Author Archive

The Difference Pitching on the Edge Makes

Note: I found some errors in the data. Data below has been corrected, as well as some conclusions — BP

Yesterday, Jeff Zimmerman examined how Tim Lincecum’s performance has depended to some extent on his ability to pitch to the edges of the plate. Last year, Lincecum was one of the worst starters in the game in terms of the percentage of his pitches thrown to the black. Coincidently (or not so coincidently), Lincecum suffered through his worst season as a professional.

As with many things, Jeff and I happened to be investigating this issue of the edge simultaneously. Of course, we were not the first to dabble in this area. Back in 2009, Dave Allen noted that differences in pitch location–specifically horizontal location–led to differences in BABIP.

Like Dave, I was curious about the overall impact that throwing to the edges–or the black–has on overall performance. My thinking about pitchers throwing to the edges naturally led to some hypotheses:

  1. Throwing a higher percentage of pitches on the edges leads to lower FIP.
  2. Throwing a higher percentage of pitches on the edges leads to lower ERA.
  3. Throwing a higher percentage of pitches on the edges leads to lower BABIP.
  4. Throwing a higher percentage of pitches on the edges is associated with lower four-seam fastball velocity.

I think the first three hypotheses are intuitive, but the last one stems from the idea that as a pitcher ages and loses zip on their fastball they cannot remain successful unless they increase their avoidance of the heart of the strike zone.

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Offensive Volatility and Beating Win Expectancy

Armed with a new measure for offensive volatility (VOL), I wanted to revisit research I conducted  last year about the value of a consistent offense.

In general, the literature has suggested if you’re comparing two similar offenses, the more consistent offense is preferable throughout the season. The reason has to do with the potential advantages a team can gain when they don’t “waste runs” in blow-out victories. The more evenly a team can distribute their runs, the better than chances of winning more games.

I decided to take my new volatility (VOL) metric and apply it to team-level offense to see if it conformed to this general consensus*.

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(Re) Introducing Hitter Volatility

I suspect many researchers and writers have their own white whale or unicorn; an idea or concept that they are always chasing, regardless of how fruitless or costly that search may ultimately be.

My unicorn is the concept of volatility. I spent a large part of my tenure at Beyond the Box Score exploring the topic for both hitters and pitchers. I even looked at the concept in relation to team performance earlier this year at FanGraphs and other outlets.

Essentially, the idea is to understand whether there are appreciable differences in how players distribute their daily performances over the course of a season. For example, if you have two hitters that are roughly equal in terms of overall skill (i.e. both are 25% better offensively than the league average) is there a difference in terms of how much each is likely to vary from their overall performance on a game to game basis? Is one hitter more consistent day in and day out, while the other mixes in phenomenal performances with countless 0-4 days?

My initial work had some problematic issues (as most initial work does), but thanks to some great feedback from readers and colleagues alike I am ready to roll out the new and improved version of Volatility (VOL), starting with hitters.

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Optimizing Batting Orders Across MLB

Of the many topics discussed in The Book is lineup optimization; essentially, the degree to which teams can extract extra runs throughout a season through better lineup construction.

The general consensus seems to be teams don’t do a great job at optimizing lineups. But the gains from proper optimization aren’t that great, anyway.

That being said, I was curious whether there’s evidence for league-wide changes in the ways players are deployed throughout lineups. Given the statistical research in the past few decades, is the league any more in line with setting lineups with the expressed idea of simply avoid outs?

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David Wright Deal a Solid Bet for Mets

Multiple sources are reporting that David Wright and the New York Mets have reached agreement on a contract extension that essentially makes the third baseman a Met for life.

Initial reports have the deal at 7 years/$122 million. This is on top of next year’s $16 million team option, taking the total years and value of the contract  to 8/$138.

It always pays to be skeptical of long-term deals for players on the wrong side of 30, simply because we know — on average — that performance only declines from this point on.

Let’s take a look at how this might play out for the club.

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When You Really Need a Fly Ball

It’s the bottom of the eighth inning. Men are on first and third base, there’s one out and your team is down by one run. The opposing team has one of the best ground-ball pitchers on the hill, and the infield is playing back and is looking for a double play. All you need is a fly ball to tie the game and significantly swing your chances of winning.

