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Articles Tagged Jeremy Giambi 

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10-16

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Future Shock: Monday Morning Ten-Pack
by
Kevin Goldstein

10-16

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Prospectus Today: LCS, Day Six
by
Joe Sheehan

10-14

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

10-14

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Prospectus Today: LCS, Day Four
by
Joe Sheehan

10-14

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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

10-12

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Prospectus Today: The Games Go On
by
Joe Sheehan

10-12

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Player Profile
by
Marc Normandin

10-11

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Remembering Buck O'Neil
by
Alex Belth

10-11

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Prospectus Today: LCS, Day One
by
Joe Sheehan

10-09

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Completely Random Statistical Trivia
by
Keith Woolner

10-09

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Prospectus Today: Division Series, Day Six
by
Joe Sheehan

10-07

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Prospectus Today: Division Series, Day Four
by
Joe Sheehan

10-06

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Prospectus Today: Division Series, Day Three
by
Joe Sheehan

10-06

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Prospectus Matchups: October Musings
by
Jim Baker

10-05

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Prospectus Today: Division Series, Day Two
by
Joe Sheehan

02-22

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

01-25

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Transaction Analysis: The Easts
by
Christina Kahrl

01-23

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Prospectus Feature: Breaking Out
by
Nate Silver

07-01

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The Week in Quotes: June 24-30, 2002
by
Derek Zumsteg

06-10

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The Daily Prospectus: Aftermath
by
Joe Sheehan

06-10

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The Daily Prospectus: Aftermath
by
Joe Sheehan

05-24

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Transaction Analysis: May 20-22, 2002
by
Christina Kahrl

05-01

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Prospectus Feature: The Muser Era Ends
by
Rany Jazayerli

12-14

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6-4-3: Gratitude and Relief
by
Gary Huckabay

10-10

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Playoff Prospectus
by
Gary Huckabay

10-12

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Call It In The Air!
by
Dave Pease

02-25

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Transaction Analysis: February 16-24, 2000
by
Christina Kahrl

02-02

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Top 40 Prospects of 1999
by
Rany Jazayerli

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October 7, 2006 12:00 am

Prospectus Today: Division Series, Day Four

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Joe Sheehan

The A's won a Division Series, and they did it their way. The Tigers are one win away from joining them in an ALCS matchup no one predicted.

\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.'; xxxpxxxxx1160276734_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.'; xxxpxxxxx1160276734_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160276734_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).'; xxxpxxxxx1160276734_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160276734_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. '; xxxpxxxxx1160276734_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).'; xxxpxxxxx1160276734_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. '; xxxpxxxxx1160276734_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160276734_26 = 'Average number of pitches per start.'; xxxpxxxxx1160276734_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160276734_28 = 'Singles or singles allowed.'; xxxpxxxxx1160276734_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160276734_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160276734_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 6, 2006 12:00 am

Prospectus Today: Division Series, Day Three

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Joe Sheehan

The Yankees continued their run through the ... hey, not so fast! In San Diego, the Cardinals continued to make a statement about the importance of home-field advantage, while in New York the Mets were the one team to keep order in the first two games.

\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.'; xxxpxxxxx1160157644_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.'; xxxpxxxxx1160157644_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160157644_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).'; xxxpxxxxx1160157644_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160157644_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. '; xxxpxxxxx1160157644_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).'; xxxpxxxxx1160157644_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. '; xxxpxxxxx1160157644_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160157644_26 = 'Average number of pitches per start.'; xxxpxxxxx1160157644_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160157644_28 = 'Singles or singles allowed.'; xxxpxxxxx1160157644_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160157644_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160157644_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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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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October 5, 2006 12:00 am

Prospectus Today: Division Series, Day Two

0

Joe Sheehan

The Play is the talk of the water coolers, but plenty of other things happened on an abbreviated second day.

