Archive for December, 2013

2014 ZiPS Projections – San Diego Padres

After having typically appeared in the entirely venerable pages of Baseball Think Factory, Dan Szymborski’s ZiPS projections were released at FanGraphs last year. The exercise continues this offseason. Below are the projections for the San Diego Padres. Szymborski can be found at ESPN and on Twitter at @DSzymborski.

Other Projections: Atlanta / Baltimore / Boston / Cleveland / Minnesota / Philadelphia / St. Louis.

Batters
San Diego’s leader by WAR in 2013 was Chris Denorfia, with a 3.9 mark — for which reason it feels odd to view him as part-time/platoon-type player entering 2014. Yet, that’s how the author has classified him in the depth-chart graphic below and how ZiPS seemingly regards him, as well — insofar, that is, as it doesn’t foresee the outfielder duplicating his career-best season, at all.

Of some difficulty with regard to understanding the 2014 iteration of the Padres is estimating precisely how playing time will work out between the team’s two catchers. ZiPS’ computer math suggests that Yasmani Grandal is probably the second- or third-best player on the whole club. That said, he underwent surgery on his ACL in August that could require up to a year of recovery. Fortunately for San Diego, Nick Hundley himself isn’t a particularly significant downgrade. Still, that’s a lot of talent to possess at one position while others could certainly afford to be upgraded.

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Rays Pay Up for James Loney

Over the past three seasons, the modus operandi for the Tampa Bay Rays has been to find a one-year solution at first base in the clearance bin of the offseason market. In 2011, that came in the form of adding Casey Kotchman on a minor league deal and watching him produce a 2.4 win season. In 2012, the team upped the budget and spent $7.25M to bring back Carlos Pena a year after he left via free agency, but Pena struggled through a 0.7 win season. Last season, James Loney was brought in on a $2M deal, and turned a profit with a career-best 2.7 win season.

The first base situation has been as much as a revolving door as the closer role has been with the club. Until Fernando Rodney repeated as the team saves leader last season, the team had had a different pitcher leads the team in saves each year under Maddon. While they have had repeated success with the closer role, the situation at first base has been a bit different.  As Joe Maddon often says about these types of situations, the Rays meatloafed the first base situation.

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Effectively Wild Episode 349: Brian Sabean’s Re-Signings and Rating GMs

Ben and Sam discuss the Giants’ offseason and their thoughts on Brian Sabean and other general managers.


Your 2014 Royals, Now With a Second Baseman

In a sense, the Yankees are back to being the Yankees. They offered a ton of money to sign Brian McCann. They offered a ton of money to sign Jacoby Ellsbury. There’s still talk they might offer a ton of money to try to sign Masahiro Tanaka. Yet the Yankees are still a team in need of an actual regular second baseman. They’ve reached this point because they were outbid on their own Robinson Cano by the Mariners, and now they’ve been outbid on Omar Infante by the Royals, who have a shiny new second baseman at a four-year commitment worth a little over $30 million.

You could say that there’s a revenge angle, since earlier in the offseason the Yankees signed Carlos Beltran with the Royals hot in pursuit. But this is less about vengeance and more about plugging an immediate hole, with a perfectly adequate player. Used to be I thought it was all but a given that the Royals would trade Billy Butler for Nick Franklin. Now they need their own DH, and they have their own second baseman. It’s a step forward for a team that would really really like to experience this year’s playoffs.

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Trading for Proven Workhorse David Price

The thing we know is that David Price is going to be traded. That much is a virtual certainty, for all of the reasons you already understand. The things we don’t know are all of the details. We don’t know where he’s going to be traded to, and we don’t know what he’s going to bring back. We don’t know when the trade is going to happen, and we don’t know if there’ll even be a trade this offseason. Would the Rays be daring enough to move Price during a competitive regular season? Would they be daring enough to wait to move Price until the next winter? Who feels a greater sense of urgency — the team with Price, or the teams that would like to have him? Behind the scenes, there’s probably a lot of activity, but from the outside it feels like nothing has budged for a matter of weeks.

