FanGraphs Baseball

ERA/FIP Visualization Tool

I’ve made an interactive visualization tool for earned run average (ERA) and fielding independent pitching (FIP) across Major League Baseball. You’ve seen this visualization before in many of Owen Watson’s articles throughout last season. Owen used this to suggest which pitching staffs might have overachieved their peripheral stats. This visualization lets us see the discrepancies between ERA and FIP among all of the MLB teams or even among different players.

Below is an example of a graph are you able to create with the tool:

You can toggle between teams and players. Players are organized by team and you are able to set the minimum number of innings pitched for the player to be on the graph. There are two places you’ll see these graphs. The primary location will be the tool’s page on FanGraphs; this is where the full tool is available. Then the graph itself can be embedded into our blog (plus Community Research) or anyone else’s blog using an iframe element.

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Howie Kendrick, Jean Segura, and Arizona’s Latest Mistake

Over the weekend, the Dodgers and Diamondbacks made a pair of related transactions. On Friday night, after failing to find a suitor due to the specter of a potential lost draft choice, Howie Kendrick re-signed with the Dodgers for a relative pittance; $20 million over the next two years. Given that Kendrick turned down the qualifying offer, which would have guaranteed him $15.8 million for just the 2016 season alone, Kendrick had to settle for far less than he thought he would get this off-season, and at that price, the Dodgers decided the value was too good to pass up, even though they didn’t really need another infielder.

Kendrick is better than Chase Utley and he should make the team better in both 2016 and 2017; however, they did surrender the possibility of obtaining a compensation pick if another team had eventually decided he was too good to pass up at that price as well.

For a good chunk of the winter, the assumption was that a team would make that choice, and for the last few months, the Dimaondbacks looked liked the obvious fit. General manager Dave Stewart publicly talked about his desire to add some offense at the top of the order to replace Ender Inciarte, and some combination of Chris Owings and Aaron Hill didn’t inspire a lot of confidence that second base was going to be well-handled in 2016. The D-Backs had talks with Kendrick, and had tried to trade for Brandon Phillips, so it was clear that they wanted to make a move for a more established second baseman, pushing Owings into the utility role that he’s probably better suited for.

But, after having surrendered the 13th pick to sign Zack Greinke, the Diamondbacks became fiercely protective of the 39th overall pick, a competitive-balance selection they were awarded that they would have to surrender if they signed Kendrick (or Ian Desmond, another free agent would could have helped them). Stewart even stated outright that they weren’t going to give up that pick:

“We’re not going to give up the pick,” Stewart said of the D-backs, who have the 39th selection (Competitive Balance Round A). “It’s just tough after we’ve already given up our first pick. To give up our top two picks, that would be difficult for us to do.”

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Dan Szymborski FanGraphs Chat – 2/1/16

11:58
Dan Szymborski: And so it begins.

11:59
Dan Szymborski: OH GOD THERES NO QUESTION QUEUE I’M SCARED

11:59
Matt: How was your weekend?

11:59
Dan Szymborski: Sleepy. I ate way too many cookies Friday.

11:59
The Dude of NY: Why does ZiPS project K/9 rather than K%?

12:00
Dan Szymborski: ZiPS doesn’t explicitly project K/9 or K%. Probably easier for Cistulli to calculate since I don’t give him TBF in the base readout.

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Miguel Sano’s Other Elite Skill

Miguel Sano didn’t exactly sneak up on the league. The massive 22-year-old Dominican slugger had been considered a top-100 overall prospect in baseball for each of the last six seasons, a top-20 overall prospect each of the last four. He’d have been a perennial No. 1 prospect for most any organization in baseball, if not for the presence of super-prospect Byron Buxton. In the prospect world, Sano played Pippen to Buxton’s Jordan.

Last season, they both arrived. And for Sano, the debut couldn’t have gone much better. Sano batted 335 times in his rookie season. Set the playing time minimum low enough, to include Sano on our leaderboards, and he was a top-10 hitter in baseball. Immediately, Sano thrust himself into the company of Giancarlo Stanton, Jose Bautista, Edwin Encarnacion and Chris Davis, not only as one of the game’s premier power hitters, but as one of the most dangerous all-around at-bats in the league.

Pitchers who had faced Sano in the minor leagues already knew what to expect. Pitchers who hadn’t faced Sano before quickly learned what to expect. The most simple scouting report goes like this: true 80-grade power, the kind of power that necessitates lofty comparisons with Stanton. Proceed with caution.

And that’s exactly what pitchers did. A reputation as a feared hitter is the kind of thing most guys have to earn. Bautista, Davis, Encarnacion: they had to earn their reputations as truly premier power hitters, as the most dangerous at-bats in the game. It wasn’t simply assumed. Sano? Sano arrived with that reputation.

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Projecting the Prospects in the Dickerson/McGee Trade

In something of a curious trade, the Rockies flipped Corey Dickerson to the Rays for Jake McGee. Those two players were the headliners of the deal, but they weren’t the only two players involved. Also changing hands were third baseman Kevin Padlo and hard-throwing righty German Marquez, who head to the Rays and Rockies, respectively. Here’s what my fancy computer math says about the minor leaguers involved.

Kevin Padlo (Profile)

The Rockies drafted Padlo in the fifth round out of high school less than two years ago, but he wasted no time putting up gaudy numbers in the low minors. Padlo graded out extremely well by an embryonic version of KATOH and, nearly a year and a half later, his enticing combination of power, speed and youth still tips the scales. He placed 37th on KATOH’s newly-minted prospect list, with a projected 5.9 WAR through his first six years in the show.

