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Articles Tagged Data Use 

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03-02

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2

BP Unfiltered: Sloan Q&A: Harry Pavlidis On f/x Tracking Data
by
Zachary Levine and Harry Pavlidis

11-13

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37

Bizball: Ranking 10 MLB Relocation and Expansion Markets Shows Why Either is Difficult
by
Maury Brown

01-31

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9

Baseball ProGUESTus: The Knuckleball Mystique: Using PITCHf/x to Distinguish Perception from Reality
by
Alan M. Nathan

01-09

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7

Resident Fantasy Genius: Contact Types
by
Derek Carty

01-03

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7

BP Unfiltered: Cot Tierney in the house
by
Dave Pease

12-21

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36

Spinning Yarn: Hit-and-Run Success is No Accident
by
Mike Fast

11-22

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30

Spinning Yarn: How Does Quality of Contact Relate to BABIP?
by
Mike Fast

10-26

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16

Spinning Yarn: Can We Predict Hot and Cold Zones for Hitters?
by
Mike Fast

08-27

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2

BP Unfiltered: Live Blog PITCHf/x Summit 2011
by
Mike Fast

07-25

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193

Manufactured Runs: Lost in the SIERA Madre
by
Colin Wyers

07-20

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14

Spinning Yarn: A Zone of Their Own
by
Mike Fast

06-20

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9

Resident Fantasy Genius: When Pitchers' Stats Stabilize
by
Derek Carty

06-13

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18

Resident Fantasy Genius: When Hitters' Stats Stabilize
by
Derek Carty

06-01

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6

Spinning Yarn: The Real Strike Zone, Part 2
by
Mike Fast

05-23

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24

The BP Broadside: The Annotated WARP Leaders
by
Steven Goldman

05-10

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12

Manufactured Runs: The Deconstruction of Falling Stars
by
Colin Wyers

03-30

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5

The BP Wayback Machine: Baseball's Hilbert Problems
by
Keith Woolner

03-02

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12

Spinning Yarn: How Accurate is PitchTrax?
by
Mike Fast

11-11

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7

Spinning Yarn: Pitcher Release Points
by
Mike Fast

10-26

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8

Spinning Yarn: Interpreting Pitch Classifications
by
Mike Fast

10-14

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8

Manufactured Runs: Just a Bit Outside
by
Colin Wyers

10-09

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24

Playoff Prospectus: The Mystery of the Inside Pitch
by
Colin Wyers

07-28

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21

Manufactured Runs: Looking Farther Afield
by
Colin Wyers

07-16

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33

Indefensible
by
Colin Wyers

04-13

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19

Manufactured Runs: Thawing Out Frozen Ropes
by
Colin Wyers

03-28

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7

Prospectus Q&A: Logan White, Part 1
by
David Laurila

03-23

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26

Ahead in the Count: Predicting BABIP, Part 1
by
Matt Swartz

01-10

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19

Prospectus Roundtable: BABIP and Line Drives
by
Baseball Prospectus

06-21

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62

Prospectus Idol Entry: Are Offensive Shortstops Becoming Toxic Sub-Prime Mortgages and Other Evolutionary Trends in Baseball Positions
by
Tim Kniker

