Think Blue Crew

I was kindly offered by Dave Cameron to write for FanGraphs after I submitted two articles to their Community Blog. My first post is up, which is a variation of my post on Rivera's cutters based on the count situation a few weeks ago. Check it out!

Here's a quick look at the contact zones of yesterday's swing-happy hitters, Vladimir Guerrero, Delmon Young, and Jeff Francoeur. Links to plots of their swing zones are right before each picture.

Against fastballs, swing zones vs. contact zones:

In the past few years, the batters who have been among the league leaders in Swing% (percentage of pitches swung at) are the same names every year. Since 2008, Vladimir Guerrero has led baseball in Swing% by swinging at 60.4% of all pitches. Delmon Young is second with 60% while Jeff Francoeur is third with 57.90%.

Let's take a look at the 50% swing zones of each of these hitters by pitch type. First up, fastballs:

Kensai over at Memories Of Kevin Malone had a fantastic and exhaustive post on the struggles of Matt Kemp this season. If you haven't read it yet, go read it right now before you continue this post.

A very short Cliff Notes version. Basically, Matt Kemp has been struggling this season, and even if you account for the low BABIP, he is still striking out at a higher rate this season compared to last. What also confounded me that even though he has a higher strikeout rate, he is also setting a career high in walk rate as well. Usually, drawing walks and getting struck out are thought of as tradeoffs, opposite ends of the "patience scale." Kensai also had a meticulous look at the changes in Kemp's swinging mechanics, and he did find a change that hopefully the Dodgers are aware of.

I would like to extend on Kensai's post using PITCHf/x. There are two areas I'd like to investigate: 1) Is Kemp swinging at more strikes in 2010 compared to 2009 and how? and 2) Is Kemp making less contact in 2010 compared to 2009 and how?

To answer these two questions, I'd like to look at Kemp against all fastballs (four-seamers, two-seamers, cutters, and splitters) and against all breaking balls (curveballs, sliders, and changeups). Let's get started with a table of Matt Kemp's plate discipline and swing outcome rates in 2009 vs. that of 2010, broken down between fastballs and breaking balls and by pitcher's handedness:

I've talked about Mariano Rivera and his cutter in the past, but it's always interesting to analyze what I consider to be the greatest pitch in the game. I don't believe that there is any other pitch in the game right now that can be used so exclusively yet so dominantly the way that Rivera uses his cutter.

We know that Rivera has pinpoint control and likes to work the outer and inner edges of the strikezone against both right-handed batters and left-handed batters. We also know that Rivera is great at working the count, rarely getting to 3 balls in a count. Combining both of these ideas, can we figure out how Rivera works the count based on the locations of his cutters?

To do this, let's first look at Rivera's cutters by each count since 2007:

You learn something new every day, and I must confess, as someone who first dabbed his feet in PITCHf/x less than a month ago, I was very excited to get my hands dirty with this data, plotting it, and analyzing it and such. I have talked about a few of the mistakes I've made in the past with some of my plots and models, and I do want to learn from my mistakes from my analysis of the corrected plots as well. I've been referring to Mike Fast's article here from time to time to understand the possible rookie mistakes a PITCHf/x analyst can make. Needless to say, it's been very helpful and definitely should keep me accountable in the future.

Which brings me to this post about Cliff Lee. Various sources (I looked at several articles, Fangraphs, and yes, Wikipedia) tell me that Lee throws five different pitches, armed with a four-seam fastball, a two-seam fastball, a cutter, a changeup, and a curveball. Plenty of past articles have detailed the faultiness and/or suggested better reclassification techniques of MLBAM's pitch type classification where all of the great PITCHf/x data comes from. I would preface this and my future posts with the knowledge that I will use MLBAM's pitch classification for now, as developing my own algorithm to determine a better classification seems like a time-consuming and daunting task to say the least.

