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Baseball Prospectus is excited to announce what we believe to be the best measure of pitching ever, as well as advances in measuring pitchers' effectiveness stifling basestealers and avoiding errant pitches.

Baseball Prospectus' Director of Technology Harry Pavlidis will be chatting with readers Thursday at 1 p.m. ET. If you have any questions after reading this overview of Deserved Run Average, ask them here.

Introduction
Earned Run Average. Commonly abbreviated as ERA, it is the benchmark by which pitchers have been judged for a century. How many runs did the pitcher give up, on average, every nine innings that he pitched? If he gave up a bunch of runs, he was probably terrible; if he gave up very few runs, we assume he’s pretty good.

But ERA has a problem: it essentially blames (or credits) the pitcher for everything, simply because he threw the pitch that started the play. Sometimes, that is fair. If a pitcher throws a wild pitch, he can’t blame the right fielder for that. And if a pitcher grooves one down the middle of the plate, chances are that’s on him too. Not too many catchers request those.

However, most plays in baseball don’t involve wild pitches or gopher balls. Moreover, things often happen that are not the pitcher’s fault at all. Sometimes the pitcher throws strikes the umpire incorrectly calls balls. Other times they induce grounders their infielders aren’t adept enough to grab. And still other times, a routine fly ball leaves the park on a hot night at a batter-friendly stadium.

ERA doesn’t account for any of that. It just tells us, in summary fashion, how many runs were “charged” to the pitcher “of record.” And so, a starting pitcher who departs with a runner on first gets charged with that run even if the reliever walks the next three batters. The same starter would get charged if the reliever makes a good pitch, but the shortstop can’t turn a double play. And none of these runs count at all if they are “unearned”— an exclusion by which the home team’s scorer decides whether a fielder demonstrated “ordinary effort.”

The list of problems goes on. Pitchers who load the bases but escape are treated the same as pitchers who strike out the side. Pitchers with great catchers get borderline calls. Guys who can’t catch a break for months show immense “improvement.” Guys who are average one year wash out the next. ERA, in short, can be a bit of a mess, particularly when we have only a few months of data to consider.


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A further explanation of the reasons Deserved Run Average is designed as it is and works as it does.

This is the #GoryMath portion of the DRA rollout. If you proceed, don’t say we didn’t warn you.

A. Introduction
One of the hardest parts of any statistical investigation is defining what question it is you are trying to answer.

This is particularly important when it comes to pitcher performance metrics. What is it, exactly, that you want to know? For example:

(1) Do you care primarily about a pitcher’s past performance?

(2) Are you more worried about how many runs the pitcher will allow going forward?

(3) Or do you want to know how truly talented the pitcher is, divorced from his results this year or next?


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We move ever closer to a catcher-framing metric that captures a player's true value.

Last year, Baseball Prospectus introduced our Regressed Probabilistic Model (or “RPM”) for catcher pitch-framing. RPM uses PITCHf/x data to increase the measured accuracy of the actual contributions made by catchers. But RPM also suffered from two limitations. First, because PITCHf/x data was not publicly available before 2008, RPM could only measure catcher framing from recent seasons. Second, it relied primarily on a piecemeal approach to identifying the individual contributions of pitchers, umpires and catchers.

This year, we are pleased to announce an improvement that will address both limitations. We propose to move RPM from a “With or Without You” (WOWY) comparison method to a mixed model we call “CSAA” —”Called Strikes Above Average.” This new model allows simultaneous consideration of pitcher, catcher, batter, umpire, PITCHf/x, and other data for each taken pitch over the course of a season, and by controlling for each of their respective contributions will predict how many called strikes above (or below) average each such participant was worth during a particular season. Although PITCHf/x data is preferable when available, the mixed model (in a revised, “Retro” form) will allow us to live without it when need be, permitting us to project regressed framing of catchers all the way back to 1988, when pitch counts were first officially tracked.[1] This same technique developed for Retrosheet can also be applied to recent minor-league data to provide an even deeper view into the progression and value of this skill.

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November 12, 2014 6:00 am

The Best Roster Cores

15

Jonathan Judge

Looking at the teams with the best chances of keeping the gang together--the best cores in baseball.

It’s hot stove time, when we shift our focus from the season that was to the season on the horizon. Tires are kicked, trades are proposed, and free agents are considered. During it all, metrics like WARP allow us to summarize the performance of individual players. But what about the overall core of a team’s major-league roster? How can we say, objectively, whether a team has built a core of ongoing contributors? Or, by contrast, whether it has been overly reliant on transient (e.g., departing) assets?

A productive core consists of two things: good players under long-term control, and good players who are not too old. Players under long-term control allow a team to be patient and avoid expensive, volatile solutions (except in those cases when the players under long-term control become those expensive, volatile solutions); players who are younger also tend to play more games, be more productive, and remain productive for longer.

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Which teams figure to get the most out of their core contributors in 2014?

Most of our writers didn't enter the world sporting an @baseballprospectus.com address; with a few exceptions, they started out somewhere else. In an effort to up your reading pleasure while tipping our caps to some of the most illuminating work being done elsewhere on the internet, we'll be yielding the stage once a week to the best and brightest baseball writers, researchers, and thinkers from outside of the BP umbrella. If you'd like to nominate a guest contributor (including yourself), please drop us a line.

Jonathan Judge has a degree in piano performance but is now a product liability lawyer. He also blogs about the Brewers, and sometimes other teams, at Disciples of Uecker. Follow him on Twitter @bachlaw.


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Which teams can count on controlling their productive 2013 players for years to come?

Most of our writers didn't enter the world sporting an @baseballprospectus.com address; with a few exceptions, they started out somewhere else. In an effort to up your reading pleasure while tipping our caps to some of the most illuminating work being done elsewhere on the internet, we'll be yielding the stage once a week to the best and brightest baseball writers, researchers, and thinkers from outside of the BP umbrella. If you'd like to nominate a guest contributor (including yourself), please drop us a line.

Jonathan Judge got a degree in piano performance, but then thought better of it and became a trial lawyer instead. His hobbies include the Brewers, proper roster construction, and thinking about BABIP (which are not all necessarily related). Follow him on Twitter at @bachlaw.

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