04-23

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31

Checking the Numbers: Inside Pitch-f/x
by
Eric Seidman

04-10

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0

Schrodinger's Bat: Defense and Pitch Classification
by
Dan Fox

03-13

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0

Prospectus Hit and Run: Running Afoul
by
Jay Jaffe

02-24

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0

Prospectus Q&A: Doug Thorburn
by
David Laurila

02-21

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0

Schrodinger's Bat: Flashing Leather Down on the Farm
by
Dan Fox

02-17

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0

Prospectus Q&A: Joe Bohringer
by
David Laurila

01-27

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0

Prospectus Q&A: Mike Pagliarulo
by
David Laurila

01-24

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0

Schrodinger's Bat: Simple Fielding Runs Version 1.0
by
Dan Fox

10-24

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0

The Ledger Domain: The Impact of the Fantasy Stats Ruling
by
Maury Brown

10-02

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0

Prospectus Toolbox: The Umpires, Part I
by
Derek Jacques

08-30

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0

Schrodinger's Bat: Tilting the Playing Field
by
Dan Fox

06-07

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0

Schrodinger's Bat: Gameday Triple Play
by
Dan Fox

05-24

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0

Schrodinger's Bat: Batter Versus Pitcher, Gameday Style
by
Dan Fox

12-14

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0

Schrodinger's Bat: Questions, Questions
by
Dan Fox

10-26

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0

Schrodinger's Bat: The Information Revolution
by
Dan Fox

10-16

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0

Future Shock: Monday Morning Ten-Pack
by
Kevin Goldstein

10-16

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0

Prospectus Today: LCS, Day Six
by
Joe Sheehan

10-14

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0

Future Shock: Where Did the Tigers and the Athletics Come From?
by
Kevin Goldstein

10-14

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0

Prospectus Today: LCS, Day Four
by
Joe Sheehan

10-14

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0

Playoff Prospectus: The Best and Worst of Mets and Cardinals Postseason Pitching
by
Jim Baker

10-13

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Prospectus Today: LCS, Day Three
by
Joe Sheehan

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In a return look at Russell Carleton's original study, Derek tries to find at what point stats stabilize and can be trusted.

Four years ago, former BPer Russell Carleton (then monikered “Pizza Cutter”) ran a study at the now-defunct MVN’s StatSpeak blog that examined how long it takes for different stats to “stabilize.” Since then, it has become perhaps the most-referenced study in our little corner of the internet.

It has been a while since the initial study was run, and since there are a few little pieces of the methodology that I believe could be improved, I decided to run a similar study myself.

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When it comes to determining the actual upper and lower boundaries of the zone, pitchers may have more to tell us than the players at the plate.

Three months ago, I investigated the nature of the major-league strike zone, focusing on its inside and outside boundaries. I concluded that the location of a pitch relative to the catcher’s target had a significant impact on the umpire’s likelihood of calling a strike. This article will examine the top and bottom boundaries of the strike zone.

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A trip through our new 1950-and-up leaderboard, including a close look at our new-formula fielding runs.

Our collection of BP-flavored single-season WARP scores currently goes back to 1950. Now that we’ve added fielding runs to the sortable choices, you can easily see the combination of offense and defense that made the top players during this period so valuable, and in some cases dragged them down from even higher perches. Herein we traipse quickly through the 20 best players of the Truman-Eisenhower years and onward.

The fielding runs featured here are the product of our new revised formula developed by Colin Wyers. As Colin says, “The difficult part of any defensive metric is estimating the batted-ball distribution among fielders. Old FRAA used season-level data about things like pitcher handedness to figure out the distribution on a seasonal level, and prorated it out to individual fielders. Now, FRAA uses play-by-play data, which allows us to use more variables (like whether or not a fielder has to hold on a runner) and to assign responsibility to each fielder based on the games he actually played in.”

This version of FRAA avoids the pitfall of subjectivity inherent in zone-based ratings. “In contrast to other popular metrics,  FRAA does not use any stringer-recorded observational data,” Colin explains. “Serious discrepancies have been noted between data providers, and research has shown that in larger samples use of that sort of batted-ball data introduces severe distortions in the metrics that impede accuracy. Without evidence that the batted-ball data has redeeming value in the short term, it seems imprudent to use that sort of data in our evaluation of player defense.”

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What does the future hold for Derek Jeter, and how can we tell?

Before we can talk about Derek Jeter (and yes, I think there’s still something to say about Derek Jeter that you haven’t already heard this season), we should probably clarify which Derek Jeter we’re talking about. There really are two Derek Jeters—the one who exists in fact, and the one who exists in myth.

