Job Posting: MLB Senior Software Engineer

Position: Senior Software Engineer at Major League Baseball

Location: San Francisco, CA

Major League Baseball is looking for experienced Software Engineers that are passionate about building new technologies for the baseball industry. Launched in 2001 as the tech arm of Major League Baseball, MLBAM is now a leading authority in real-time sports data processing, distribution and analysis.

The Baseball Data team is the central data hub for MLB. Using cutting edge technology, our data is consumed by fans, broadcasters, stadiums, and MLB teams. Our team’s primary product line is MLB.com Gameday, Statcast and Pitchcast.

The Opportunity:
As a Senior Software Engineer, your primary responsibilities will be to write clean, concise, modular code in an agile environment, mentor developers and provide code reviews.

You’ll also:

  • Lead and take ownership of critical projects and your own initiatives.
  • Work on a great technology stack including HTML5, Javascript, React, SQL, Java 11+, Spring, Scala and more.
  • Introduce the technologies you feel passionate about.
  • Collaborate with a team of extraordinary engineers and technologists.
  • Influence the innovation of products used by millions of users worldwide.
  • Work alongside top data scientists on data analysis, machine vision and NLP.
  • Participate in the full lifecycle of software development (requirements gathering, designing, building, testing and maintenance).
  • Change the way baseball is consumed.
  • Receive amazing benefits – you get 100% employer-paid Medical, Dental and Vision.

You have:

  • 7+ years of experience using front end technologies: JavaScript, React, HTML5, CSS3.
  • Experience using JVM languages (Java, Scala, Kotlin…).
  • Experienced building large and scalable applications.
  • An avid learner, independent with excellent problem-solving skills.
  • Passionate about mentoring peer developers, providing code reviews, etc.
  • Baseball fan.

Preferred, but not required:

  • Exposure to Google Cloud Platform or Amazon Web Services.
  • Familiar with messaging queues: ActiveMQ or RabbitMQ or similar
  • Experience with SQL databases
  • Understanding of big data concepts and knowledge of big data languages/tools such as Hadoop, Kylin, or Spark
  • Experience with 3D modeling and statistical analysis of 3D models

What Is It Like to Work at MLB?
Major League Baseball (MLB) is the most historic of the major professional sports leagues in the United States and Canada. Employees love working at MLB because of the culture of growth, teamwork, and professionalism. Employees who are most successful at MLB take initiative, know how to identify problems and provide solutions, and always put the Team first. For those ready to step up to the plate and join the Major Leagues, MLB takes the same approach as teams do with their players: empowering them to be at their best by engineering experiences that put employees in the best position to succeed. Major League Baseball is looking for candidates who are passionate about growing America’s pastime to best serve its fans for decades to come.

MLB’s vision is to be the global sport of choice for youth to play, fans of all backgrounds to enjoy and a desired destination for employment. With a belief that the journey to growth and greatness is ongoing, MLB gives employees the opportunity to continue learning and honing their skills with programs such as: tuition reimbursement; mentorship programs; lunch and learns; online course subscriptions; paid industry certifications; business resource groups; and more.

MLB provides its employees with exceptional medical, dental, and vision coverage. Premiums are 100% employer covered to help employees focus on being their best!

All in-office and ballpark-based positions are subject to MLB’s mandatory Covid-19 vaccine policy

To Apply:
To apply, please follow this link.

The content in this posting was created and provided solely by Major League Baseball.


Sunday Notes: Chris Denorfia and Emma Tiedemann are Bullish on Ezequiel Tovar

Ezequiel Tovar came into the season ranked as the No. 4 prospect in the Colorado Rockies system. Despite being just 20 years old, he might finish it in the big leagues. In 229 plate appearances with the Double-A Hartford Yard Goats, Tovar is slashing .317/.393/.579 with a 165 wRC+. Moreover, he has a dozen home runs and has swiped 16 bases in 17 attempts.

His calling card is his glove. Described by our own Eric Longenhagen as “a no-doubt shortstop with balletic defensive footwork and a well-calibrated internal clock.” Tovar had received similar rave reviews from MLB scouts in the Arizona Fall League. And that was before he blossomed with the bat.

I asked Yard Goats manager Chris Denorfia about the offensive strides that have elevated Tovar’s profile.

“Coming into this year, I was told that there was some chase on down-and-away sliders,” said Denorfia, who played 10 big-league seasons. “But I haven’t seen what everybody was talking about. Somewhere between the Fall League and this spring, he’s made this developmental jump. Something clicked to where he’s recognizing situations where pitchers are going to try to get him to chase. Whether you call it slowing the game down, or just having enough reps, he’s made that adjustment. It was probably the one thing that was holding him back, which is kind of weird to say, because he was only 19 last year.”

