GM Report Card – JP Ricciardi

In December 2002 I can vividly remember calling friends and family, excited that the Phillies had just acquired Kevin Millwood.  With the imminent return of Mike Lieberthal, Johnny Estrada had become an expendable commodity and Millwood had been a key cog in the Braves rotation.  Two years later, my evaluation of the trade had changed.  Millwood had not been the answer to the Phillies pitching woes and Estrada turned out to be the lone Braves representative on the all-star team.
Of course hindsight is always 20/20 but general managers are, more often than not, evaluated by the production levels of the players they acquire and send away as well as how these production levels translate to wins.  Millwood did not meet expectations while Estrada exceeded them; therefore, it was Ed Wade’s fault for making a bad move.
With this in mind I decided to begin a bi-weekly or monthly feature evaluating general managers.  The method is somewhat of a combination of Geoff Young’s trade-tracking chapter in the 2008 Ducksnorts Baseball Annual, and Dan Levitt’s analysis of Terry Ryan at Baseball Analysts.  Win Shares is the statistic used to evaluate moves and they are assigned to all players acquired and lost during a GMs tenure.  The major difference between what I will do here and what was done in Levitt’s wonderful analysis is that he assigned Win Shares to lost players for every subsequent year; I am only assigning them for the years on the first new team they join.
For instance, in the Millwood/Estrada deal, Ed Wade would be debited for Estrada’s tenure with just the Braves.  When the Braves sent Estrada to the Diamondbacks, he then became a player lost by John Scheurholz.  Otherwise, the evaluations are pretty straight-forward.  For those unfamiliar with Win Shares, it is a statistic created by Bill James and explained in the self-titled book by James and Jim Hentzler and it measures the contribution of a player to his team’s total wins.  3 Win Shares = 1 Win; 20+ is an all-star season and 30+ is an MVP season.
To kick off this series of evaluations I chose to look at J.P. Ricciardi, GM of the Toronto Blue Jays.
Meet J.P.
A disciple of Billy Beane, Ricciardi took over the Toronto reigns in November 2001.  He replaced Gord Ash, who had more recently found himself embroiled in the Shouldergate controversy; he also hired a manager that feigned fighting in Vietnam.  The team had struggled to finish higher than third place and hoped that Ricciardi’s knack for quantifying players would pay off major dividends.
Now in the midst of his eighth season at the helm, the team is still yet to experience the success envisioned at the time of his hiring.  Sure, they finished in second place in 2006, but it did not result in a playoff berth.  In fact, they have not been in the playoffs since 1993, when some guy I have erased from memory hit a world series winning walkoff home run.
Overall Results
Before looking at each area of moves on their own, here are the overall results of his moves:

TYPE

WS ACQ.

