Spin rate is becoming ever more important to baseball analysis now that we have access to more reliable measurement devices. Namely, Trackman. But there are other technologies as well which are being used by high school, college, and minor league teams. Trackman is the big name, though, since it has been adopted by MLB, NPB and KBO along with many colleges and even a few high schools.

Trackman uses Doppler radar to measure the movement of the ball. I want to paint a picture in your mind of what this may look like, in the eyes of the radar. Remember, we’re trying to track the ball here. Read the rest of this entry »

I have never been supportive of pitch clocks. In fact, the first ever thing I wrote about baseball (formally), was an article in the Journal of Sports Sciences, illustrating how pitch clocks could elevate muscle fatigue in pitchers, possible contributing to increased injury risk. I also came up with a workload metric which factors in the time between pitches when calculating the number of Fatigue Units a pitcher can accumulate. I was pleased to read Travis Sawchik’s article on pace of play solutions, focusing on how it may be more on the batters than the pitchers when it comes to speeding up the games. Well, I was pleased until the last paragraph, where he proposed the ol’ 15 second pitch clock – but we’ll get there.

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Pitching blisters were an afterthought just two years ago but the reported instances have jumped the past two seasons. Detailed accounts were written by Eno Sarris here at FanGraphs and Ben Lindbergh at the Ringer.

Throwing a curveball may be to blame according to Sarris:

But we can’t dismiss that chart completely. The players who have gone down with blister problems have thrown curves 14.9% of the time, far above the 10-11% baseball as a whole averaged over that timeframe. The players who ended up on the list more than once averaged 18.9% curveballs. Enough to say there’s some smoke here.

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It’s probably been awhile since you’ve read a traditional “buy low, sell high” article.  In today’s golden age of baseball analytics where complex physics and statistics can be boiled down to a few simple indicators accessed instantly using one hand, it’s not very often that we (readers, fans, fantasy players) find ourselves in possession of knowledge before the masses.  For example, try “selling” Avisail Garcia and his recent .375 wOBA around your league without getting some type of response that includes “yeah, but he had a .392 BABIP”.

Thankfully, despite all the data available at our fingertips, the one ingredient that will always play a critical role in the mixture of value is the human element of perception, which can swing wildly in different directions depending who you’re dealing with.  Today I’d like to isolate a few players who’s perception may be suppressing their actual value a little more than it should be, which may represent a buying opportunity for savvy fantasy owners prepping for 2018.  The good news is you don’t have to stand in line to land these deals, but you will still need to get them early.

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I’ve finally compiled the 2017 Disabled List (DL) information. The main change from the last few seasons is the transition from the 15-day DL to 10-day DL and the subsequent increase in DL trips. With the total trips up, the number of days lost is down which makes it tough to draw any major conclusions. It’s time to dive into the numbers.

First off, I collected the information from MLB.com’s transaction list. I like to use this list because it is easy to go back and check. I waded through it and it wasn’t pretty. It took me twice as long to compile the data compared to previous seasons. I would just like to give a big thank you to ProSportsTransactions.com for having most of the missing data.

With my venting out of the way, here is how the days missed for pitchers and hitters compare over the previous 4 seasons.

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The offseason begins with a decent bit of uncertainty in the closer’s role for many teams. The free agent and trade markets could shuffle a lot of 9th inning plans across the league for contenders and pretenders alike. Looking at the free agent market, I’ve identified four middle relievers who I think have a real shot at landing a closer gig this winter.

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Last offseason, I created an individual pitch metric, pERA, which gives each pitch an ERA and prospect grade based on its ground ball nature and swing-and-miss capability. With the 2017 season over, I’ve compiled the final 2017 values. This year, I’ve added in exit velocity (EV) grades for each pitch.

The process I used for creating pERA is in the article linked above but here is a quick rundown.

• The key change is to give each pitch an ERA value (pERA) based on the pitch’s swinging strike and groundball rate. All the values are based on the average values for starting pitchers. Closers will have higher grades because their stuff plays better coming out of the bullpen.
• The pitcher’s control is determined from their walk rate which is separate from the pitch grades.
• I’ve put each pitch on the 20-80 scale with 50 being average, 80 great, and 20 horrible. For starters, target pitchers with three average or better pitches. For relievers, they just need two pitches.

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Last week, I examined pitchers whose strikeout per nine (K/9) increased while the strikeout per plate appearance (K%) dropped. This article focuses on the pitchers who saw their strikeout rates go in the opposite directions. Besides the strikeout divergers, I’m going to include the walk rate divergers since both player sets aren’t long.

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The season seems to never end for fantasy baseball writers. Once the regular season is over, it’s time to begin writing player previews for the next season. Pitchers who’ve had their strikeout (K% and K/9) and walk rates change in different directions spin me for a loop. Now, I query these schizophrenic pitchers to start the preseason previews. I’ll give a quick look at some of these pitchers. I’ll start with those pitchers who’ve seen their K% (strikeout per batter faced) drop while K/9 (strikeouts per nine innings) increase.

Two reasons exist for why the rates diverge. The key for both is increasing the number of plate appearances per innings. More plate appearances lead to their K% dropping if the strikeouts remain constant per inning. The other factor is how many hits a pitcher allows (basically BABIP). If a pitcher had good luck on balls in play and recorded more outs, they could quickly get through an inning and thereby raise their K%. Once the BABIP normalizes, the K% will drop.
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While 2017 was the year of the dinger, it also looks like it was the year of velocity. Has baseball changed (both the sport, and the physical ball itself)? The signs point to yes – but on the pitching from, the importance of velocity has never been higher. Exhibit A:

The slowest fastball the @Yankees threw tonight was 96 MPH… That is completely absurd.

— Daren Willman (@darenw) October 10, 2017

That’s not average. That’s not maximum. That’s … the slowest. Let’s borrow a little bit of math from the documentary “Fastball” to just put into context how crazy this is.

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