Oh, and there’s another thing we know. David Price has been outstanding. Truly outstanding, since he graduated into the majors. He’s posted four consecutive seasons of at least 180 innings and at least an average ERA, and the reality is that he’s mostly exceeded those marks with relative ease. Over the four seasons, he’s averaged 208 innings and a 78 ERA-. Price has been one of the game’s great workhorses, and that’s a big part of how the Rays are selling him. You get Price, and you can write his next season’s numbers in ink.

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Federal Court Hearing In San Jose vs. MLB Could Move Process Forward

The federal judge overseeing the antitrust lawsuit by the City of San Jose against Major League Baseball held a case management conference Friday morning. But the hearing dealt with weightier issues as compared to the usual case management conference. Most particularly, the court is deciding whether to dismiss the two remaining state law claims for interference with contract and allow those claims to be re-filed in state court. If so, the court would enter final judgment in the federal case, and San Jose would have the right to immediately appeal to the Ninth Circuit Court of Appeals.

The hearing came two months after Judge Ronald M. Whyte issued an order that dismissed San Jose’s antitrust claims based on the court-created antitrust exemption for MLB. In the same order, the court held that San Jose had adequately pled two claims for interference with contract, on the theory that MLB’s delay in making a decision on the A’s proposal to move to San Jose had interfered with the A’s option agreement with San Jose to purchase five acres of land in downtown San Jose on which to build a new ballpark. My previous post on the Court’s ruling is here.

Judge Whyte began Friday’s hearing by stating that he was tentatively inclined to dismiss the state court claims. He then heard arguments by attorneys for the parties: John Keker for MLB and Philip Gregory for San Jose.

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Are Aging Curves Changing?

For years it’s been assumed hitters will get to the major leagues and peak offensively around age 30. Teams and fans can hope the new, shiny, 20-home-run-hitting rookie will improve over time and someday will hit 30 to 40 home runs. Hitters were expected to improve until their late twenties and then begin to decline. But recent data show there’s no longer a hitting-peak age. Instead, hitters arrive at their peak and simply decline with age.

I pretty much stumbled on this finding a few days ago. I created an stolen base aging curve for Mike Podhorzer and then created one for home runs. I separated the data into pre- and post-PED ban eras, the latter of which happened between the 2005 and 2006 seasons. It didn’t surprise me to see a slow decline in the home run curve during the PED era. My biggest surprise was the post-PED data where home runs no longer peaked, they only declined. I examined just about every overall offensive stat (OPS and wOBA, to name a couple) and found the same thing: Hitters no longer peaked, they only declined. Here’s a look at the wOBA aging curve from pre- and post-PED ban eras, along with a note on how the curves were created.

Note: The aging curve was created by the delta method by weighting plate appearances using their harmonic means. With this method, there’s a small survivor bias summarized by Mitchel Lichtman at the Hardball Times:

… survivor bias, an inherent defect in the delta method, which is that the pool of players who see the light of day at the end of a season (and live to play another day the following year) tend to have gotten lucky in Year 1 and will see a “false” drop in Year 2 even if their true talent were to remain the same. This survivor bias will tend to push down the overall peak age and magnify the decrease in performance (or mitigate the increase) at all age intervals.

For 20 seasons, hitter production began to decline significantly around age 30. Over the past seven seasons, the decline has occurred immediately.

A problem exist when using wOBA in the recent lower scoring environment. The league wOBA in 2006 was .337, and in 2013 it was at .318. That’s a drop of 19 points in seven seasons, or 2.7 points  per season. Players will have the appearance of aging from season to season.

Hitting (wOBA) has been on the decline for several reasons. Teams have been better at evaluating players’ defense abilities and deploying better defensive alignments in the field. Also, the quality and quantity of hard-throwing relief pitchers has increased across the league. Finally, 2006 was the first full season with the harsher PED punishments (from 50-game suspensions to 100-games suspensions t0 lifetime bans). This overall decline leads to a large year-to-year aging factor. The recent decline in offense led me to create aging curves with wRC+, which is weighted to the season’s, the league’s and the park’s run-scoring environment. I ran the aging curve to look at four, seven-year time frames.

With wRC+, the most recent aging curve doesn’t immediately begin declining like the wOBA curve. Instead, it remains constant until it begins to decline. The decline starts at the same point when previous players began declining (between age 25 to 26 season). The curve shape is the same for pitcher aging curves: no up and down, just constant and then down. Additionally, the most recent rate of decline is almost the same as the pre-PED aging rate (82-89).