WS LOST

NET

WINS/YR

Trades

272

378

-106

-5.89

Free Agents

327

319

+8

+0.44

Waivers

42

47

-5

-0.28

Rule V

14

2

+12

+0.67

Overall

655

746

-91

-5.06

As mentioned above, one win equals three WS.  For example, based on the free agents Ricciardi has signed, as opposed to those released or lost, the net of +8 WS equates to about three added wins.  Over the course of his six years he has added about a half-win per season in free agent moves.
Elsewhere, he has not made many Rule V moves or waiver claims, resulting in very little net Win Shares.  In trades, though, Ricciardi has bombed.  His trades have cost the Blue Jays approximately 8 wins per year.  Now this is contingent upon the traded away players performing the same way in Toronto as they did in their new destination; however, as mentioned at the start of the evaluation, whether fair or not, this is how GMs are evaluated.
Free Agent Signings
Ricciardi has received 42 WS, or 14 wins, from the free agents he has signed, starting in November 2001.  During his tenure these signings have added just about 0.5 wins per season. 
Click here to view the results for all of his free agent signings.
Of the forty signings, fourteen resulted in ten or more WS; only one, Victor Zambrano, produced negatively.  Frank Catalanotto is far and away the best signing he made, providing the team with around 17 total wins, or 4/yr.  The next highest is Gregg Zaun, previously a backup catcher who recently found himself the primary backstop for the Jays.
The highest single-season signing is a tie between BJ Ryan in 2006 and Frank Thomas in 2007.  Each had seventeen shares and contributed as much as six whole wins in the respective seasons.
Free Agents Lost
This category not only refers to players lost to free agency but also those who were released.  While Ricciardi’s 40 signings produced an aggregate 42 WS, the 29 players let go produced 47 for their new team.  Now, as I mentioned earlier, I only look at the very next team for a lost player.  Doug Davis was released and signed with the Brewers; I debit Ricciardi all of Davis’s WS while on the Brewers.  Once he joined the DBacks, he becomes Brewers GM Doug Melvin’s “problem.”
Of the 29 lost or released, five produced WS totals of 30 or more: Esteban Loaiza (30), Kelvim Escobar (51), Carlos Delgado (31), Chris Carpenter (48), and Doug Davis (36).  Looking at the yearly averages: Loaiza (15/yr), Escobar (13/yr), Delgado (31/yr), Carpenter (12/yr), Davis (9/yr).
Click here to view the results for all free agents lost/players released.
Trades
Ricciardi has made 29 significant trades from 2002-2007; trades that resulted in at least one win share on either his, or the other, side.  A trade was considered insignificant if nobody made the major leagues or both parties summed to 0 WS.  Overall, his trades have been the worst facet of his moves.  The players acquired produced an aggregate 272 WS–91 wins–which comes to +15 wins/yr.
The players lost, however, produced 378 WS for their new clubs.  378 WS = 126 wins = -21 wins/yr.  Though rounded a bit, he brought in 15 wins/yr with these trades but lost 21 wins/yr.  The net of -5.89, or -6 really leaves a significant stain on his Toronto resume.
The best trade pulled off involved getting Eric Hinske and Justin Miller in exchange for Billy Koch on 12/7/2001.  Koch played just one year with Oakland, bringing in 19 WS; Hinske and Miller combined for 65 WS.
He also made two really bad trades that, on their own, account for much of the net loss.  Both trades involved ridding the Jays of major league commodities for prospects that never cut the mustard.  The first, completed just six days after the Hinske deal on 12/13/2001, saw Luke Prokopec head to Toronto in exchange for Cesar Izturis and Paul Quantrill.  Prokopec contributed 0 WS in a brief 2001 stint while Quantrill and Izturis combined for 66 WS from 2001-2006.  The other one, completed almost a year later on 12/15/2002, saw Jason Arnold join the Jays while Felipe Lopez headed to Cincinnati.  Essentially the same story, Arnold contributed nothing while Lopez produced 43 WS from 2003 to 2006.
In terms of trades, commenter Darren pointed out that certain players were being double-counted; he was correct and these are now fixed.  What he meant can be explained in the Bobby Kielty deals; the Jays traded Shannon Stewart for Kielty mid-2003 and I counted Kielty’s one half-year with the Jays and Stewart’s 3+ years with the Twins.  In the end this gave Kielty 4 WS for JP and Stewart -39 WS against JP.  This was not correctly done on my part because Kielty was traded the next year for Ted Lilly.  At that point, Stewart’s WS with the Twins should have stopped and it would then be Kielty vs. Ted Lilly.  So, the Stewart-Kielty would be +4 vs -9 and then the Kielty-Lilly would remain the same.  Otherwise, it would be Stewart counting against Kielty even though the K-Man was not there anymore.  This did not happen too often in the trade log but I did make the corrections reflected in the results.
Click here to see the results for all players acquired and lost through trades.
Waiver Wire
Another way to acquire free talent or get rid of the undesirables is the waiver wire.  Ricciardi was essentially even in this acquisition aspect, bringing in 42 WS and giving away 47.  His most productive waiver claims were Pete Walker (12) and Frank Menechino (11).  Of players he lost to waivers, Scott Eyre produced 19 WS for the Giants and Bruce Chen chimed in with 16 for the Orioles.
Click here to see the results for his waiver moves.
Rule V
Ricciardi’s Rule V selections and losses were often than not returned; in other cases, they simply never amounted to anything.  The only three Rule V picks that were significant resulted in 14 WS gained and 2 WS lost.  Though a small sample this happened to be his best area.  Corey Thurman gave him 4 WS in 2001 and Aquilino Lopez gave him 10 in 2002; Matt Ford contributed 2 WS to Milwaukee in 2002.
Position Evaluation
Another interesting way to analyze his moves is to look at how he fared by position.  Perhaps he had a knack for finding relievers but struggled to sign quality shortstops.  Here are the results:

TYPE

WS ACQ.

