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Articles Tagged Defensive First Basemen 

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02-29

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12

Prospectus Preview: AL West 2012 Preseason Preview
by
Jason Parks and Jason Wojciechowski

02-01

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1

Heartburn Hardball: All That Heaven Will Allow
by
Jonathan Bernhardt

12-28

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42

Prospectus Hit and Run: The Class of 2012: The First Basemen
by
Jay Jaffe

05-23

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24

The BP Broadside: The Annotated WARP Leaders
by
Steven Goldman

05-19

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11

Prospects Will Break Your Heart: U Got the Look: Fielders, Part I
by
Jason Parks

12-23

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16

Prospectus Hit and Run: The Class of 2011: Bagwell and Baggage
by
Jay Jaffe

11-10

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5

So You Need: Corner Infielders
by
Marc Normandin

02-11

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14

You Could Look It Up: Three Joes and Some Other Guys Named Overbay
by
Steven Goldman

12-23

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14

Prospectus Hit and Run: Hall of Fame Cases at Third and Short
by
Jay Jaffe

12-21

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52

Prospectus Hit and Run: Alomar, the Crime Dog, the Big Cat and Big Mac
by
Jay Jaffe

11-22

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23

Prospectus Today: Infield Free Agents Review
by
Joe Sheehan

03-13

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6

Prospectus Q&A: John Dewan
by
David Laurila

01-24

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0

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

06-28

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0

Future Shock: The Draft Spectrum, Part Two
by
Kevin Goldstein

02-13

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0

Lies, Damned Lies: PECOTA Takes on Second Base Prospects
by
Nate Silver

10-14

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0

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

10-12

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0

Player Profile
by
Marc Normandin

10-06

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0

Prospectus Matchups: October Musings
by
Jim Baker

03-22

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0

Lies, Damned Lies: Rethinking Replacement Level
by
Nate Silver

03-15

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0

Future Shock: Taking A Step Back, Part Two
by
Kevin Goldstein

03-07

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0

Doctoring The Numbers: The Draft, Part Eight
by
Rany Jazayerli

12-12

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0

The Class of 2006
by
Jay Jaffe

09-22

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0

Lies, Damned Lies: A New Look at Aging
by
Nate Silver

09-13

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0

Doctoring The Numbers: The Draft, Part Seven
by
Rany Jazayerli

12-16

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0

The Class of 2005
by
Jay Jaffe

02-21

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0

Prospectus Roundtable: Top 50 Prospects, Part I
by
Baseball Prospectus

01-06

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0

The Class of 2004
by
Jay Jaffe

01-23

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0

Breaking Balls: The Thrill is Gone
by
Derek Zumsteg

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January 24, 2008 12:00 am

Schrodinger's Bat: Simple Fielding Runs Version 1.0

0

Dan Fox

With a few minor tweaks, Simple Fielding Runs version 1.0 is ready for release.

"Let him hit it, you've got fielders behind you."
--Alexander Cartwright, attributed by Bob Chieger in Voices of Baseball


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June 28, 2007 12:00 am

Future Shock: The Draft Spectrum, Part Two

0

Kevin Goldstein

In the second part of his series, Kevin investigates where players come from across the defensive spectrum.

Last week, I began to delve into the concept of the draft spectrum. To recap: I decided to try going through today's players to see if we could identify any trends when it comes to where a player plays and how he entered the pro game (the term I'm using is "source"). The player pool I'm using here consists of 254 players, defined in this exercise as starters, chosen by selecting the player on each team with the most playing time at each defensive position. So 30 x 8 = 240 + 14 designated hitters = 254. Then I identified their source of entry into the pro game. Admittedly, this is a quick-and-dirty system. There are players who are normally starters but are not counted due to injury, and there have already been job changes that will lead to the pool having a turnover somewhere in the 10-20 percent range at the end of the season.

