Position: Sports Info Solutions Research and Development Associate

Location: Coplay, Pa.

Description:

Sports Info Solutions (SIS) is looking for candidates to fill a full-time position in our R&D Department. The R&D Associate will work out of our office near Allentown, PA and will contribute as a member of our R&D team, supporting research for publications and future products.

Responsibilities:

• Perform modeling and research using SIS’s internal database as well as other notable data sets such as StatCast, Trackman, and PITCHf/x.
• Write articles and research pieces to be featured in publications such as The Fielding Bible, The Bill James Handbook, ESPN Insider, and Stat of the Week, among other prominent sports outlets.
• Prepare cutting-edge research for presentation in a professional setting, including sales presentations and conferences.
• Collaborate with BIS colleagues to help illuminate the value of SIS’s analytical products to prospective clients.

The position requires a variety of skills including (but not limited to) an analytical mind, computer expertise, writing ability, and a passion for sports, particularly baseball and football. Ideal candidates will possess the following qualifications.

Qualifications:

• Familiarity with contemporary baseball/football/sports analytics, including first-hand research experience.
• Analytical/Mathematical ability.
• Experience with MySQL, SQL Server, or similar databases.
• Proficiency working in Microsoft Office programs (or equivalents), especially Excel.
• Aptitude for data visualization using programs like Tableau and/or R.
• An ability to write and communicate effectively with a variety of audiences.
• An ability to work both collaboratively and independently.
• Experience with other statistical packages (i.e. R) and programming languages (i.e. Python, .NET) is a plus.

Compensation:
This position is compensated.

To Apply:
For more information or to apply, please submit your résumé and cover letter to careers@baseballinfosolutions.com.

Last week, I created a visualization of offensive stat projections for our Depth Charts, which use a blend of ZiPS and Steamer projections adjusted for playing time. It reflects the updates we make to the Depth Charts with injuries and roster moves. Below is its counterpart — pitching stats projections.

For our pitching visualization, I’ve included eight different stats we commonly use at FanGraphs: ERA, FIP, K/9, BB/9, HR/9, BABIP, RA9-WAR and WAR. For those not familiar with the different versions of pitching WAR FanGraphs hosts, our primary WAR calculations are based on a modified version of fielding independent pitching (FIP), which relies on strikeouts, walks, infield flies and home runs. RA9-WAR is based on runs allowed per nine innings. Each provides a different perspective on a value of a pitcher. I also chose to include batting average on balls in play (BABIP) this year to illustrate differences in expected BABIP, since some pitchers are able to affect the quality of contact of balls that are put into play.

The players are grouped into three categories: All Pitchers, As Starters, and As Relievers. These classifications are pulled from the playing time allotted to pitchers on the Depth Charts. A pitcher can be on both the starters graph and relievers graph; the number of inning he is projected to pitch will be different, along with WAR stats which are dependent on playing time. For “All Pitchers” playing time will be combined.

The circles on the graph represent an individual pitcher. The yellow line is the roster’s combined stat, which is specific to the category of pitcher you select. The gray bars represent the 25th and 75th percentile of the players shown on the graph. This illustrates the middle 50% of the pitchers available on the roster.

The data will update to account for roster moves consistently until the beginning of the season.

ERA

FIP

K/9

BB/9

HR/9

BABIP

RA9-WAR

WAR

All Pitchers

As Starters

As Relievers

2016 MLB Pitching Projections

FanGraphs Depth Charts

Over the last few years, there have been some players who have publicly acknowledged that they enjoy and use analytics to help themselves on the field. Zack Greinke, Brandon McCarthy, and Glen Perkins are some of the more notable players who have embraced nerd stats, and guys like Craig Breslow — with his molecular biophysics degree from Yale — buck the stereotype of the typical jock. But thanks to this great Travis Sawchik profile on Cole Figueroa, we might have a new contender for the title of King of the Ballplayer Nerds.

But he wasn’t interested in baseball analytics until he was traded to the pioneering Tampa Bay Rays in 2010, his third year in pro baseball.

“I said ‘OK, it’s important to them. Why isn’t it important to me?’” said Figueroa of analytics.

Figueroa said in the spring, in an auditorium setting, the Rays hold hitters’ meetings. He had never been in meetings like these. For example, Rays coaches spoke about evaluating the quality of hitter not by batting average but by batted ball exit velocity.

“Depending on who you were you could sleep through (the meetings), you could take exactly what they are giving you,” Figueroa said, “or you could expand upon it.”

Figueroa expanded.

“What can I do to become the most optimal player?” Figueroa asked himself. “What are my strengths? What are my weaknesses?”

Seeing the vast amount of data pouring into the game, and thinking about how to take advantage of it, he began to teach himself code, ‘R,’ or programming language.

He spent hours at Coursera.org — the Web site reassures a new visitor one can “Code Yourself!” — where there are step-by-step instructions in learning how to code and program.

With his nascent coding skills, he began to research and refine data given to him by the Rays, though the Rays kept much of their data off limits from their proprietary database.

He created models to understand how a player with his skills would age. He studied players with similar physical and statistical profiles. He studied what skills would age well, which would age poorly. In three consecutive seasons in Triple-A, he improved his on-base percentage.