\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.'; xxxpxxxxx1160071649_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.'; xxxpxxxxx1160071649_19 = 'Support Neutral Lineup-adjusted Value Added (SNVA adjusted for the MLVr of batters faced) per game pitched.'; xxxpxxxxx1160071649_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).'; xxxpxxxxx1160071649_21 = 'The percentage of double play opportunities turned into actual double plays by a pitcher or hitter.'; xxxpxxxxx1160071649_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. '; xxxpxxxxx1160071649_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).'; xxxpxxxxx1160071649_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. '; xxxpxxxxx1160071649_25 = 'Batting average (hitters) or batting average allowed (pitchers).'; xxxpxxxxx1160071649_26 = 'Average number of pitches per start.'; xxxpxxxxx1160071649_27 = 'Average Pitcher Abuse Points per game started.'; xxxpxxxxx1160071649_28 = 'Singles or singles allowed.'; xxxpxxxxx1160071649_29 = 'Batting average; hits divided by at-bats.'; xxxpxxxxx1160071649_30 = 'Percentage of pitches thrown for balls.'; xxxpxxxxx1160071649_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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February 22, 2004 12:00 am

Prospectus Roundtable: Top 50 Prospects, Part II

0

Baseball Prospectus

Wright or Marte, Marte or Wright. I love 'em both. I've put Andy Marte ahead for the moment, because of the 10-month age difference and because scouts seem to like him a lot more, but I really feel strongly that David Wright's as complete a prospect as there is in the game. I'd love to hear comments comparing the two, and Nate, I'd love to see what their PECOTA comps look like. Nobody else is that impressive. Dallas McPherson put up some serious numbers last year, and while some of that was in The Hangar in Rancho Cucamonga, he hit .314/.426/.569 in Arkansas. He doesn't have a great defensive reputation, but it's not terrible either, and he clearly outhit everyone else on this list. I don't know if anyone else deserves Top 50 consideration. I know people love the Greek God of Walks, but he hit .165/.295/.248 in Triple-A, over a 32-game sample. Of course, his full-season OBP was still .446, so... Chad Tracy hit .324 and his defense took a big step forward, but he doesn't do much more than hit singles, and it was Tucson. I respect that he's had two good seasons in a row, but he was in El Paso in 2002, so I'm not sure that means anything either. And as much as I hyped him a year ago, I have to concede that Brendan Harris may not be quite as good as I thought he was. But he's still a better prospect than almost anyone gives him credit for.

Baseball Prospectus Top 40 Prospects Roundtables:
2003 Part II
2003 Part I
2001


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Howdy gang, nothing like spending five hours typing up the index for this year's edition of Baseball Prospectus to make me desperately hungry to dive right into playing catch-up on real-time baseball news. Yes, Transaction Analysis is long overdue, and for that I apologize, having spent the intervening time working with our writing team and the incomparably enthusiastic Jonah Keri to get this year's book out the door. If you can forgive me that, you'll also have to forgive me this temporary break from format, as I run down the most-notable moves made over the last couple of months, going by divisional pairs (Easts, Centrals, and Wests) to get caught up and resume your regularly scheduled TA mayhem by next week.

Howdy gang, nothing like spending five hours typing up the index for this year's edition of Baseball Prospectus to make me desperately hungry to dive right into playing catch-up on real-time baseball news. Yes, Transaction Analysis is long overdue, and for that I apologize, having spent the intervening time working with our writing team and the incomparably enthusiastic Jonah Keri to get this year's book out the door. If you can forgive me that, you'll also have to forgive me this temporary break from format, as I run down the most-notable moves made over the last couple of months, going by divisional pairs (Easts, Centrals, and Wests) to get caught up and resume your regularly scheduled TA mayhem by next week.

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In an article that appeared last week on ESPN.com, Peter Gammons provided a list of 20 players whom respondants to an informal straw poll described as candidates for a breakout season. The list, derived from a survey of major league executives, included a mix of pitchers and hitters, five-tool talents and makeup guys, united only in their ability to tease hibernating fantasy leaguers into dreams of greener days ahead. If one needs any reminder that lists like these are little more than a grownup's version of pin-the-tail-on-the-donkey, it's worth reviewing a similar list that Gammons produced last year.

In an article that appeared last week on ESPN.com, Peter Gammons provided a list of 20 players whom respondants to an informal straw poll described as candidates for a breakout season. The list, derived from a survey of major league executives, included a mix of pitchers and hitters, five-tool talents and makeup guys, united only in their ability to tease hibernating fantasy leaguers into dreams of greener days ahead.

If one needs any reminder that lists like these are little more than a grownup's version of pin-the-tail-on-the-donkey, it's worth reviewing a similar list that Gammons produced last year. That list includes roughly equal representation of the good (Alfonso Soriano and Derek Lowe), the bad (J.D. Drew), and the ugly (Juan Uribe), as well as four players whose performances were so impressive that they made repeat appearances on this year's list.