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February 13, 2007 12:00 am

Lies, Damned Lies: PECOTA Takes on Second Base Prospects

0

Nate Silver

Nate examines the curious discrepancy between conventional prospect rankings and PECOTA with regards to second basemen, and defends one of his projection system's favorite young players.

PECOTA sings a far more optimistic tune when it comes to second basemen. Kendrick was its #1 overall prospect last year, Dustin Pedroia was #4, and Barfield and Ian Kinsler ranked 13th and 14th, respectively. Second basemen don't do quite as well this year, but Pedroia is back, and joined by several other players who are sure to be ranked higher by PECOTA than by most other systems.

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October 14, 2006 12:00 am

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

0

Kevin Goldstein

Even Alexis Gomez came from somewhere (Kansas City). Kevin tells us how the Tigers and A's acquired the rest of their postseason difference-makers.

\nMathematically, leverage is based on the win expectancy work done by Keith Woolner in BP 2005, and is defined as the change in the probability of winning the game from scoring (or allowing) one additional run in the current game situation divided by the change in probability from scoring\n(or allowing) one run at the start of the game.'; xxxpxxxxx1160846402_18 = 'Adjusted Pitcher Wins. Thorn and Palmers method for calculating a starters value in wins. Included for comparison with SNVA. APW values here calculated using runs instead of earned runs.'; xxxpxxxxx1160846402_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160846402_20 = 'The number of double play opportunities (defined as less than two outs with runner(s) on first, first and second, or first second and third).'; xxxpxxxxx1160846402_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160846402_22 = 'Winning percentage. For teams, Win% is determined by dividing wins by games played. For pitchers, Win% is determined by dividing wins by total decisions. '; xxxpxxxxx1160846402_23 = 'Expected winning percentage for the pitcher, based on how often\na pitcher with the same innings pitched and runs allowed in each individual\ngame earned a win or loss historically in the modern era (1972-present).'; xxxpxxxxx1160846402_24 = 'Attrition Rate is the percent chance that a hitters plate appearances or a pitchers opposing batters faced will decrease by at least 50% relative to his Baseline playing time forecast. Although it is generally a good indicator of the risk of injury, Attrition Rate will also capture seasons in which his playing time decreases due to poor performance or managerial decisions. '; xxxpxxxxx1160846402_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160846402_26 = 'Average number of pitches per start.'; xxxpxxxxx1160846402_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160846402_28 = 'Singles or singles allowed.'; xxxpxxxxx1160846402_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160846402_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160846402_31 = 'The Baseline forecast, although it does not appear here, is a crucial intermediate step in creating a players forecast. The Baseline developed based on the players previous three seasons of performance. Both major league and (translated) minor league performances are considered.

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October 12, 2006 12:00 am

Player Profile

0

Marc Normandin

The A's second-best hitter showed considerable improvement in his second full season in the majors.

\nMathematically, leverage is based on the win expectancy work done by Keith Woolner in BP 2005, and is defined as the change in the probability of winning the game from scoring (or allowing) one additional run in the current game situation divided by the change in probability from scoring\n(or allowing) one run at the start of the game.'; xxxpxxxxx1160675573_18 = 'Adjusted Pitcher Wins. Thorn and Palmers method for calculating a starters value in wins. Included for comparison with SNVA. APW values here calculated using runs instead of earned runs.'; xxxpxxxxx1160675573_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160675573_20 = 'The number of double play opportunities (defined as less than two outs with runner(s) on first, first and second, or first second and third).'; xxxpxxxxx1160675573_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160675573_22 = 'Winning percentage. For teams, Win% is determined by dividing wins by games played. For pitchers, Win% is determined by dividing wins by total decisions. '; xxxpxxxxx1160675573_23 = 'Expected winning percentage for the pitcher, based on how often\na pitcher with the same innings pitched and runs allowed in each individual\ngame earned a win or loss historically in the modern era (1972-present).'; xxxpxxxxx1160675573_24 = 'Attrition Rate is the percent chance that a hitters plate appearances or a pitchers opposing batters faced will decrease by at least 50% relative to his Baseline playing time forecast. Although it is generally a good indicator of the risk of injury, Attrition Rate will also capture seasons in which his playing time decreases due to poor performance or managerial decisions. '; xxxpxxxxx1160675573_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160675573_26 = 'Average number of pitches per start.'; xxxpxxxxx1160675573_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160675573_28 = 'Singles or singles allowed.'; xxxpxxxxx1160675573_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160675573_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160675573_31 = 'The Baseline forecast, although it does not appear here, is a crucial intermediate step in creating a players forecast. The Baseline developed based on the players previous three seasons of performance. Both major league and (translated) minor league performances are considered.