“People think coding is some foreign language … in a sense where it’s only something really intelligent people can do,” Figueroa said. “And it’s really totally the opposite. Anyone can code.”

The whole thing is a great read, and even includes Figueroa giving hitting instruction to a teammate based on things he’d read from Alan Nathan, but the fact that Figueroa is writing his own code puts him on another level. I’d imagine that even if he doesn’t end up having a particularly great career on the field, every team in baseball has probably already penciled Figueroa’s name down for a potential front office or coaching job.

As we move closer to April 3, our Depth Charts have a better estimates for roster composition and playing time for the upcoming season. The Depth Charts use a blend of ZiPS and Steamer projections, which adjusts for playing time and calculates many of the stats we host on FanGraphs. Last year, I made a modified box plot which compares the teams by showing their distribution of players using their offensive stats and playing time. I’ve improved upon the concept slightly by adding more stats: OPS, wOBA, wRC+, K%, BB%, AVG, WAR. All these projections come from the same data the teams’ Depth Chart pages are built on.

In the plot below each player is represented by a green circle, whose area is proportional to the number of plate appearances the player is expected to have over the course of the season. The players are grouped by their teams, which have team stats represented by yellow lines. This represents the what the team AVG, wRC+, wOBA, OPS, etc. are. (Differing from traditional box plots, these marks do not represent the median of the data points.) The gray box representing the middle 50% of players on the roster. The box gives you an idea of the roster composition. Teams with a few star or elite players will skew the team stat higher than a team with a more balanced roster.

The visualization is interactive with tooltips when hovering over a player’s dot. Clicking a player’s dot will take you to his player stat page. The data will be current to when you load the page up until the day before Opening Day (4/2/2016).
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It’s become a practice of the present author in recent years to begin, towards the end of winter, a painstaking search for the new ballcap that will express his entire being. It’s also become a practice in recent years to parlay that search into web content so that the author might “remain” “employed.”

Two years ago, this pursuit yielded a Winston-Salem Spirits cap from 1994 with a weird red sun and melancholy eagle on it. Last year, I had the fortune of procuring a handsome Diablos Rojos cap from the actual team store at Parque Fray Nano in Mexico City. In each case, I have documented the relevant search for the benefit of posterity — even if posterity has failed to show any real interest in my work.

Recently, the author has renewed his dumb search. What follows is the third installment of same.

To wit:

Big Ten 10 Basketball Indiana Hoosiers Nutmeg nwt (Link)
Style: Snapback
Time Left: 17 days, 11 hours
Cost: US $19.99 (Buy It Now)

Essential to the task of becoming an adult is learning to abide life’s myriad, ridiculous contradictions. At an institutional level, the Big Ten Conference presents an excellent model for doing that exact thing. For years, it was composed of 10 actual universities. Since 1990, however, the membership has slowly increased to 14 schools. And yet, despite these mathematical realities, the conference’s constituents have remained unflinching in their commitment to the Big Ten moniker. Accordingly, wearing this cap is less a means by which to exhibit one’s support for a handful of midwestern flagship universities and more to acknowledge publicly the inherent absurdity of existence.

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With all due respect to Carter Capps, it looks like we have our first major injury of spring training.

Jhonny Peralta suffered a left thumb injury on Saturday. Early indications are that he tore a ligament, could miss 2-3 months.

— Jenifer Langosch (@LangoschMLB) March 7, 2016

The Cardinals have a good team, and are looking to contend again this year, but they don’t have a lot of organization depth at shortstop, and were counting on Peralta to play everyday. Barring a future move, this injury likely pushes Jedd Gyorko from a utility role into the starting line-up, which isn’t a position the Cardinals wanted to find themselves in. Not only is Gyorko not really a shortstop, losing him off the bench would mean taking away Kolten Wong’s platoon partner, weakening the team against lefties even more than simply swapping out Peralta for Gyorko would suggest.

While the gap between Peralta and Wong at shortstop over a full season is probably only 2-3 wins, and it sounds like Peralta will only miss about half the season, this seems like the kind of injury that should encourage the Cardinals to make a move for outside help. For one, the Cardinals can’t really afford to just surrender a win, given the fight the NL Wild Card race is shaping up to be, not to mention how good the Cubs are likely to be this year. And this isn’t a team that is built to just say “let’s get them next year”, as veterans like Adam Wainwright, Matt Holliday, and Yadier Molina aren’t getting any younger. The Cardinals need to maximize their chances of winning in 2016, and running Gyorko out at shortstop for a few months is at odds with that goal.

Unfortunately for St. Louis, the injury occurred a week after Ian Desmond and Jimmy Rollins signed as free agents, so there’s no easy solution sitting around looking for a job. On the trade market, Erick Aybar would seem to be a potential fit, as the Braves don’t really need a walk-year shortstop during their rebuild, but they don’t have any internal replacements ready, so Atlanta might not be keen on giving up their only decent option. The Mets have infield depth, with Ruben Tejada and Wilmer Flores both set to serve as reserves this year, but they might not be interested in helping an NL contender stay in the race.