The actual Derek Jeter is interesting enough as a player that one wonders why the myth was necessary—always an exceptional hitter, Jeter has always been a player who could’ve had a job on any team in the league. He will go into the Hall of Fame on the first ballot, and nobody will bat an eye. Then there’s the Captain—the athlete whom ad agencies consider akin to Tiger Woods and Roger Federer. The player so exceptional that he can displace a generational talent like Alex Rodriguez from his natural position.

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How many of the last millenium's burning baseball questions remain unanswered over a decade down the road?

While looking toward the future with our comprehensive slate of current content, we'd also like to recognize our rich past by drawing upon our extensive online archive of work dating back to 1997. In an effort to highlight the best of what's gone before, we'll be bringing you a weekly blast from BP's past, introducing or re-introducing you to some of the most informative and entertaining authors who have passed through our virtual halls. If you have fond recollections of a BP piece that you'd like to nominate for re-exposure to a wider audience, send us your suggestion.

Over 11 years after their publication in Baseball Prospectus 2000, how many of Keith's questions for a new millenium have we already set to rest?


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Before you yell at the umpire, consider making a few adjustments to your dataset.

After the last two postseasons, most baseball fans are familiar with the strike zone location graphic known as PitchTrax. Here’s an example from Game One of the 2010 American League Championship Series:

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PITCHf/x data can shed light on pitchers' throwing mechanics.

Pitcher Release Points

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A closer look at what the various pitch types mean and how to approach pitch classification.

Several of the leading pitchers in this year’s postseason make their living with a cut fastball, most notably Roy Halladay and Mariano Rivera. The list of playoff pitchers who have the cutter as an important pitch in their arsenal, though, is long. It includes Cliff Lee, C.J. Wilson, and Tommy Hunter on the Rangers; Andy Pettitte and Phil Hughes on the Yankees; and Cole Hamels on the Phillies.

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Another look at calling balls and strikes from home.

Prompted by some of the complaints about umpiring, last week I investigated why watching on television may not give an accurate picture of where the ball is actually going. The short version—the position of the camera has a distorting effect on the image, and when the brain reconstructs a three-dimensional view, it is fooled by those distortions. Some people were skeptical of my claims.

Now, as it happens, we have a ready source of data we can use to evaluate the question of observer positioning bias in scoring balls and strikes off of video cameras—the plate discipline stats published by Fangraphs. Those figures are calculated using data provided by Baseball Info Solutions, which uses “video scouts” to collect data off baseball broadcasts (the same telecasts that we see as fans). These video scouts have a representation of the batter, the plate, and the strike zone, and they map the perceived location of the pitch on that image. That data is then aggregated.

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Was that really a ball or a strike Lance Berkman saw?

Regardless of what team they follow, what league they favor, baseball fans seem to be united by one common cause: they all seem to think that umpires don’t know how to call balls and strikes. That would be problematic, of course, seeing as how often umpires are called upon to do that and how important it is to the game of baseball.

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An attempt to construct a defensive metric without bias.

I have been making something of a ruckus recently about where I feel the state of current defensive analysis is. I have been long on listing problems, and short on proposing solutions.

Well, allow me to make amends there. I don’t pretend to have the problem solved. I’m not sure any of us will ever see it truly solved. But I think—or at least, hope—this can point us in the right direction.

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July 16, 2010 8:00 am

Indefensible

33

Colin Wyers

The difficulty of creating a new defensive metric when there are numerous disagreements in data.

Occasionally, I get asked—what’s going on with my attempts to make a defensive metric? I started off working on a Loess-based defensive metric, and then efforts just stalled. Because of the stall, it’s a fair question, and one that’s harder to answer than I think the questioners realize, because I’ve been slowly coming to some realizations about defensive metrics in general, and they aren’t encouraging.

The short version: I’m not really sure that we’ve gotten any further than where we were when Zone Rating and Defensive Average were proposed in the '80s. And if we have gotten further, I’m not sure how we would really tell. I’ve discussed some of this recently, first in a rather sprawling discussion at Tom Tango’s blog, and then in a conversation with Kevin Goldstein and Jason Parks on the BP podcast. But now’s a nice time to sort of take some time and compose those thoughts.

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