The Baseline forecast is also significant in that it attempts to remove luck from a forecast line. For example, a player who hit .310, but with a poor batting eye and unimpressive speed indicators, is probably not really a .310 hitter. Its more likely that hes a .290 hitter who had a few balls bounce his way, and the Baseline attempts to correct for this.

\nSimilarly, a pitcher with an unusually low EqHR9 rate, but a high flyball rate, is likely to have achieved the low EqHR9 partly as a result of luck. In addition, the Baseline corrects for large disparities between a pitchers ERA and his PERA, and an unusually high or low hit rate on balls in play, which are highly subject to luck. '; xxxpxxxxx1160675573_32 = 'Approximate number of batting outs made while playing this position.'; xxxpxxxxx1160675573_33 = 'Batting average; hits divided by at-bats. In PECOTA, Batting Average is one of five primary production metrics used in identifying a hitters comparables. It is defined as H/AB. '; xxxpxxxxx1160675573_34 = 'Bases on Balls, or bases on balls allowed.'; xxxpxxxxx1160675573_35 = 'Bases on balls allowed per 9 innings pitched.'; xxxpxxxxx1160675573_36 = 'Batters faced pitching.'; xxxpxxxxx1160675573_37 = 'Balks. Not recorded 1876-1880.'; xxxpxxxxx1160675573_38 = 'Batting Runs Above Replacement. The number of runs better than a hitter with a .230 EQA and the same number of outs; EQR - 5 * OUT * .230^2.5.'; xxxpxxxxx1160675573_39 = 'Batting runs above a replacement at the same position. A replacement position player is one with an EQA equal to (230/260) times the average EqA for that position.'; xxxpxxxxx1160675573_40 = 'Breakout Rate is the percent chance that a hitters EqR/27 or a pitchers EqERA will improve by at least 20% relative to the weighted average of his EqR/27 in his three previous seasons of performance. High breakout rates are indicative of upside risk.

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Jim cleans up some old business, ponders the all-time greats at second base, and tries to avoid throwing things at the TV set.

\nMathematically, leverage is based on the win expectancy work done by Keith Woolner in BP 2005, and is defined as the change in the probability of winning the game from scoring (or allowing) one additional run in the current game situation divided by the change in probability from scoring\n(or allowing) one run at the start of the game.'; xxxpxxxxx1160158525_18 = 'Adjusted Pitcher Wins. Thorn and Palmers method for calculating a starters value in wins. Included for comparison with SNVA. APW values here calculated using runs instead of earned runs.'; xxxpxxxxx1160158525_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160158525_20 = 'The number of double play opportunities (defined as less than two outs with runner(s) on first, first and second, or first second and third).'; xxxpxxxxx1160158525_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160158525_22 = 'Winning percentage. For teams, Win% is determined by dividing wins by games played. For pitchers, Win% is determined by dividing wins by total decisions. '; xxxpxxxxx1160158525_23 = 'Expected winning percentage for the pitcher, based on how often\na pitcher with the same innings pitched and runs allowed in each individual\ngame earned a win or loss historically in the modern era (1972-present).'; xxxpxxxxx1160158525_24 = 'Attrition Rate is the percent chance that a hitters plate appearances or a pitchers opposing batters faced will decrease by at least 50% relative to his Baseline playing time forecast. Although it is generally a good indicator of the risk of injury, Attrition Rate will also capture seasons in which his playing time decreases due to poor performance or managerial decisions. '; xxxpxxxxx1160158525_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160158525_26 = 'Average number of pitches per start.'; xxxpxxxxx1160158525_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160158525_28 = 'Singles or singles allowed.'; xxxpxxxxx1160158525_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160158525_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160158525_31 = 'The Baseline forecast, although it does not appear here, is a crucial intermediate step in creating a players forecast. The Baseline developed based on the players previous three seasons of performance. Both major league and (translated) minor league performances are considered.

