Author Archive

Introducing the Interactive Spray Chart Tool

I’ve been working on an interactive tool that allows you to create spray charts using Game Day data from the past two years for a few weeks now. I’ve always loved the Katron Batted Ball tool, and it’s been a great resource of mine for years. However, I wanted to put something together that was a bit more interactive, allowed for more filtering, and made side-by-side comparisons easier.

Our writers here at FanGraphs have been kind enough to play around with it and offer suggestions. After some tweaks I am ready to officially release the tool into the wild so that anyone can use it.

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Matt Moore and Others Likely to Lose Velocity

As some of you might remember from previous articles, velocity trends in July provide the strongest signal in terms of whether a pitcher is likely to experience “true” velocity loss over the course of a full season.

Yes, I know, we are more than halfway through August. However, between work, vacation, and Saber Seminar (which, if you didn’t attend you really missed out. You can still purchase posters and t-shirts, so get on that. It’s for a good cause) I’ve struggled to sit down and run the numbers. Better late than never.

Again, for reference, the table below breaks out the percent of pitchers who experience at least a 1 mph drop in their four-seam fastball velocity in a month relative to that same month a year ago and who also went on to finish the season down a full 1 mph. It also shows the relative risk and odds ratios for each month — meaning, the increased likelihood (or odds) that a pitcher will experience a true velocity loss at season’s end when compared to those pitchers that didn’t lose 1 mph in that month.

Month 1 mph Drop No 1 mph Drop Relative Risk Odds Ratios
April 38% 9% 4.2 6.2
May 47% 6% 7.8 13.9
June 55% 5% 11 23.2
July 56% 4% 14 30.6
August 53% 6% 8.8 17.7

So while the overall rate of velocity loss based on a loss in June and July look pretty even, the relative risk and odds ratios increase by a solid amount in July.

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More on Called Strikes on the Edge

When we last left our discussion of Edge% we were looking at the differences in the rate of called strikes based on the count. Generally speaking, umpires were less likely to call strikes on the Edge in pitcher-friendly counts and more likely to give those calls in hitter-friendly counts.

While we learned a bit from that analysis, it was really just the tip of the iceberg. There are a number of additional ways to cut the data, and that is the focus of this article. Count is just one dimension when we are thinking about what might influence the likelihood of close called strikes. There are a number of additional dimensions we can layer onto count, and that’s precisely what I show in the (admittedly large) table below.

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Getting Strikes on the Edge

The last time I wrote about Edge% it was in the context of the Tampa Bay Rays using it to get their pitchers into more favorable counts on 1-1. But now I want to take that topic and drill a little deeper to understand how often edge pitches are taken for called strikes.

Overall, pitches taken on the edge are called strikes 69% of the time. But that aggregate measure hides some pretty substantial differences. Going further on that idea, I wanted to see how the count impacts the likelihood of a pitch on the edge being called a strike.

Here are the results:

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Velocity Decline Trends for June, 2012-13

Well friends, we are now approaching that time of year where a significant drop in a pitcher’s velocity passes the 50% threshold in terms of signaling that they will finish the year down at least one full mph.

Month 1 mph Drop No 1 mph Drop Relative Risk
April 38% 9% 4.2
May 47% 6% 7.8
June 55% 5% 11.0
July 56% 4% 14.0
August 53% 6% 8.8

The table above breaks out the percent of pitchers who experience at least a 1 mph drop in their four-seam fastball velocity in a month relative to that same month a year ago and who also went on to finish the season down a full 1 mph. It also shows the relative risk — meaning, the increased likelihood that a pitcher will experience a true velocity loss at season’s end when compared to those pitchers that didn’t lose 1 mph in that month.

For example, pitchers that lost velocity in May finished the season down a full 1 mph 47% of the time, compared to just 6% that didn’t lose 1 mph in May — an increased likelihood of 7.8.

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Putting Hitters Away with Heat

In his Major League debut for the Mets, 23-year-old Zack Wheeler struck out seven hitters in his six innings of work. Of those seven strikeouts, six came on fastballs — and of those six, four came on whiffs induced by fastballs.

This got me wondering, what pitchers this year have generated the largest percentage of their strikeouts off of their fastball? And how many generated those strike outs on swings and misses on fastballs*?

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Hitter Volatility Through Mid-June

Last year I reintroduced VOL, a custom metric that attempts to measure the relative volatility of a hitter’s day to day performance. It is far from a perfect metric, but at the moment it’s what we have.

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Velocity Trends Through May

We are a little more than two months into the season, and that means it’s time to check on early season velocity trends. As I’ve mentioned before, declines in velocity are a less reliable signal in April and May than in June and July, but nevertheless large declines can still be a solid predictor that a pitcher’s velocity has in fact truly declined and will remain lower at season’s end. Almost 40% of pitchers that experience a decline in April — and almost 50% in May — will finish the season down at least 1 mph. And while the signal gets much stronger in July, 40% is still a pretty sizable number.

So let’s take a quick look at the major decliners from April and May.

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Reliever Pitching Metric Correlations, Year-to-Year

A little over a year ago I published the results of a study that examined which metrics were most consistent on a year-to-year basis for starting pitchers. My colleague, Matt Klaassen, followed up and expanded on that study recently here at FanGraphs. Matt’s study also focused on starting pitchers–those with a minimum of 140 innings pitched in consecutive years.

Recently I was asked the following on Twitter:

I can’t speak specifically to what the common wisdom is Justin is referring to, but I can certainly run the correlations for relief pitchers and compare them to what I found for starters.

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How the Rays Leverage the Edge

In Sports Illustrated’s 2013 baseball preview, Tom Verducci wrote a great profile of the Tampa Bay Rays and their approach to optimizing the performance of their pitching staff.

One topic that was especially interesting to me was the apparent importance the Rays place on the 1-1 count. Verducci recounts how pitching coach Jim Hickey described the organization’s focus on getting opposing batters into 1-2 counts:

The Rays believe no pitch changes the course of that at bat more than the 1-and-1 delivery. “It’s almost a 200-point swing in on-base percentage with one ball and two strikes as opposed to two balls and one strike,” Hickey told the pitchers.

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