you had a shoulder injury two years ago, how many extra batters you faced last year from the year before (with a greater increase meaning that you were less likely to be injured), and the two-strike foul rate (just barely).”

Still. Let’s look at the top sinkerballers of the last three years. Perhaps sinkers are the source of the issue, not straight ground ball rate. You can get a ground ball with your secondary stuff, after all, and there is something about the sinker that combines internal shoulder rotation and big velocity that might actually be mechanically risky.

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When we looked at movement and velocity with respect to changeups, curves, sliders, and rising fastballs, we found that more movement was almost always better. It gets a little bit more complicated that than that — drop is mostly better for swinging strikes and horizontal movement was better for grounders, and the effects are not super large — but it’s a decent pole to hang on to in the storm that is projecting pitchers.

We can then easily do the query that asks: which pitches changed the most from last year to this year?

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Before I try to do this in a (slightly) more scientific way, let me say that you can easily create tiers via the sniff test. Take a look at the pitching pool and try to assign groups labels, like ‘ace’ and ‘front of the rotation’ and ‘mid-rotation’. It’s what we do when we are trying to talk about prospect pitchers and where they might slot in later, it should come fairly naturally, and it will help you make sense of your specific player pool. It’s a worthy exercise no matter how rigorous the background work was.

Now let’s try to apply a more reasoned approach to the matter.

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We looked at strikeouts plus pop-ups minus walks, even if I need to re-run those numbers with pop-ups divided by plate appearances. And then we looked at Arsenal Scores, even if I need to re-run those numbers with more precision. Those things, plus projections, all inform my rankings, which I’ll run below.

But a word about my process. Pitching foils projection systems more than hitting for a reason: there are small changes that can make a huge difference. And changes in role are huge.

So, if you sort for the third category in my rankings below (difference percentage), you’ll find a bunch of guys that made small changes down the stretch that I think will make a big difference. And a bunch of guys that I think will win the fifth starter role. As well as guys that get hidden outs with the pop-up, and a bunch of guys undervalued by their overall numbers despite good arsenals.

You might be surprised to hear that I don’t run this all through a projection system and press go, and then run the rankings. That might be the best way to go. But I’m more intuitive. I’d rather play the would you rather and rely on my first impression in some cases. I’d rather go by my own sense of the depth charts than any that is put together for me. I’d rather feel my way through the ranks.

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The theory first. By looking at the results on a per-pitch level, we can spot pitchers that have somehow been worse than the sum of their parts to date. Those pitchers, with better sequencing and selection of their existing pitches, or just luck, could be better in the future.

In order to avoid the problems inherent in balls in play data, we’re going to focus on two classes of information that help us the most — ground balls and strikeouts. We’ll z-score every pitch thrown over 100 times last year and sum up the scores. Let’s focus on starters — depth of arsenal matters more for them. And let’s report summed up z-scores as well as average ones per pitch. One tells us how good their collective pitches are, the other how even their arsenal is.

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We know that strikeout minus walk percentage is the best in-season predictor, or at least we knew that the last time someone checked. We know that pop-ups are automatic outs, and that they have the same season-to-season correlation (.49) as strikes thrown, or at least we know that if you define pop-ups as infield flies per ball in play (PU/BIP) instead of just IFFB (which is PU/FB). And that means we know that these three metrics are three of the strongest by year-to-year correlation, at least among the metrics that the pitcher has the most control over.

Since we ‘know’ these things about as well as you can know things in baseball, it seems about right to combine them into a simple metric. Strikeouts plus pop-ups (the good things) minus walks (the bad things). It’s a quick and easy way to rank pitchers based on what they actually did last year, and it’s how I’ll sort my rankings the very first time I start working on them.

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There aren’t a lot of ways to predict closer change. Don’t go looking at ERA, projected or past, it’s not useful. Nor are three-Year Fielding Independent Pitching stats, even if those give you a bigger sample. Experience closing? Nah. Shutdown percentage? Nope. It’s not even important whether the pitcher was the favorite or a bullpen committee member. Depth of arsenals — and platoon splits on pitches — seem important, but aren’t really.

These things don’t seem to matter much when it comes to closer changes.

The list of things that might matter is super short, and the effects not so large that you’d want to stake your life on them. Reliever strikeout rate and velocity is important — new closers have higher rates and more velocity than the closers they replace, at least. Closers have slightly more experience in general (they are older). And lefty closers are about half as likely as you’d expect given the population of lefties in the game. Closers usually come from the end of the bullpen, so role is important.

We could use these facts to create a list of relievers that might close this year, really. If you then somehow controlled for the excellence of the closer in front of them, you could even sort this list for likelihood of change. Then we’d have the Non Closers Most Likely to Close This Year. Seems possible.

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