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2016 ZiPS Projections – Oakland Athletics

After having typically appeared in the very hallowed pages of Baseball Think Factory, Dan Szymborski’s ZiPS projections have been released at FanGraphs the past couple years. The exercise continues this offseason. Below are the projections for the Oakland Athletics. Szymborski can be found at ESPN and on Twitter at @DSzymborski.

Other Projections: Arizona / Atlanta / Baltimore / Boston / Chicago AL / Chicago NL / Cincinnati / Cleveland / Detroit / Houston / Kansas City / Los Angeles NL / Minnesota / New York AL / New York NL / Philadelphia / Pittsburgh / St. Louis / San Diego / San Francisco / Seattle / Texas / Toronto / Washington.

Batters
There’s always the sense, given the organization’s record of innovation and willingness to reconstruct its roster, that the A’s are likely to succeed then most when mediocrity appears to be the only possible outcome. If that sense is correct, then Oakland is likely to succeed very hard in 2016 — because the club, as presently constructed, is not well-acquitted by the projections.

Consider the following table, a version of which appears in the glossary entry for WAR and which provides a rough characterization for various WAR ranges:

WAR Figures in Context
Category WAR
Scrub 0-1
Role Player 1-2
Solid Starter 2-3
Good Player 3-4
All-Star 4-5
Superstar 5-6
MVP 6+

By this rough taxonomy, Oakland currently employs only two batters classified as “solid starters” (Josh Reddick, Marcus Semien) and a third (Billy Burns) who profiles as precisely average. That triumvirate represents the exact sort of cost-controlled core a team like Oakland requires to win. Unfortunately, they’re surrounded not by stars, but role players.

It’s difficult, while examining the modest projections here, not also to consider for a moment the distinctly less modest one produced by ZiPS for Josh Donaldson. Last year’s American League MVP is expected to record more than six wins in 2016, at the cost of about $11.5 million. One needn’t be employed — or even have any training — as a rocket scientist to recognize what a benefit Donaldson would be to this club.

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FanGraphs Audio: Jeff Sullivan Bares Some!

Episode 628
Jeff Sullivan is a senior editor at FanGraphs. He’s also the live-in-person guest on this edition of FanGraphs Audio.

This edition of the program is sponsored by Draft, the first truly mobile fantasy sports app. Compete directly against idiot host Carson Cistulli by clicking here.

Don’t hesitate to direct pod-related correspondence to @cistulli on Twitter.

You can subscribe to the podcast via iTunes or other feeder things.

Audio after the jump. (Approximately 1 hr 31 min play time.)

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01:30:47

Job Posting: New York Mets Analyst, Baseball Research & Development

Position: New York Mets Analyst, Baseball Research & Development

Location: New York

Description:
The New York Mets are seeking a Data Analyst to work its Research and Development team. The employee will analyze baseball data in order to build and maintain predictive models that support the decision-making processes within Baseball Operations. The Analyst will report to the Manager, Baseball Research and Development.

Responsibilities:

  • Research, develop, and test predictive models to support Baseball Operations (ie, player evaluation, roster construction, player development, in-game decision making).
  • Assist development team to create and integrate new analysis and tools into existing Baseball Operations application.
  • Collaborate with members of Research and Development team to maintain long term information and systems architecture for Baseball Operations.
  • Write scripts which support data collection, automation, and report generation.
  • Interface with Baseball Operations leadership on player evaluation, in-game strategy, and transactions by presenting the results of analysis in a clear, understandable fashion using a variety of methods.
  • Keep Baseball Operations staff abreast of cutting edge statistical techniques.

Qualifications:

  • Advanced degree or equivalent experience in Statistics, Data Science, Operations research, Mathematics, Computer Science, or related quantitative field.
  • Demonstrated experience with statistical tools and packages, such as R, STATA, Julia, SPSS, or SAS.
  • Familiarity with SQL query design and optimization.
  • Strong understanding of baseball specific datasets (ie, Pitch Fx, Trackman, Statcast) & knowledge of current baseball research.
  • Ability to effectively communicate complex concepts to a non-technical audience.

To Apply:
Interested applicants should apply here by Sunday, February 7th.


Sunday Notes: Christin, Chi Chi, Collins’ Decision, Reliever Value, more

Christin Stewart is the top power-hitting prospect in the Detroit Tigers system. He aspires to be the best overall hitter.

The 22-year-old outfielder got off on the right foot after being drafted 34th-overall last summer out of the University of Tennessee. Swinging from the left side, the muscular slugger slashed ..285/.372/.508 and bashed 10 home runs in half a season. He did the bulk of his damage in West Michigan, where he helped lead the Whitecaps to a Midwest League championship.

Stewart is highly touted, although the accolades come with cautions. Baseball America has lauded his plus bat speed and raw power, but also opined that he’s “an aggressive hitter whose swing gets long.”

This past summer, I asked the first-year pro about the latter assessment.

“There’s not a lot of movement in my swing,” Stewart told me. “I think I have a short swing to the ball. My extension through the ball can get a little long at times, and maybe that’s what they mean.”

Phil Clark, West Michigan’s hitting coach last year, had a different take. He concurred with his charge on length, but then to pointed to the start, as opposed to the finish. Read the rest of this entry »


The Best of FanGraphs: January 25-29, 2016

Each week, we publish north of 100 posts on our various blogs. With this post, we hope to highlight 10 to 15 of them. You can read more on it here. The links below are color coded — green for FanGraphs, brown for RotoGraphs, dark red for The Hardball Times, orange for TechGraphs and blue for Community Research.
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