The discipline is reflected in the numbers. Despite being one the youngest players in his league, Tovar possesses a 9.6 walk-rate and a 22.3% K-rate. When you add his improved pop to the equation, it’s easy to see why speculation of a call-up — premature that it may be — has begun to grow legs. Read the rest of this entry »


Effectively Wild Episode 1861: I’m Not Maddon, I’m Just Disappointed

EWFI
Ben Lindbergh and Meg Rowley banter about Joe Maddon’s firing, the impact and end of the Angels’ 14-game losing streak, and whether the Angels or Phillies are in a worse position for the future, Tony La Russa’s intentional walk on a 1-2 count, whether the weather and the humidor can explain MLB’s sudden upticks in fly-ball distance and home-run rate, the testing of experimental, legalized sticky stuff in the minor leagues, Hunter Greene’s rain-shortened run at a Statcast no-hitter, how the Cardinals and Rays played a nine-inning game in less than two hours, Joey Bart’s demotion and the wide range in the performance of this season’s promoted top prospects, the return of Stephen Strasburg (sort of), an update on Cody Bellinger and Christian Yelich and observations about Alex Bregman, David Robertson, Sandy Alcantara, Willians Astudillo, and Tony Gonsolin and the Dodgers, the teaser for the latest TV adaptation of A League of Their Own, Angel Hernandez filing an appeal over his discrimination lawsuit, the Rays’ Pride Night debacle, a NYT crossword conflating plate appearances and at-bats, and pedantry about whether home-run hitters are actually on base, plus a Past Blast about 1861.

Audio intro: Nick Lowe, “14 Days
Audio outro: Imperial Teen, “One Two

Link to Jay Jaffe on Maddon
Link to Sam Blum on Maddon
Link to Rosenthal Q&A with Maddon
Link to Ohtani’s streak-ending highlights
Link to story about signature significance
Link to James Fegan on La Russa
Link to Ginny Searle on La Russa
Link to Ben Clemens on La Russa
Link to broadcast clip of La Russa IBB
Link to La Russa explanation video
Link to Seager 1-2 IBB
Link to Trout 1-2 IBB
Link to Ballpark Pal home-runs thread
Link to Alan Nathan on Twitter
Link to Mike Axisa on homers and Greene
Link to Evan Drellich on MiLB sticky stuff
Link to Sam on Statcast no-hitters
Link to Greene’s batted balls allowed
Link to short Rays-Cardinals game
Link to MLB.com on McClanahan
Link to pitcher pace leaderboard
Link to Jay on Bart’s demotion
Link to Ben on the minors-to-majors gap
Link to MLB.com on Strasburg
Link to David Laurila on Bregman
Link to Ben on Longoria
Link to Jay on Gonsolin
Link to Astudillo scoring video
Link to A League of Their Own teaser
Link to story about Hernandez’s appeal
Link to Hernandez at Umpire Scorecards
Link to Ginny on the Rays
Link to Emma’s crossword tweet
Link to tweet about NL Central losing streak
Link to Richard Hershberger’s Strike Four
Link to 1861 story source
Link to Cabrera’s spring hidden-ball trick

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 Email Us: podcast@fangraphs.com


Checking Out 2022 zStats for Pitchers After Two Months of Play

Hunter Greene
The Enquirer

As anyone who does a lot of work with projections could likely tell you, one of the most annoying things about modeling future performance is that results themselves are a small sample size. Individual seasons, even full ones over 162 games, still feature results that are not very predictive, such as a hitter or a pitcher with a BABIP low or high enough to be practically unsustainable. For example, if Luis Arraez finishes the season hitting .350, we don’t actually know that a median projection of .350 was the correct projection going into the season. There’s no divine baseball exchequer to swoop in and let you know if he was “actually” a .350 hitter who did what he was supposed to, a .320 hitter who got lucky, or a .380 hitter who suffered misfortune. If you flip heads on a coin eight times out of 10 and have no reason to believe you have a special coin-flipping ability, you’ll eventually see the split approach 50/50 given a sufficiently large number of coin flips. Convergence in probability is a fairly large academic area that we thankfully do not need to go into here. But for most things in baseball, you never actually get enough coin flips to see this happen. The boundaries of a season are quite strict.