So who do you want at the plate?

It’s likely that the opposing manager will either bring in a ground-ball specialist or just tell the pitcher to stay away from pitches that could be hit in the air to the outfield. Knowing who you’d want to hit requires an understanding of what pitches are the most likely to induce a ground ball — and what hitters manage to hit fly balls against those pitches most often.

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The Most Backward Starters in MLB

So much of what makes pitchers effective at the major league level is their ability to keep hitters off-balance. Sure, a 95 mph fastball with movement and a Lord Charles curveball help, but even these physical tools are only as effective as a pitcher’s ability to create uncertainly in the hitters mind from pitch to pitch.

One — admittedly crude — way of looking at this is whether a pitcher throws the type of pitch that’s expected in a given count. Does a pitcher throw fastballs in “fastball counts”, or do they throw off-speed pitches? Pitchers that throw counter to expectations are often said to “pitch backwards”. The Rays’ James Shields is someone that has been referenced as such a pitcher over the past few years.

But exactly how backwards does Shields pitch? And who are some other pitchers that fit into this category?

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David Wright: Swinging Off — But Near — the Black

David Wright experienced a resurgence of sorts in 2012. After four straight outstanding offense seasons, Wright’s offensive production dipped significantly in 2009 — from a 141 wRC+ to 125. In 2011, Wright’s wRC+ declined all the way to 116.

But this year, the old David Wright reappeared and the 29-year-old third basemen posted a 140 wRC+. The Mets, encouraged by Wright’s year at the plate, have not only picked up his 2013 option (which was predictable), but have also continued discussions for a long-term contract extension.

How likely we are to see Wright put up similar numbers in the future is debatable.

Regardless, one thing was clear: Wright was making better decisions at the plate in 2012. And while his plate discipline numbers were positive (e.g. -2.1% O-Swing), the overall change didn’t seem to capture how well Wright’s plate approach improved.

In an effort to tease this out beyond the basic plate discipline metrics, R. J. Anderson used Mike Fast’s “correct” decision-making approach to look at how Wright’s decision-making improved in the past three season. Anderson calculated the percentage of “correct” pitches Wright swung at in 2012, compared to the two previous seasons. He found Wright had improved his decision-making by 7%.

I decided to take an even narrower view than Anderson and focused only on the location of balls Wright swung at that were just off of the plate, or that were off the black.

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Velocity Trends and Pitchers to Watch in 2013

I’ve written quite a bit this year about pitcher aging — specifically, trends in velocity loss for pitchers. There are two general findings that I want to revisit today and apply to pitchers from 2012; the predictive power of velocity loss in July and end of season velocity, and the impact of losing velocity in one season on next season’s velocity.

First, a pitcher’s velocity will tend to vary throughout the year. Trying to get a read on whether a pitcher is having trouble velocity-wise during a season is difficult if you simply compare to last year’s overall velocity. So I compared a pitcher’s velocity in each month to their velocity the previous year in that same month and found that pitchers who lose at least 1 mph of velocity in July are 13.7 times more likely to finish the entire year down at least 1 mph.

Second, 91% of pitchers that do finish a season down at least 1 mph compared to the previous season will lose additional velocity the following season (average decline of 1.6 mph), with only 7% regaining some (but, likely, not all) of that velocity back.

With the close of the 2012 season, I checked back on how well July-over-July velocity trends predicted full season declines as well as which pitchers ended the season losing over 1 mph off of their fastball.

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Pitching Inside: The Best of 2012

One of the oldest truisms in baseball is that, to be successful, pitchers need to pitch inside. Establishing the inside of the plate allows pitchers to more effectively use the outer-half of the plate — and get batters to swing and miss or make weak contact more often on pitches thrown to the outer part of the zone. But it isn’t easy to pitch inside. Pitchers who lack the ability to get away with throwing inside tend to stay away from that part of the plate for fear that hitters will drive those pitches for extra-base hits. This can lead to hitters cheating on outside pitches and can force pitchers to throw fatter pitches as a result of throwing behind in the count.

So who were this year’s best pitchers when it came to throwing inside? I dove into our PITCHf/x data and found out.

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