Archive for Meta Analysis

Pitch Sequencing and Pitcher xBB%: We’re Getting There

I expected to follow up my xK% differential post from last week with a complementary xBB% differential post. For those who don’t enjoy surprises, I’ll let you know now that that didn’t happen. In its stead, I bring what I hope is good news — news that will not only influence a future xBB% differential post but also may impact general pitcher analysis henceforth and possibly international diplomacy.

The title of this post, however, is a tad misleading. I think I can say, with some degree of certainty — and I hope to demonstrate, with some degree of competency — that pitch sequencing indeed plays a role in a pitcher’s walk rate, as the devilishly handsome Mike Podhorzer has postulated. What I can’t describe, with any degree of certainty, is the magnitude of the role it plays. In truth, I desperately want to prove Mike wrong: there must be other factors, outside of pitch sequencing (and pitch framing, perhaps), that help explain a pitcher’s walk rate. For example, I have tried incorporating O-Swing% and Zone%, two PITCHf/x metrics provided by FanGraphs that I swore would fill in the cracks, but they offer little in the way of additional explanatory power.

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The Starting Pitchers that Baffle the Rankers: Outside the Top 100

Yesterday, I discussed some of the starting pitchers ranked inside the top 100 who us rankers most disagreed on. Though it was suggested that a better comparison would be solely between ranks within the position and not overall, I’m not sure that matters since it’s all relative. If one ranker devalues pitchers (Jeff), then all his pitchers will be ranked lower, so it’s moot.

Here is a selection of starting pitchers ranked outside the top 100 who we greatly disagree about.

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The Starting Pitchers that Baffle the Rankers: The Top 100

Last week, I discussed which hitters us rankers most disagreed on based on our consensus top 300. Today I move on to the starting pitchers. Keep in mind that innings pitched plays a major role in valuations. Aside from the boost in both wins and strikeouts that come with more innings, the ratios have more of an effect. For example, an $8.16 Michael Pineda in 155 innings is worth $15.49 in 200 innings! Now it’s on to the head-scratchers.

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The Long Bad Buy

Our long National League nightmare is over. Two and a half weeks and 750 draft picks after it began, the NFBC slow draft is done. Though we used it primarily as preparation for our NFBC Main Event draft in April, we weren’t opposed to success, though it may seem that way when you review what we did.

Our draft can be described, accurately and justly, as “high-risk, high-reward.” It can also be described, with equal accuracy and justice, as “feeble.” Laugh and weep with us as we explain what we were planning to do, what we thought we were doing, and what we actually did. And that’s right, wise guys, it was in fact a mixed-league draft, but we liked our opening line too much to jettison it.

Our strategy going in to the draft was animated by several insights, or, if you prefer, delusions. They were:

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Hitter Analytics (2/22/15)

Last Friday, I wrote about some ways I plan on investigating a deeper into hitters. Here is the first weekly column on the information. I will pulish the data on Sunday night to help with setting weekly leagues. The format and information are not close to being 100%, so expect some changes for a few weeks as I iron out a few wrinkles.

Pitchers’ Approach Attacking Hitters

Robert Arthur at Baseball Prospectus has shown pitchers will change their approach depending on the hitter’s talent level. Here is a complete list of the number of fastballs (including sinkers) thrown to each hitter of the past two years divided into half seasons.  Also the number of pitches in the strike by half season is included along with the fastball percentage in the strike zone.  I will begin adding 2015 information as it becomes available.

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Taking Hitter Analysis to Another Level

Truthfully, I have had it. Here at RotoGraphs we are almost too good at identifying emerging pitchers. We can decently find up-and-coming pitchers with Arsenal Score being the last great accomplishment. Additionally, I am also to blame by looking at how pitchers change and determining if they may be injury prone (example with Scott Kazmir). Most of the advancements in examining pitchers is because of the addition of Pitchf/x data. We know immediately if a pitcher is throwing slower or if he has a new pitch. I feel hitters have taken a back seat for a few years and I would like to try to increase our knowledge of them. I plan on expanding into new areas for batters. Also, I am completely open to new ideas from our readers.

One of the biggest issues with hitters is it tough to know if/when they have changed. The difference may involve power, foot speed, swing adjustments or how pitchers are adjusting to the hitter. I want to take hitter analysis to the next level. I will attempt to live on the “tip of the spear”. The problem with living on the tip is I will probably get cut a few times. I am going to look at some never published data and see if it is useful/predictive. I could see several of my ideas not working out.

Finally before I get into some of my ideas, I will gladly welcome any of your ideas. It can be tweak to something I bring up or a completely new idea. I am ready to give hitters their fair shake.

Idea 1 – Use Pitchf/x Data To See How Pitchers Are Attacking Hitters Read the rest of this entry »

The Hitters that Baffle the Rankers: Outside The Top 100

Yesterday, I investigated our top 300 consensus rankings and discussed hitters in our top 100 with the most disagreement between us rankers. Today I jump outside that top 100 to identify those we disagree with most among the rest of the hitters.

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xK%, History and Speculating on Dellin Betances

Hi, everyone. You probably don’t recognize my name, as you shouldn’t, and that’s fine. I’m new here. I don’t have the credentials to certify that I’m an established fantasy baseball analyst (yet), nor am I related to Wilt Chamberlain (yet). But I do have a handful of things going for me, some of which I outlined for the very kind Dave Cameron under the “Certifications, Achievements and Immensely Useless Trivia” section of my resume when applying to write for FanGraphs:
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Could the Strike Zone Change?

We’re living through an era where pitching is king. Nobody disputes it. A number of reasons have been cited. Velocities are increasing due to better training. Teams and players better understand the relationship between strikeouts, walks, and success.
One cause may stand above them all, the strike zone has grown in recent seasons. The zone has increased by 40 square inches in the last five years, according to Jon Roegele. The growth is in one direction, down. As this becomes common knowledge, the league may discover a simple solution to inject more offense into the game – shrink the strike zone. Read the rest of this entry »

The Hitters that Baffle the Rankers: The Top 100

Yesterday, we published our consensus top 300 players, including the breakdown between the five rankers. Naturally, there are some players with more disagreement between us than others. So I decided I would investigate those very players. I calculated the standard deviation of the five rankings and sorted. Unfortunately, players lower in the rankings will almost always have higher standard deviations, even though the difference between a rank of 180 and 220 is much smaller than 1 and 15. As such, I split the group into those inside the top 100 and those outside. What follows is a selection of hitters ranked within the top 100 whose rankings are all over the map.

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