This information is important in predicting young players’ performance. Once a hitter makes it to the majors, he doesn’t really improve. In the past, people used to hope for improvement and growth as the player aged. These days, people should expect to see the player performing at his career best immediately.

A couple possible reasons may be behind the lack of improvement. First, players are more prepared for majors, physically and mentally. In the past, a player may not have had the best conditioning, coaching and training while he was in the minors. Teams are putting more resources into their minor league affiliates, and there isn’t room for improvement with the major league team. Second, teams may be better at knowing if or when a player will be MLB ready, meaning the player doesn’t have to mature and grow at a lower level. They are ready to contribute immediately

This trend of contributing right away may have been occurring before 2006. The uncontrolled use of PEDs may have masked the lack of an up and down curve. Players were improving chemically past their previous peak and were able to maintain their performance over time.

For years, pitcher performance declined as those players aged, but hitters seemed to have an up and down performance curve. In the past few seasons, hitters no longer improve once they arrive in the majors. Instead, their performance is constant until they begin to decline, which, on average, is at 26 years old. Improved training and development is probably behind the shift. If fans are hoping for a young position player’s performance to peak, they might be sorely disappointed. Chances are the player is likely producing at his career-best already.


Job Posting: Baseball Info Solutions Multiple Openings

Company Overview

Baseball Info Solutions (BIS) is committed to providing the most accurate, in-depth, timely professional baseball data, including cutting-edge research and analysis, striving to educate major league teams and the public about baseball analytics.

We are seeking highly motivated individuals with a passion for baseball to join our team.

.NET Developer

Would you like to launch your software development career working with the latest .NET tools and technologies? Would you be interested in working closely with a small team of senior developers to create new products and features in a baseball centric environment? Baseball Info Solutions is seeking a Junior .NET Developer in our Coplay, PA office to help deliver new web-based products to our customers. This is a great opportunity in a casual office environment with one of the leading providers of in depth baseball statistics.

The candidate will develop assist in developing new products as well as help maintain existing products. Strong candidates will possess a self-motivated attitude, great communication skills, and be able to work in a collaborative, team environment or independently as needed.

Candidates must possess:

  • Develop new features, applications and maintain existing applications.
  • Full life-cycle development.
  • Web development in C# and Asp.NET 4.0.
  • Full understanding of Asp.NET using a C# object oriented code base.
  • Understanding of SSRS.
  • HTML and CSS
  • In depth knowledge of MS Development tools
  • Knowledge of baseball statistics and analytics.
  • SQL Server Development is a plus.

Skills and Qualifications:

For more information or to apply, please submit your résumé and cover letter to careers2013@baseballinfosolutions.com.

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2014 Video Scouts

BIS Video Scouts watch multiple games per day throughout the season and record their observations for our clients’ consumption. The BIS Video Scout internship is perhaps the best pipeline into a successful career in the baseball industry. Many executives inside major league front offices credit BIS for their first steps into the baseball industry.

Responsibilities:

  • Score and pitch chart MLB games using specialized computer software
  • Check the accuracy and validity of data
  • Prepare and analyze statistical data for delivery to customers
  • Assist with the production of the 2015 Bill James Handbook
  • Provide administrative support to the full-time staff
  • Demonstrated knowledge of baseball and baseball scorekeeping
  • Ability to identify and differentiate between pitch types
  • Computer proficiency and the ability to quickly learn new software
  • High school or college baseball playing experience is preferred but not necessary
  • Must be able to work nights and weekends
  • Must be willing to work from our Allentown/Bethlehem, PA office

Qualifications:

Timeframe:

Interns will begin in either January or March and conclude at the end of the regular season (September 29th), with a possibility of extending through the middle of October.

Compensation:

An hourly rate of $7.25 and/or college course credit will be offered to each Video Scout. Anyone interested in the internship should send a cover letter and resume to Dan Casey at dan@baseballinfosolutions.com.