What does this have to do with projections? This volatile data becomes the source of future predictions, and one of the things done in projections is to find things that are not only as predictive as the ordinary stats, but also more predictive based on fewer plate appearances or batters faced. Imagine, for example, if body mass index was a wonderful predictor of isolated power. It would be a highly useful one, as changes to it over the course of a season are bound to be rather small. The underlying reasons for performance tend to be more stable than the results, which is why ERA is more volatile than strikeout rate, and why strikeout rate is more volatile than the plate discipline stats that result in strikeout rate. Read the rest of this entry »


Tony Gonsolin Is the Latest Dodgers’ Starter To Dominate Hitters

© Gary A. Vasquez-USA TODAY Sports

Given their success over the past half-dozen years and the strength of their preseason projections, it’s no surprise to find the Dodgers owning the National League’s top record (37-20, .649) while continuing to hold the league’s highest Playoff Odds (98.4%) and highest odds of winning the World Series (15.5%). What’s unusual is that they’ve done it with Clayton Kershaw missing about half the season thus far and with both Walker Buehler and Julio Urías struggling to regain their front-of-the-rotation form. Instead it’s been Tyler Anderson and Tony Gonsolin — two pitchers we initially projected to throw fewer than 100 innings as starters — leading the way in a rotation that has the majors’ lowest ERA (2.65).

On Thursday, Anderson’s scoreless streak came to an end at 28 innings against the White Sox, thanks in part to a ball that parkour’d its way into becoming a triple, but so far this year, he’s ridden an improved changeup to unexpected success. The night before that, it was Gonsolin holding Chicago to one run over six innings while helping to halt a three-game losing streak, the Dodgers’ second within a nine-day span. In the process, the 28-year-old righty took over the official NL ERA lead, at least for the moment, via a 1.58 mark. He’s pitched 57 innings while the Dodgers have played 57 games, but he’ll slip below the qualifying threshold again before he next gets the ball.

Regardless, Gonsolin is showing signs of a breakout, and at the very least enjoying his longest sustained run of major league success. Though he’s pitched for the Dodgers for four seasons — and largely pitched very well, with a 2.48 ERA and 3.50 FIP in 199.1 innings — it’s been in fits and starts. The ninth-round 2016 pick out of St. Mary’s College of California debuted in the majors three years later but that year was yo-yoed between Los Angeles and Oklahoma City, totaling just six starts, five relief appearances, and 40 innings. In 2020, Gonsolin totaled eight starts, one relief appearance, 46.2 innings, and three times being optioned to the Dodgers’ alternate training site. Last year, he spent two separate stretches on the injured list due to recurring right shoulder inflammation, not debuting until June 9 and then spending all of August and part of September sidelined. He made a career-high 13 starts plus two relief appearances but finished with just 55.2 innings. Read the rest of this entry »


Does Framber Valdez Warrant a Five Man Infield?

Framber Valdez
Peter Aiken-USA TODAY Sports

FanGraphs readers are a smart bunch. Though the comments can sometimes unravel into a series of shouting matches, the usual atmosphere is encouraging and collegial. For example, here’s a thought-provoking question I received a few weeks ago and my reply to it:

This is from an article I wrote about Framber Valdez and how he was on pace to shatter his own historic groundball-to-fly ball ratio. A five-man infield in any other circumstance would be out of the question, but consider just how many grounders Valdez generates. Among starters with a minimum of 200 innings pitched since 2020, he’s first in groundball rate (66.7%) by a wide, wide margin. With so few balls heading towards the outfield, does it make sense to reinforce the infield instead? It’s an intriguing inquiry, one that I promised would receive an answer. So here goes! Read the rest of this entry »


FanGraphs Audio: GM Nick Krall on the Cincinnati Reds

Episode 978

On this edition of FanGraphs Audio, we talk to another major league general manager before some banter about recent writing on the site.

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Audio after the jump. (Approximate 62 minute play time.)


Tony La Russa Is at It Again

© Kamil Krzaczynski-USA TODAY Sports

I thought this week couldn’t get any better. I got to write about bunts, one of my favorite things to do, and about the Giants picking up tiny edges, another personal favorite. I got to write about Yordan Alvarez and how people underrate him; now I can cross that off my yearly to-do list. But Thursday took the cake. Have you seen this nonsense?

I love writing about bad intentional walks. I love writing about bad managerial decisions. But I can’t really wrap my head around this one, hard as I try. Let’s try to do the math, such as it is, while keeping in mind that no amount of math is going to make this make sense.

