Note: I am using velocities from BrooksBaseball.net which has corrected their values from the 2016 to 2017 transition.

Dylan Bundy -2.5 mph (2016 FBv: 94.8mph, 2017 FBv: 92.3 mph)

Bundy’s decline is being obscured by the fact he relieved in 2016. Owners can see the 2017 drop and chalk it up to the normal velocity difference between starting and relieving. After removing the 2016 relieving values, his velocity is still down 2.5 mph.

For reference, here are his 2016 stats as a starter all of his 2017 ones.

Bundy’s approach and results are almost a textbook example of fastball velocity loss. The swinging strike rate on his fastball has dropped from 8.2% to 4.8% and therefore his strikeout rate dropped. Bundy realized his fastball isn’t the same, dropped its usage (61% to 50%) and relied on breaking pitches more.

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For a full primer on the process behind these rankings, check out episode 458 of The Sleeper & The Bust.

I decided to go a different route than the traditional 1 to whatever listing and went a step beyond the tiered rankings which allow for more nuance than just a numbered ranking, but still feel inadequate to tackle the many challenges of in-season pitcher management. I do still have tiers, but they are much different tiers and so they aren’t just talent-based groupings. They are more about usability in the fantasy game.

I have five different levels for active arms and then injury and minor league groupings for those we’re waiting on. We always talk “rest of season” when looking at deals and pickups, but I think we have to be more short term than that, especially with pitching. This doesn’t mean I’m wildly shifting rankings and my outlook on pitchers after every start, but rather I’m acknowledging that the landscape is going to shift so much throughout the six month season that trying to focus beyond a month or two is foolhardy.

The tiers are as follows:

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The leaderboards at FanGraphs is a fun place to poke around. Behold this list of pitchers:

What do they all have in common? Aside from having thrown at least 20 innings, these are the only hurlers in baseball who rank in the upper half of the stats I first look to when evaluating pitchers. Namely, they all boast better than average K-BB%, GB%, Z-Contact%, and swinging strike rates. There are some obviously great pitchers on this list but I’m not interested in talking about Clayton Kershaw, Jon Lester, or Carlos Martinez. Though if you’re a little frustrated with Lester or CarMar, I both empathize and suggest exercising a little patience. Rather, I’d like to dive deeper into some of the list’s lesser-owned and lesser-known players who won’t cost nearly as much to acquire.  Read the rest of this entry »

We all know that names like Chris Sale, Danny Salazar, and Chris Archer are going to rank among the top tier in SwStk%. So let’s instead discuss the surprising names inside the top 20 in the American League of SwStk% that have all enjoyed surges from last season.

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Having last week identified some hitters who seem to us to have been lucky or unlucky so far this season, and then suggested what their trade value might be if their luck evens out, we now work the same magic with starting pitchers. These guys’ granular stats, we posit, indicate that they’ve pitched significantly better or worse than their Fantasy-relevant numbers suggest that they have.

We propose that they’ve been unfortunate, and that their fortunes will change. So we ask ourselves (1) who are these guys? (2) what will their stats look like over the rest of the season if their luck balances out and their full-season numbers are about what they were projected to be? and (3) what other pitcher’s expected performance will our guy’s rest-of-season stats resemble?

Our methodology is simple. We first tried it last year, with some success, and then in the preseason, where it would have pointed you towards Dallas Keuchel and away from Julio Teheran. So it shows promise. To find guys who’ve been lucky, we look for starting pitchers who are the top third of their cohort in Batting Average on Balls in Play and in Flyball/Home Run percentage, but the bottom third in Hard-Hit Percentage.

We figure that a guy who’s not getting hit hard but giving up a disproportionate number of hits and home runs is a good candidate to turn his season around. And we turn the method on its head to identify the lucky guys who do get hit hard but—because they’re giving up fewer home runs and hits than they should be—don’t yet have the scars to show for it. We think those guys are headed for a fall. Read the rest of this entry »

By now, most gamers have noticed Trevor Cahill’s excellent start to the year for the Padres. Another member of San Diego’s rotation is pitching fairly well, too. A 4.13 ERA and 1.38 WHIP don’t result in fantasy gamers flocking to the waiver wire to add a player in most cases, but this pitcher’s underlying stats are mighty intriguing.. This groundball-inducing machine is owned in just 20% of CBS leagues, 4.0% of ESPN leagues and 3% of Yahoo! leagues. A look under the hood hints at some very real breakout potential, and at the least, deep league relevance. Read the rest of this entry »

5/11/17

The latest episode of “The Sleeper and the Bust” is brought to you by Out of the Park Baseball 18, the best baseball strategy game ever made – available NOW on PC, Mac, and Linux platforms! Go to ootpdevelopments.com to order now and save 10% with the code SLEEPER18!

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Strategy Section: Buy Low Arms

• Drew Pomeranz (5:55)
• Jeff Samardzija (12:10)
• Sean Manaea (21:18)
• John Lackey (27:25)
• Kevin Gausman (30:07)
• Danny Salazar (37:55)
• Kenta Maeda (42:33)
• Jake Arrieta (46:02)

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In my AL-only league, I needed to fill in a couple pitching slots with James Paxton and Corey Kluber on the DL (and Berrios still in the minors). With almost no time for research (8 pm Sunday deadline), I bought both JC Ramirez and Mike Clevinger on a whim. Here’s what I ended up with.

JC Ramirez

Ramirez was exclusively a reliever in the majors until his last five starts. While his 3.74 ERA is not ideal, he has an 8.8 K/9 and 2.9 BB/9. I went back and watched his start on April 19th against the Astros (great camera angle). Here’s what I saw.

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Traditional pitching metrics, such as innings pitched, and pitch counts, have often missed the mark when it comes to preventing pitcher injuries. As a result, I developed the Fatigue Units metric – which shows promise in illustrating how extreme workloads can influence pitchers in the subsequent seasons.

As a quick refresher – Fatigue Units are calculated by looking at an interaction between the number of pitches thrown, the velocity they are thrown at, the time taken between pitches, and the number of days between appearances. In the 2015 and 2016 season – these were your FU leaders.

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Last week, I identified and discussed eight American League starting pitchers that have seen their fly ball rate increase most versus last year. Let’s flip the coin this time and check in on those starters that have seen their fly ball rate decline.

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