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March 22, 2006 12:00 am

Lies, Damned Lies: Rethinking Replacement Level

0

Nate Silver

Nate wonders if there's still more to be learned when it comes to considering replacement level talent.

To answer this simple question, I performed a search for players for all players since 1985 that met the following criteria:

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March 15, 2006 12:00 am

Future Shock: Taking A Step Back, Part Two

0

Kevin Goldstein

Kevin's scouting primer continues with a look at the defensive tools.

After taking a look at how scouts evaluate players when they have a bat in their hands, today I'll look at the "non-bat" tools, and how those tools are weighed once you have a complete feeling for a player's abilities.

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March 7, 2006 12:00 am

Doctoring The Numbers: The Draft, Part Eight

0

Rany Jazayerli

The Good Doctor returns with Part Eight of his draft study, focusing on college hitters.

Last time, we looked at the relative merits of high school players by position, ending with this chart:

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December 12, 2005 12:00 am

The Class of 2006

0

Jay Jaffe

Jay Jaffe uses JAWS to look at the newly eligible hitters on this year's Hall of Fame ballot.

Clay Davenport's Wins Above Replacement Player (WARP) figures make an ideal tool for this endeavor because they normalize all performance records in major-league history to the same scoring environment, adjusting for park effects, quality of competition and length of schedule. All pitchers, hitters and fielders are thus rated above or below one consistent replacement level, making cross-era comparisons a breeze. Though non-statistical considerations--awards, championships, postseason performance--shouldn't be left by the wayside in weighing a player's Hall of Fame case, they're not the focus here.

Election to the Hall of Fame requires a player to perform both at a very high level and for a long time, so it's inappropriate to rely simply on career WARP (which for this exercise refers exclusively to the adjusted-for-all-time version, WARP3). In past years I identified each player's peak value by his best five consecutive seasons, with allowances made for seasons lost to war or injury. That choice was an admittedly arbitrary one, and for the 2006 ballot I've revised the methodology to instead use each player's best seven seasons without concern as to whether they're consecutive or not. It's a subtle change that doesn't have a huge impact, but it does require less manual labor to determine the injury and war exceptions, a welcome development from where I sit. Effectively, we're double-counting more of a player's best seasons, but given what we know about pennants added and the premium value of star talent, individual greatness can have a nonlinear effect on a team's results both in the standings and on the bottom line.

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September 22, 2005 12:00 am

Lies, Damned Lies: A New Look at Aging

0

Nate Silver

Nate uses Joe Crede and poker as points of departure to investigate when position players peak.

This week’s column was originally supposed to be a break from the usual LDL routine, inspired by Tuesday night’s fantastic white Sox/Indians game, which I got to take in with New York Sun buddy Tim Marchman. Tim and I have some mysterious, voodoo-like power when we go to Sox games together. Earlier this year,

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September 13, 2005 12:00 am

Doctoring The Numbers: The Draft, Part Seven

0

Rany Jazayerli

Rany returns with a look at the value of high-school hitters drafted between 1984 and 1999.

Using the technique described in the last part of this draft series, here's a breakdown of draft pick value for college and high school players, separated into pitchers and regulars, from 1984 through 1999:

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