WS LOST

NET

WINS/YR

SP

125

267

-142

-8

RP

172

122

+50

+3

C

76

13

+63

+4

1B

41

32

+9

+0.5

2B

22

89

-67

-4

SS

33

94

-61

-4

3B

166

17

+149

+9

OF

20

112

-92

-5

These numbers are much more rounded than the overall results but you can see Ricciardi has fared best with third baseman and worst with starting pitchers and outfielders.  In fact, 14 of those 20 WS for outfielders belong to Matt Stairs; most of the other OFs he acquired did nothing. 
Conclusion
I hope this shed some light on what Ricciardi has done and how it effected his team’s success.  There is still room to improve the system and one such facet I am considering would be to compare the lost players to their replacements; for instance, Orlando Hudson was traded away but how did he compare to the incumbent second baseman?  Perhaps he would not count as much against Ricciardi when we see Aaron Hill’s numbers. 
Until we have a bunch of these analyses conducted we cannot rank the GMs but, based on Win Shares, Ricciardi certainly will not be amongst the leaders as he has cost his team about five wins per season with his transactions.
I am still deciding who the next GM for this should be, so if anyone has thoughts, leave them in the comments section.  I’d prefer it be a somewhat current time frame and, whoever you pick, also specify the team; don’t just say Pat Gillick, say Gillick with the Mariners or Gillick with the Blue Jays, etc.

Low Risk, Any Reward in 2008?

This past week I was lucky enough to have my article “Low Risk, Any Reward?” featured in the SABR statistical newsletter, By the Numbers. The article, which can be seen here, looks at the low-risk pitcher signings from 2002-2007 and analyzes whether or not the likelihood of a reward is worth the risk.
In case you choose not to read the article–which would be a shame since there are some other great articles as well–I defined a low-risk pitcher signing by parameters in contract duration and salary. For duration, the following qualified:
a) 1-yr deal
b) 1-yr deal w/option
c) Minor League deal
d) Waiver claim
With regards to salary, anything accounting for a maximum of 5.25% of the given team’s salary qualifies. The percentage is used rather than a raw figure to level the field of play between teams with significant payroll discrepancies. For example, Randy Wolf was signed to a 4.75 mil, one-yr deal by the Padres. The Padres have a payroll of 73.68 mil, meaning that Wolf accounts for 6.4% of their entire payroll. He would not qualify by these standards. The same could be said for Livan Hernandez who, despite signing just a 1-yr, 5 mil deal, takes up just under 10% of the Twins payroll. Now, the Mark Prior signing of 1-yr at 1 mil, by the Padres, does qualify. The ONLY time I broke from these parameters dealt with the Florida Marlins, who have an absolutely ridiculous 21 mil payroll.
A little over a month into the season I thought it might be interesting to take a look at this year’s crop of low-risk pitchers. Since we are still dealing with small sample sizes I will refrain from evaluating the signings via dollars per win, as in the article, but we can still see which players have been worth the risk thus far.
By my count, there were 58 low-risk pitcher signings coming into this season; so far just 32 have pitched. The others are either injured or still in the minor leagues.
In the article, I first ranked the players by VORP–Value Over Replacement Player–which, for pitchers, looks at the amount of runs saved relative to a replacement level player given the same amount of opportunities. Once they were compiled, the conversion rate of 10 VORP runs = 1 WAR (Win Above Replacement) helped in determining just how many wins a given pitcher contributed above a replacement level pitcher.
Now, in checking who has truly helped we will compare these WAR totals to the individual league average for all pitchers, not just low-risk pitchers. In the National League, the current average WAR is 0.24; in the American League it is 0.20. Essentially, as of right now, the average major league pitcher is contributing somewhere between 0.20 and 0.24 wins above, say, what Kevin Jarvis or Matt Beech would contribute. With this in mind, here are the low-risk pitchers above their league’s average:
National League
1) Odalis Perez, 0.95
2) Shawn Chacon, 0.94
3) Wil Ledezma, 0.77
4) Ron Villone, 0.69
5) Joe Beimel, 0.64
6) Doug Brocail, 0.63
7) Mark Hendrickson, 0.53
8) Rudy Seanez, 0.51
9) Phil Dumatrait, 0.48
10) Jeremy Affeldt, 0.42
11) Kyle Lohse, 0.41
American League
1) Sidney Ponson, 0.53
2) Jorge Julio, 0.27
The small number of AL low-risk pitchers that have above average WAR totals initially strikes me as odd; however, the fact that the two come in the forms of Sidney Ponson and Jorge Julio makes it even odder! Of the 58 low-risk signings, the NL had 36 to the 22 in the AL, so it was not as if the AL only had six such signings.
I am going to revisit this at season’s end in order to apply the same dollars per win method as in the original article but, as of right now, by evaluating moves based on approximately 40 team games, the above players have been worth the risk.
In the cases of Odalis Perez, Shawn Chacon, and Wil Ledezma, they have really been worth the risk; those three fall into the top 30 of the entire National League.

