When looking at Jake Arrieta’s season thus far, it’s really hard to complain. His 1.74 ERA and 0.98 WHIP are virtually indistinguishable from his 2015 combo of 1.77/0.86. Expanding out further, the 28% K rate, 0.3 HR/9, .244 BABIP, and 57% GB rate look virtually identical to the 27%, 0.4, .246, and 56% marks from last year. There has been one stark difference, though. Arrieta’s walk rate has climbed from 6% to 9% this year. To put a finer point on it, he walked 48 batters in all of 2015; he has 40 already this year.

So what’s going on and should we worry at all?

First place I usually look with walk issue is first-pitch strike rate. Is Arrieta falling behind early and losing more hitters? The answer to that is a flat “no”. His 60% rate is the same as it was last year and if you move the decimal out, he’s actually a tiny tick better at 60.4% compared to 60.2%. From there I go to the chase rate. Are batters spitting on more pitches outside of the zone? That is definitely the case so far this year. His O-Swing rate was 34% last year, good for 11th in baseball. He’s down to 29% this year, just 49th among the 96 qualified starters.

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Four straight disaster outings in which Aaron Nola hasn’t seen the fifth inning, and he’s suddenly available on waiver wires. With seven walks and 14 strikeouts in those 13 innings, we already have one clue — his stuff looks unchanged, but something is being lost in translation.

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In this week’s edition of Deep League Waiver Wire, we’re doin’ a little plumbin’. Got to plumb! Plumb the depths, the depths of hell 18 team leagues and deeper. If you’re in a 14, 15, or 16 team league, you might be wise to pass on these players or just add them to your watch list but for those in leagues with 18+ teams or extremely large benches, I hope these guys are available. If not, let me know and the next time I’ll plumb further.

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There are numerous ways to use Statcast data to estimate FIP, many involving various methods for estimating HR/FB ratios using average fly ball distances or launch angles. I address the issue using a more granular approach, evaluating each batted ball on a case by case basis.  I am calculating the probability of the batted ball going over the fence by comparing it to all similarly hit balls dating back to the beginning of the 2015 season. Next, I sum all of these probabilities, and call it the estimated number of home runs. In theory, this number should be park and environment (temperature, altitude, weather) neutral, similar to xFIP in some ways.  I call this scFIP.

The following table shows the top 10 pitchers by scFIP. These pitchers have a minimum of 40 IP.

Last week, I discussed the importance of randomness in DFS, and some strategies one can use to take advantage of the large amount of random variation that occurs in daily fantasy. I’d like to expand further on that topic today by delving deeper into the process of focusing on specific portions of player projection distributions.

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Pitchers seemingly undergo true talent level changes far more frequently than hitters do, especially on a game by game basis. The velocity and movement of a pitcher’s pitches, along with his command, on any given day go a long way toward determining his fate. Let’s talk about two pitchers who struggled earlier in the year. One of whom we may never know for sure what the root cause of his issues were, while the other was almost surely injury related.

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The summer is heating up which means the standings are starting to solidify in your league. Big trades are going down and you find yourself uncharacteristically indecisive – do I make this deal or not? Will it actually improve my team enough to matter?

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We’re back from a couple of weeks on the DL, and just like actual baseball players, we got ready for our return by playing catch, though in our case it was with a couple of 9-year olds. Then, in our quest for the sabermetric equivalent of extended spring training, we sought a nice, easy research project of no particular consequence. The results of this project are set forth below.

The occasion for this particular project is the imminent return of Daily Fantasy Sports to the State of New York, where we reside. The story of how DFS came to disappear from New York in the first place and how it came to return is one about which we harbor numerous and abrasive opinions, all of which we will keep to ourselves for the moment.

We aren’t ardent DFS guys—it’s too time-consuming, too hard. But sometimes, we grow weary of our life’s work of translating the plays of Corneille into Estonian, and like to unwind with a twenty-five-cent sporting flutter. And sometimes, more to the point, our Roto season goes so sour so early—that’s you we’re glaring at, Randal Grichuk—that we need a diversion beyond what our efforts to keep our teams from finishing last provide. So we’re glad to greet DFS upon its return.

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“What makes a man, Mr. Lebowski? … Is it being prepared to do the right thing? Whatever the cost? Isn’t that what makes a man?”

I know how that exchange ends, and you probably do too. Perhaps the Dude’s response to the other Jeffrey Lebowski, the millionaire, was, indeed, right. But maybe there’s something else — something I’ve concocted to make myself feel better. Perhaps what makes a man is the capacity to admit he is wrong.

I was wrong. About Jeremy Hellickson, specifically. In late April, I pegged Hellickson as someone who would regress in his strikeout rate (K%) based on his zone contact rate (Z-Contact%). Technically, I was right — Hellickson’s 75.7% zone contact rate as of April 24 has converged almost all the way back to his career rate of 84.6% (it currently sits at 83.1%).

It’s the change-up I was wrong about. Hellickson’s change-piece posted some filthy outcomes through the end of April. I claimed nothing about the pitch changed. I looked at velocity and movement. I didn’t look at location. Hellickson is spotting the ever-loving crap out of his change-up, and it has worked wonders for him.

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Who’s inducing more swings and misses? Let’s take a gander at the American League starting pitchers whose SwStk% marks have most surged versus last year. Perhaps it’s added velocity, a new pitch, or change in pitch mix driving the spike. Let’s find out.

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