Let’s start at the top. Trea Turner is an excellent hitter, and Bennett Sousa is a lefty. Turner boasts average platoon splits for his career. Sousa has hardly pitched in the majors, so let’s just consider him an average lefty. With a runner on second and two outs, passing up an excellent righty hitter against your lefty pitcher is standard operating procedure. Read the rest of this entry »


Effectively Wild Episode 1860: Start Them Young

EWFI
With Meg Rowley on the road, Ben Lindbergh talks to a trio of guests. First (4:10), he’s joined by Mr. King, the creator of Northwoods Baseball Sleep Radio, to talk about baseball as ASMR, crafting a fictional league, broadcaster, and collection of players, replicating the soothing, white-noise sounds of a baseball broadcast, putting his listeners to sleep, and more. Then (34:32) Ben brings on coach and journalist John W. Miller to examine how the rise of private travel baseball clubs and pay-to-play tournaments has reshaped youth baseball and excluded some kids from the sport, discuss the ramifications from Little League to the major leagues, and propose some solutions. After that (1:18:12), former major leaguer (and former EW guest) John Poff rejoins, along with John Brave Bull and Ardyce Taken Alive from the Standing Rock Reservation, to talk about their histories, explain their efforts to bring baseball to kids at Standing Rock, and ask the EW audience for help (plus a reading of a Poff poem). Finally (1:50:05), Ben shares a baseball-history anecdote from 1860.

Audio intro: Julie Andrews, “Stay Awake
Audio interstitial 1: Dave Dudley, “George (and the North Woods)
Audio interstitial 2: Peter, Paul and Mary, “Right Field
Audio outro: Raye Zaragoza, “Driving to Standing Rock

Link to Baseball Sleep Radio website
Link to Baseball Sleep Radio on Spotify
Link to FG post on Baseball Sleep Radio
Link to the real Northwoods League
Link to Bloomberg on white noise podcasts
Link to The Universal Baseball Association
Link to old baseball broadcasts on YouTube
Link to old baseball broadcasts on archive.org
Link to GameChanger Plays Announcer post
Link to John Miller on youth baseball
Link to John on improving youth baseball
Link to Tom House baseball-size tweet
Link to McCutchen at The Players’ Tribune
Link to Pittsburgh Hardball Academy site
Link to info on the Dream Series
Link to RBI Baseball site
Link to article on commercializing youth sports
Link to data on youth sports participation
Link to John Miller’s baseball resume
Link to John Miller’s website
Link to John Poff’s SABR bio
Link to John’s first podcast appearance
Link to Poff Stat Blast episode
Link to Standing Rock Reservation wiki
Link to KLND website
Link to Community Alliance Group website
Link to John’s North Dakota Quarterly poems
Link to John’s GoFundMe fundraiser page
Link to Richard Hershberger’s Strike Four
Link to 1860 story source 1
Link to 1860 story source 2

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Checking Out 2022 zStats for Hitters After Two Months of Play

Taylor Ward
Darren Yamashita-USA TODAY Sports

As anyone who does a lot of work with projections could likely tell you, one of the most annoying things about modeling future performance is that results themselves are a small sample size. Individual seasons, even full ones over 162 games, still feature results that are not very predictive, such as a hitter or a pitcher with a BABIP low or high enough to be practically unsustainable. For example, if Luis Arraez finishes the season hitting .350, we don’t actually know that a median projection of .350 was, in fact, the correct projection going into the season. There’s no divine baseball exchecquer to swoop in and let you know if he was “actually” a .350 hitter who did what he was supposed to, a .320 hitter who got lucky, or even a .380 hitter who suffered misfortune. If you flip heads on a coin eight times out of ten and have no reason to believe you have a special coin-flipping ability, you’ll eventually see the split approach 50/50 given a sufficiently large number of coin flips. Convergence in probability is a fairly large academic area that we thankfully do not need to go into here. But for most things in baseball, you never actually get enough coin flips to see this happen. The boundaries of a season are quite strict.

What does this have to do with projections? This volatile data becomes the source of future predictions, and one of the things done in projections is to find things that are not only as predictive as the ordinary stats, but also more predictive based on fewer plate appearances or batters faced. Imagine, for example, if body mass index was a wonderful predictor of isolated power. It would be a highly useful one, as changes to that over the course of a season are bound to be rather small. Underlying reasons for performance tend to be more stable than the results, which is why ERA is more volatile than strikeout rate and why strikeout rate is more volatile than plate discipline stats that result in strikeout rate.

MLB’s own method comes with an x before the stat, whereas what ZiPS uses internally has a z. I’ll let you guess what it stands for! I’ve written more about this stuff in various places such as here and here, so let’s get right to the data for the first two months of the MLB season. Read the rest of this entry »