There are over 30 starting pitchers on the disabled list right now. I tabbed about 29 of them as fantasy viable, while understanding that the viability ranges substantially from 10-team mixed to 12-team AL or NL only. The point is that the pool has taken a hit in the first 2.5 months, as it does every single year. We haven’t seen the spate of Tommy John surgeries that struck the league the past couple of years, but there are plenty of injuries that can be severe without being TJ. The piling up of injuries takes its toll on waiver wires everywhere and lowers our barrier for entry to tab a guy worthy of bidding.

In April, an exemplary start from someone available on the wire isn’t instantly going to draw attention. You might not have anyone you’re ready to cut to make for him and if a guy wasn’t worthy of being draft a week or two ago, one strong start isn’t likely to change that opinion. Now 2.5 months in, you’ve got high-strikeout middle relievers bridging the gap on your latest injuries and all of a sudden you’re making eyes at Jered Weaver because he has a two-start week.

First things first, don’t pick up Weaver. Five relievers have more strikeouts than Weaver’s 46: Dellin Betances (59), Andrew Miller (51), Seung Oh, Kyle Barraclough, and Brad Hand (47). Hand’s 35.7 IP is the high in that group and still less than half of Weaver’s 75.7. Beyond avoiding Weaver, you really have to be ready to act fast on pitchers. Magnitude takes on a bigger role at this stage in the season when we aren’t afforded the luxury of waiting for a reasonable sample. Truth be told, this act first, ask questions later model is just the new way to play, even early in the season. But as options dry up, decisions have to be even quicker.

This method will produce some duds. We’re using small samples and picking up guys who are still on the wire in June for a reason (or reasons), but if you’re going to find this year’s Cody Anderson (3.05 ERA in 91.3 IP after coming up on 6/21 last year) or Erasmo Ramirez (joined rotation in mid-May, but had 4.96 ERA at this time last year before finishing with a 3.17 in 110.7 IP), you have to be ready to pounce. Here are a few pounce-worthy arms who may still be on your wire depending on league size.

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Throughout his career, Danny Duffy has shuffled between the Royals starting rotation and their bullpen. Let’s compare his underlying skills in each role:

Danny Duffy Skills – Starter vs Reliever

Role	K%	BB%	LD%	GB%	FB%	IFFB%	SwStr%	BABIP	LOB%	HR/FB	ERA	SIERA
Starter	18.6%	9.7%	21.6%	36.3%	42.1%	15.1%	8.3%	0.288	75.5%	8.7%	3.89	4.48
Reliever	31.2%	7.1%	21.7%	43.4%	34.9%	10.3%	15.0%	0.298	79.2%	3.4%	2.08	2.48

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Jeff Sullivan wrote about Matt Shoemaker last week, being one of the first (to my knowledge) to note that Shoemaker had recently ramped up the usage of his splitter. I’m reluctant to overdo it, but you should read that first. I’d also like to borrow one of the main points he made in order to better establish my narrative. I hope you don’t mind.

Sullivan noted Shoemaker’s increased use of the splitter in all counts. Which is great, because it’s arguably his best pitch. His slider is good, too — both induce an almost-equal percentage of whiffs per swing — but it’s the splitter that has coerced a meager .117 isolated power (ISO) in his Major League career. That’s a big part of it. More splitters means fewer other things, and those other things, as Sullivan noted, have generally been bad.

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Traditionally, daily fantasy sports projections use average projected points as the primary method of evaluating players. While one can get a sense of a player’s consistency and upside based on their batting profile and game log, it is difficult to accurately and precisely project players’ upside in terms of DFS points and performance relative to each other.

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It’s that time of year again, American League starting pitcher tier update time! I still pay no attention to ERA, as it’s not a metric I use for evaluation and ranking pitchers for rest of season performance. Player movement between tiers will only occur when there’s a change in underlying skill, pitch mix, or velocity.

