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Articles Tagged High School Players 

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09-25

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Area Code Games
by
Chris Rodriguez

08-31

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13

108 Stitches: The Importance of the Area Code Games
by
Dan Evans

10-14

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39

Doctoring The Numbers: Starting Them Young, Part Two
by
Rany Jazayerli

10-13

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57

Doctoring The Numbers: Starting Them Young, Part One
by
Rany Jazayerli

06-04

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28

Future Shock: Mock Draft 2010
by
Kevin Goldstein

06-04

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Future Shock: Mock Draft 2008
by
Kevin Goldstein

08-19

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Lies, Damned Lies: Slotto Bonanzas, Part Two
by
Nate Silver

06-28

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

10-16

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Future Shock: Monday Morning Ten-Pack
by
Kevin Goldstein

10-14

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

10-11

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Remembering Buck O'Neil
by
Alex Belth

06-05

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Doctoring The Numbers: The Draft, Part 12
by
Rany Jazayerli

06-02

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Doctoring The Numbers: The Draft, Part 11
by
Rany Jazayerli

03-27

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Future Shock: How Do Teams Draft?
by
Kevin Goldstein

09-13

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

08-02

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

07-13

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Lies, Damned Lies: Book Review, Scout's Honor
by
Nate Silver

06-09

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

06-02

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

05-25

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

05-19

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

05-13

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Doctoring The Numbers: The Draft
by
Rany Jazayerli

07-09

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Lies, Damned Lies: Digging in the Backyard
by
Nate Silver

04-03

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Minor League Q&A
by
Craig Elsten

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September 25, 2013 6:00 am

Area Code Games

0

Chris Rodriguez

Video and reports on some of the top prep players in the nation.

Here are five more hitters who shined in front of hundreds of scouts at the Area Code Games a couple weeks back. You can see part one here.

Blake Wiggins, 3B/ C/OF, Yankees #14

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August 31, 2012 5:00 am

108 Stitches: The Importance of the Area Code Games

13

Dan Evans

The Area Code Games offer the best opportunity for MLB officials to evaluate amateur talent. Our resident former GM explains all.

Nearly 600 of baseball's top amateur talent evaluators converged on historic Blair Field in Long Beach, California earlier this month for the 26th Annual Area Code Games. For the 240 high school players who gathered from all over the nation, it was the toughest job interview they had ever experienced.

"A player cannot attend the Area Code Games and hide," said UCLA Head Coach John Savage.

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In part two, Rany examines just how important age is for a draft pick.

Yesterday’s column made the claim that small differences in age among high school hitters can have a dramatic impact on their return as draft picks. Today, I intend to prove that claim.

Read the full article...

One of BP's co-founders returns to reveal an important amateur draft inefficiency.

Everyone missed on Mike Trout. Don’t get me wrong: Trout was a well-regarded player headed into the 2009 draft, a certain first-round talent. But he wasn’t—yet—a phenom. Everyone liked Trout; it’s just that no one loved him. Baseball America ranked him as the 22nd-best player in the draft. No one doubted his athleticism or his work ethic; a lot of people doubted the level of competition he faced as a high school player from rural New Jersey. The Angels drafted him with the 25th pick overall, and they’ll tell you today that they knew he was destined to be a special player. What they won’t tell you is that they had back-to-back picks at #24 and #25, and they announced Randal Grichuk’s name first.

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BP's in-house guru takes his shot at projecting how team's top picks go next week.

1. Washington Nationals: This is now a no-brainer. Over the course of the spring, we've slowly gone from "Will they take Harper?" to "Will they sign Haper?" to "How much will they pay Harper?" He's going No. 1, and you could even end up seeing a creative deal that, on paper, gets him more than Stephen Strasburg received.

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Looking into the crystal ball to see who drops where.

With 24 hours to go before the selections begin, the draft remains a muddled mess, making the process of doing a mock a series of hedged wagers. "This is easily one of the most unpredictable first rounds I've ever seen," said one team official. Basically, the draft pool has two clumps of players, one made up of the top ten, followed by a larger group of up to 40 players. With even the first overall pick still up in the air, any one last-minute flip could change the board dramatically.

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August 19, 2007 12:00 am

Lies, Damned Lies: Slotto Bonanzas, Part Two

0

Nate Silver

Nate turns his attention to the individual big bonus players from the last decade, and determines whether their teams would do it all over again.

What follows is a comprehensive roster of all players between 1998 and 2006 who were drafted with one of the first 100 selections and who also went for at least $500,000 over slot, considering both their signing bonus and any guaranteed MLB money. I've used the 2006 slot values for all seasons from 2000-2006, as MLB has generally been very successful at containing draft inflation during this period (in fact, the draft slots went down in 2007). The slots do appear to have been a little lower in 1999 and 1998, and so I've scaled those back by five percent and 10 percent respectively, rounding off to the nearest "big" number. I've also indicated those cases where the player's alternative careers in football or basketball could have influenced his signing bonus. Finally, I've posed a simple question: If the team had perfect knowledge of what that player was going to do, would they commit the same money again?

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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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October 16, 2006 12:00 am

Future Shock: Monday Morning Ten-Pack

0

Kevin Goldstein

Kevin checks out the newsmakers in the winter leagues.

\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.'; xxxpxxxxx1160988517_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.'; xxxpxxxxx1160988517_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160988517_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).'; xxxpxxxxx1160988517_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160988517_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. '; xxxpxxxxx1160988517_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).'; xxxpxxxxx1160988517_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. '; xxxpxxxxx1160988517_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160988517_26 = 'Average number of pitches per start.'; xxxpxxxxx1160988517_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160988517_28 = 'Singles or singles allowed.'; xxxpxxxxx1160988517_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160988517_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160988517_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 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 11, 2006 12:00 am

Remembering Buck O'Neil

0

Alex Belth

A great ambassador for the game--and for humanity--passed away last week.

\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.'; xxxpxxxxx1160583428_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.'; xxxpxxxxx1160583428_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160583428_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).'; xxxpxxxxx1160583428_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160583428_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. '; xxxpxxxxx1160583428_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).'; xxxpxxxxx1160583428_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. '; xxxpxxxxx1160583428_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160583428_26 = 'Average number of pitches per start.'; xxxpxxxxx1160583428_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160583428_28 = 'Singles or singles allowed.'; xxxpxxxxx1160583428_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160583428_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160583428_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. '; xxxpxxxxx1160583428_32 = 'Approximate number of batting outs made while playing this position.'; xxxpxxxxx1160583428_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. '; xxxpxxxxx1160583428_34 = 'Bases on Balls, or bases on balls allowed.'; xxxpxxxxx1160583428_35 = 'Bases on balls allowed per 9 innings pitched.'; xxxpxxxxx1160583428_36 = 'Batters faced pitching.'; xxxpxxxxx1160583428_37 = 'Balks. Not recorded 1876-1880.'; xxxpxxxxx1160583428_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.'; xxxpxxxxx1160583428_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.'; xxxpxxxxx1160583428_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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June 5, 2006 12:00 am

Doctoring The Numbers: The Draft, Part 12

0

Rany Jazayerli

Rany closes out his epic series, identifying the new inefficiency in the market before tomorrow's Rule 4 draft.

Well, there's no reason to think that change suddenly ground to a halt in 1999, and the data from a decade ago may hold little bearing on the decisions that will be made next Tuesday.

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