Now, none of this is meant to be a knock on Gammons, or the lists he has compiled. Everybody likes to talk about breakout candidates this time of year, ourselves included (Eddie Yarnall, anyone?). Having formerly moonlighted as a daily team correspondent for another baseball website, I can attest to the fact that virtually every player provides at least some excuse each winter for gushing commentary, delusions of grandeur, or other forms of irrational exuberance.

As it happens, however, we're unrolling a new forecasting system at BP this year--one that is also preoccupied with the question of breakout candidates. The PECOTA system--short for Player Empirical Comparison and Optimization Test Algorithm--seeks to identify potential breakouts by comparing a player against a database of his historical peers. In so doing, it comes up with an objective estimate of the probability that a player will display marked improvement in the upcoming season (defined as an increase of at least 20% in his Equivalent Runs per plate appearance, or a decrease of at least 20% in his PERA, relative to a weighted average of his previous three years of performance). We refer to this estimate as a player's Breakout score. Readers interested in a more extensive treatment of the PECOTA system will find it in this year's book, and in the PECOTA glossary provided here.

One brief caveat: the PECOTA system is new technology. That doesn't mean that we stole it from the Raelians, or that we haven’t tested it thoroughly. But sometimes PECOTA provides us with definitive and unexpected answers, and we need to work backwards to try and explain why they came about. That's a bastardization of the scientific method, and I'll ask that you'll excuse me as I run through the hitters on Gammons' list.

Rank on Gammons List, Player, PECOTA Breakout Score

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July 1, 2002 7:41 pm

The Week in Quotes: June 24-30, 2002

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Derek Zumsteg

STRIKE! STRIKE! "If you have kids who might [grow up to] be major league baseball players, we're fighting for your kids, possibly. If I work for your newspaper and you're in the union fighting for your equality and rights, sure I would strike, and so would you..." --Barry Bonds, Giants outfielder

STRIKE! STRIKE!

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June 10, 2002 9:52 am

The Daily Prospectus: Aftermath

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Joe Sheehan

Despite the odd Jeremy Giambi for John Mabry spot, the A's are on an offensive tear

About three weeks ago, the A's made the weirdest trade of the year, swapping left fielder and OBP guy Jeremy Giambi to the Phillies for fringe major leaguer John Mabry. There seemed to be little justification for the trade; the stated reasons—defense, Mabry's clubhouse presence, the desire to clear at-bats for Adam Piatt—were weak, and the gap in talent between the two players is wide.

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Since the trade, the A's are 13-5, and following a sweep of the Astros this weekend they're just six games behind the Mariners in the AL West. Admittedly, this run came against a very weak schedule-11 games against the Orioles and Devil Rays-but at the 62-game mark, the Athletics are a hell of a lot closer to a playoff spot than they were at the same point one year ago.

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May 24, 2002 11:17 am

Transaction Analysis: May 20-22, 2002

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Christina Kahrl

Nevertheless, in the wake of the most bizarre deal we've seen in a very long time, I couldn't help myself; I peeked around. Now, I have a lot of respect for Rob Neyer, and for Rob's work. As a fellow product of the analysis revolution of the '80s, I suspect we share a basic philosophy of trying to inject some element of quantitative analysis to provide better qualitative commentary. That said, I think any attempt to quantitatively assess the trade of Jeremy Giambi--regardless of your opinion of Win Shares and their utility--ignores two basic problems.

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There was little joy in watching the final, desperate days of the Tony Muser Era arrive at their inevitable conclusion. Nor was there any sense of anger or frustration from knowing how much opportunity has been wasted while we waited for the axe to fall.

Finally.

There was little joy in watching the final, desperate days of the Tony Muser Era arrive at their inevitable conclusion. Nor was there any sense of anger or frustration from knowing how much opportunity has been wasted while we waited for the axe to fall.

There was only relief. Relief, and closure.

The players can finally prepare for each game without wondering whether the man who picks the lineup today will do the same tomorrow. The fans can once again root for their favorite team without that awful feeling of conflict that arises when you feel winning the day's game is no longer in your team's best interests. Even Muser can finally start making arrangements for a future that he has long known would come.

We all deserved better than this, though, no one more than Muser himself. If there's one lesson to learn from this, it's that you really can kill with kindness. Allard Baird stuck with Muser to the bitter end for one simple reason: he liked him. Sure, Baird also thought that Muser was the right man for the job, blah, blah, blah, but in the end it was really all about friendship, and all the qualities--trust, faith, and loyalty--that go along with it.

That friendship didn't help Muser one bit. Instead, it may have ruined him.

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