The Cardinals have a long history of finding hidden gems, but unless they know something about Gyorko’s defense that no one else does, this could be a pretty big blow. Talking the Braves out of Aybar seems like the best option available at the moment, at least from my perspective.

Right-handed Washington prospect Lucas Giolito recorded his spring debut this afternoon in Florida, producing a 3:0 strikeout-to-walk ratio in 2.0 innings while conceding no runs and just a single hit against the Miami ball club (box).

If certain, possibly British sources are to be trusted, the three strikeouts were facilitated, at least in some part, by means of Giolito’s breaking ball — a breaking ball described recently by former Mets GM Steve Phillips as “bowel-locking.”

Because Evil is both real and constantly among us, video footage of those particular curveballs isn’t available for public consumption. What is available, however, is the educational film above, excerpted from the right-hander’s August 14th start against Double-A Baltimore affiliate Bowie. Within that footage, one finds a specimen of Giolito’s curveball, both in real time and also provocative slow-motion.

The reader is advised to locate his or her keys before consuming said video, however, so that it might be easier to unlock his or her bowels after examining it.

Brian Reinhart is a stranger, even to himself. He’s also responsible for bringing this series of events to the author’s attention.

Position: Texas Rangers TrackMan Operators

Locations: Surprise, AZ; Adelanto, CA; Round Rock, TX; Spokane, WA

Description:
The TrackMan operator will be responsible for running TrackMan system, and one is desired for each Rangers affiliate. The position runs from April to mid-September for Adelanto, Round Rock and Surprise, and mid-June to mid-September for Spokane.

Responsibilities:

• Responsible for setting up rosters and tagging the information.
• Track/chart information for the entire game – monitoring the system and making any changes throughout the game (i.e. roster changes, defensive substitutions, etc.).
• Responsible for fixing any errors, uploading the game to the TrackMan system, and running data and reports for coaches/front office staff.

Qualifications:

• Must be able to work all home games.
• Previous experience with TrackMan System is preferred but not required.
• Must have strong attention to detail and ability to communicate well with others.
• Strong preference will be given to local applicants at each location.

Compensation:
This position is compensated.

To Apply:
Interested applicants can email their materials to abrenner@texasrangers.com. Please specify which location you are applying for.

Larry Walker is a great hitter.

He’s a great hitter at Olympic Stadium. He’s a great hitter at Coors. He’s a great hitter at Busch. He’s a great hitter at any ballpark named after a beer.

Whereas the average hitter might create 120 runs per 162 games at Coors, Walker would create 190. That’s +60%.

Whereas the average hitter might create 85 runs per 162 games in every non-Coors park, Larry Walker would create 110. That’s +30%.

When you evaluate Larry Walker, you have two choices:
1. Neutralize Larry Walker by giving him 268 plate appearances in each of the home ballparks of the 30 MLB teams. His 2501 PA at Coors? Now we only count about 11% of that. His 32 PA in Oakland? We have to figure out how he’d have done if he got 268 PA. And so on.

2. Take a league average hitter, and put him in the same playing conditions as Larry Walker. Walker had 2501 PA at Coors? Great, let’s count it all. But let’s compare him to a league average hitter who also got to bat 2501 times at Coors. He came to bat 32 times in Oakland? Then the league average hitter also came to bat 32 times.

So, what are the strengths of these two options. In Option 1, we don’t allow Larry Walker to take “unfair” advantage of a park he might be ideally suited for. Whereas most hitter would increase their runs created by 40% at Coors relative to a non-Coors park, Larry Walker increased his by 70%. Given that he got 2501 PA at Coors, Walker ends up shining more than he would otherwise. It’s like letting Mariano Rivera come in 1- and 2-run games, while letting Trevor Hoffman and Billy Wagner only enter blowouts. They are all suited to close games, but if only Mo gets to leverage that, he’ll be the one getting all the saves. Is that fair? I dunno.

In Option 2, we deal with what actually happened. We don’t have to play a game of what-if. We simply accept what the player did, and that he was able to leverage (or not leverage) his unique playing conditions. All we do is make the comparison level all those thousands of players who also played in those exact same conditions, at the same frequency as our player. Walker@Coors is compared to average player at Coors, and Mo in high leverage situations is compared to the average reliever in high leverage situations, and so on. Everyone gets to keep what they did.

So, how do you want to see it?

While much of what appears on the author’s desktop is both detestable and also capable of being detested, that’s less the case with the image above, itself recently captured and and edited and uploaded by that same author by means of his personal computer.

Depicted in that image are Toronto right-hander Drew Hutchison and Philadelphia batter J.P. Arencibia, the latter of whom one finds in the process of recording what the Phillies broadcast team has referred to optimistically as Arencibia’s “first spring-training home run.”

While such a course of events typically wouldn’t merit attention, it’s notable today on account of how the image has been made by possible by the first telecast available this spring by way of MLB.TV. Later today, it would appear, curious fans also have the opportunity to observe Cleveland and Cincinnati face off roughly 2000 miles away from the dirty, dirty shores of the Cuyahoga River. For the moment, however, Maikel Franco is batting for Philly and in the midst of a 1-1 count.