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Research & Development Intern

Baseball Info Solutions is looking for candidates to fill a paid internship in our R&D Department in the spring and/or summer seasons.  The intern will work out of our office near Allentown, PA and will assist our R&D team, supporting research for publications and future products, including Stat of the Week, The Bill James Handbook, and The Fielding Bible.  Recent R&D interns have landed internships and full-time jobs with major league teams.

The position requires a variety of skills including (but not limited to) an analytical mind, computer expertise, writing ability, and a passion for baseball.

Ideal candidates will possess:

  • Knowledge of and familiarity with baseball and sabermetric research
  • Analytical/Mathematical ability
  • Proficiency working in Microsoft Office programs (or equivalents), especially Excel
  • Experience with MySQL, SQL Server, or similar databases.
  • 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, programming languages, and/or graphical visualizations would be a plus.

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


2014 ZiPS Projections – Minnesota Twins

After having typically appeared in the entirely venerable pages of Baseball Think Factory, Dan Szymborski’s ZiPS projections were released at FanGraphs last year. The exercise continues this offseason. Below are the projections for the Minnesota Twins. Szymborski can be found at ESPN and on Twitter at @DSzymborski.

Other Projections: Atlanta / Baltimore / Boston / Cleveland / Philadelphia / St. Louis.

Batters
“How will Joe Mauer’s move from catcher to first base affect the Twins?” is likely a question that a number of people have asked this offseason, either aloud or just to themselves. The answer, at least so far as ZiPS is concerned, is probably “Not much.” In either case, that is, Minnesota doesn’t resemble anything much like a club that’ll find itself in playoff contention during the waning months of baseball’s regular season. That’s not to say it won’t affect Mauer’s production, personally. After receiving a projection of four-plus wins from ZiPS last winter and then actually outproducing that figure during 2013, the erstwhile backstop receives here a projection of fewer than three wins as a first baseman.

Part of that appears to be adjustment for BABIP: no player is reasonably forecast to record one above .350, even though Mauer has exceeded that figure each of the last two seasons. Part of that is likely a product of whatever aging curve Dan Szymborski’s math computer utilizes. But a third part of it is due, also, to the positional adjustment for a first basemen relative to a catcher. Whether projected to record a 125 OPS+ (as he was last year) or 121 OPS+ (as with this one), that’s a less formidable number when it’s being produced by a first baseman.

An encouraging development, on the other hand, is the projection for Mauer’s replacement at catcher, Josmil Pinto, about whom Steamer is also rather optimistic.

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Tool: Basically Every Pitching Stat Correlation

In doing my research, I often like to take a look at correlations to get an idea about whether factors might be connected.  At the end of this season, I put together a spreadsheet to help me with that.  Well, I haven’t finished the research yet (FG+ subscribers will probably soon find out what’s been keeping me from it), but in the meantime, I thought I’d share what I hope will be a pretty handy tool for whomever out there might be interested in what lies a little beneath the surface of all these stats on FanGraphs.  And I do mean all of them.  Any pitching-related stat on FanGraphs should be represented in this tool.  You can compare one stat to another, or to itself in a different year.  Or, what the heck, you can even compare a stat to a different stat in a different year.  And, for you sticklers out there, it will even give you a confidence interval on these correlations (by default, it gives you the range of correlations that the true correlation has a 95% chance of being within).

What can you do with this?  Well, let’s say you want to see whether a stat is predictive of the next year’s ERA.  You could, for example, set Stat 1 to K% (after selecting the correct white box, type it in, or select from the drop-down list via the arrow to the right of the box), with the year set to 0 (meaning the present year), then set Stat 2 to ERA, with the year set to 1 (meaning the next year).  If you don’t change the IP or Season filters, you should see a correlation of -0.375.  That shows there’s a pretty decent connection between the two stats, in that if a pitcher has a high strikeout percentage in one season, he’ll likely have a low ERA the next (relative to the rest of the pitchers in the comparison).  If you change the year under ERA to 0, you’ll see the correlation gets stronger, whereas if you change it to 2 or 3, you’ll see it gets weaker.  That has a lot to do with the unpredictability of K%, and especially of ERA.  You’ll notice if you compare year 0 K% to year 1 K%, the correlation is a very strong 0.702, whereas if you do the same for ERA, it’s a moderate-to-weak 0.311.  Hopefully the graph will give you an idea of how strong those connections really are.
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