Tiers are named for the best characters on the brilliant FXX show, Man Seeking Woman.

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We are now two months into the season and I’ve definitely evolved my thinking on a number of pitchers. I try not to overreact and change my outlook start-to-start, but we’re getting a relatively worthwhile sample on the books and pitchers are always changing so if you stay married to everything you thought in March, you’re going to get left behind on guys for better and worse. Here are three guys I’ve really changed my tune on so far (and they’ll weirdly all lefties).

Steven Matz is Really Good

I hated Matz’s draft slot coming into the season. I thought he was being way overdrafted as the 30th SP off the board and it was more because of his health than his skills. It felt like a lofty draft status based on six MLB stats. Coming up through the minors, he put up great numbers, but only once topped 106 innings in a season. He was pummeled in his debut after being pushed back to April 11th, but he’s been damn near unhittable since: 1.13 ERA, 0.85 WHIP, 49 Ks and 7 BBs in 48 IP. He has three scoreless starts and three where he allowed just 2 ER. A balky elbow caused another layoff in the midst of this run, but he has shown no ill affect with two brilliant starts since returning.

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I figured it was time.

I used strikeouts minus walks for the first sort because that’s been shown to be the best in-season predictor. I then eyeballed fastball velocity and pitching mix. There are a few places where I went with upside because I saw these as mixed league rankings. If you’re in a deeper league, look past the prospects and instead consider the veterans that are pitching now.

Feel free to argue a guy up or down. I may make the move!

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I know some tiered rankings have come out this week, but I wanted to take you in a little different direction this week. Next week I will have the first base tiered rankings up. This week, I wanted to explore a new statistic I came up with that will probably not help you win your league. It is simply a fun way to look at pitchers in a different light, so I hope you enjoy reading about it as much I enjoyed exploring it.

I am fortunate enough to have Jake Arrieta on one of my teams, so I have been able to look at his starts individually. I started to notice that even though he was giving up very few hits, he seemed to be giving up a lot of walks along with a high number of strikeouts. This got me wondering if Arrieta was turning into a modern day Nolan Ryan, where he was not going to let you make contact even if that meant walking the hitter. Turns out there are better comps to Nolan Ryan, but I’ll get more into that later.

Initially, I thought I could look at contact%, but that looks at every single pitch and that is not really what I wanted. I wanted to see which pitchers allowed the least amount of balls in play on average. So I created the Nolan Ryan percentage (NR% for short). To calculate NR%, you simply add K% and BB%. Nothing complicated. Nothing groundbreaking. Just a fun way to see which pitchers are like Nolan Ryan in terms of either striking out or walking most of their hitters.
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SaberSim Daily Projections

Daily projections require a great deal of context in order to project each specific game. SaberSim daily projections account for lineups, starting pitchers, and bullpens, as well as more nuanced factors like weather, umpires, park effects, home/away, handedness splits, and more. Even within these specific factors, there’s a tremendous amount of detail involved, and constant room for tweaks and improvements. For instance, the park effects are not applied broadly, but rather based on how they affect each individual outcome (BB, K, 1B, 2B, 3B, HR) for left-handed and right-handed batters.

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Last year, I determined that pitcher batted ball distance allowed was correlated with HR/FB rate to a reasonable degree. This was fairly obvious, though the correlation was much lower than I expected, and less significant than that of hitters. It’s why I rarely discuss pitcher batted ball distance, along with the fact it doesn’t correlate from year to year all that well. But the correlation is there and it does convey meaning. We could run the same analysis for pitchers, comparing their distances with HR/FB rates to identify those due for improvement or regression. So today I’ll look at American League starting pitchers with highly inflated HR/FB rates, but distances that suggest major improvement is on the horizon.

While some of these players will obviously improve due to how high their HR/FB rates are, you might wonder if that improvement means a 10% mark going forward or a 14% mark the rest of the way. This analysis should help form those expectations.

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