But before I dive into plots of Cliff Lee's pitches, I need to look at his pitch types first according to MLBAM. Here's a list of the frequency of his pitches by handedness since 2007, according to MLBAM's classification and my database:

A few weeks ago, I took a first look at Mariano Rivera's cutters, and saw that Rivera locates his cutters so accurately and so effectively by painting the left and right edges of the strikezone without hitting the middle much. To recall what these scatter plots looked like, check this out.

Now I've learned quite a lot of interesting things since then, including a technique called kernel density estimation, a simple method to estimate the frequency/density of x,y coordinates. I wanted to take a look at Rivera's cutters again, this time in the form of pretty plots.

I've used hexagonal binning methods before to show Rivera's pitch movement plots, as well as filled contour loess regression plots for other players. Here's some plots of Rivera's cutters against RHH and LHH using bivariate kernel density estimation, a catalog of various colorful schemes:

There is an awesome leaderboard over at Fangraphs.com where you can check out the best (and worst) hitters by pitch type. What stats like 'wFB,' 'wSL,' and 'wCB' do is that they calculate the number of runs scored above average a hitter attained against that particular pitch. The wFB/C and wSL/C stats look at runs above average per 100 pitches, so wFB/C would be looking at runs above average per 100 fastballs.

If you look at the leaderboard for the past three seasons combined, Albert Pujols, Kevin Youkilis, and Mark Teixeira come out on top as the best fastball hitters in the MLB. In the past three years, Pujols gained 121.6 runs above average against the fastball, while Youkilis and Teixeira gained 99.8 and 94.1 runs above average respectively.

A look at heat maps of run value against the fastball would give the best look at how these hitters fared against the heat. However, I wanted to create plots showing a measure that most readers will understand intuitively. Let's take a look at Pujols, Youkilis, and Teixeira in contact percentage against fastballs (percentage of fastballs they swung and made contact off of):

Jeff Zimmerman over at Fangraphs had an interesting post about the expansion of the strikezone as the season goes on. He mentions that there may be evidence to bolster David Ortiz's claim that umpires are calling more strikes and less balls as the season goes on.

I wanted to see this for myself using my own method, so I created a called strike probability model for April 2008 vs. August 2008, April 2009 vs. August 2009, and April 2010 vs. August 2010. What I did was I pulled all called strikes and balls (ignoring all the times when the batter swings) within half a foot from the rule book strikezone, half a foot inside and half a foot outside. I then modeled a surface fit for all called strikes over pitches where the batter didn't swing. I assumed that the middle of the inner 0.5 foot border returned called strikes 100% of the time if the model did not project that far inward, and same with balls way outside the strikezone.

Let's take a look at called strikes in April 2008 vs. August 2008 to see if umpires called more strikes as the season went on in the past, where red indicates called strikes and blue indicates balls (blue balls, snicker). Note that I split the strikezone into nine equal-sized boxes for reference, while the outer border is the approximate rule book strikezone:

I submitted my Mark Reynolds post yesterday to Fangraphs' community blog... and they accepted! Needless to say, I'm getting some site traffic from Fangraphs now, and I thought I'd share some plots of the other prodigious power hitter who strikes out a ton. Let's take a look at Ryan Howard, Mark Reynolds' left-handed counterpart, only 40 pounds heavier.

Ryan Howard has been either second or third in the entire MLB in swinging strike percentage and other strikeout categories since Mark Reynolds' debut in 2007. Fangraphs' stats tell us that Howard has swung and missed on 14.6% of pitches so far in 2010 while posting a swinging strike percentage consistently above 15% in the previous three seasons. Like Reynolds, Howard doesn't actually swing at everything compared to other swing-happy batters, swinging at less than 50% of pitches every season for his career.

Again, I'm going to leave out cutters and just look at four-seam fastballs, sliders, curveballs, and changeups due to sample size. Let's look at four-seam fastballs (987 pitches from RHP, 649 pitches from LHP):