Catching Up With a 99-Year Old Veteran

In case it is not yet known I am currently in the research stage of writing a book on the storied career of former major leaguer Bucky Walters.  It is a dual-story, actually, involving not just Bucky’s career but also the fifteen-year effort of his grandson, Jeffrey, to get Bucky inducted into the Hall of Fame.  The book is not necessarily advocating Bucky’s induction but what both Bucky and Jeffrey accomplished is remarkable and deserves to be more commonly known.  In conducting my research I came into possession of a scrapbook made by Bucky’s wife as well as newspaper clippings from the ’30s and ’40s, and letters to Bucky from some pretty prominent baseball people.
Still missing first-hand accounts, I sought out any former teammates.  Luckily, Jeffrey and I found that Bill Werber, a ten-year veteran of the Red Sox, Athletics, and Reds, was still alive.  Werber, who helped spearhead one of the most underrated infields of all time (Frank McCormick, Lonnie Frey, Bill Werber, Billy Meyers), is currently 99 years old and living in a retirement home in North Carolina. 
I called him this past week in order to conduct an interview about Bucky but, in the end, my fascination split its interests between Bucky and Werber himself; I went from asking questions for the book to just talking to a former MVP-candidate.  It is always important to record these voices since they won’t be with us much longer and so I decided to post portions of the interview transcript here, hoping that you will find some of this as interesting as I did while speaking with him.  The hardest part of this interview was knowing when to chime in with another question; while Werber is still very cognizant it became very hard to tell if he had finished a thought or was still gathering them.
For the most part, you will see direct quotes from Werber himself.  Some of the information was slightly altered to make more sense to those perhaps unfamiliar with names/stories from 1927-1943.
ES: Now, according to what I can see here it appears you were first called up to the major leagues in 1930, with the Yankees.  What can you tell me about your experiences on such a dominant team?
BW: Well, haha, I was actually called up earlier, though I didn’t play at all.  In 1927 I was called up for the first time.  The scout that liked me made me a proposition.  He was a big admirer of Miller Huggins, the Yankees manager at the time, and thought it would be to my benefit to sit on the bench and travel with the team, learning how Miller ran the ballclub.  I was on the team in the summer of 1927 for two to three weeks.  I was lonesome because I lived in a hotel by myself, and the ballplayers had little time for a college kid.  After all, they were in a pennant chase.  They would push me out of the batting cage, and take over for me at shortstop in fielding practice.  This made me very unhappy.  I went to see Ed Barrow, the Yankees general manager, and told him “Mr. Barrow, this is not of any benefit to me.  I should be taking batting practice, running, fielding grounders, but I never get the chance.”  He tried to talk me out of it but I had made up my mind.
ES: What can you tell me about that 1927 team?  You said they didn’t necessarily acknowledge you, but Ruth, Gehrig, what were these guys like?
BW: They were, well, a… rambunctious… crew.  They won the AL pennant by ten to twelve games that year and they were called, well the writers called them, Murderer’s Row.  Murderer’s Row was their nickname.  They also beat the Pirates four straight to win the world series.
ES: Now in 1934, you did something now considered a form of betrayal, in going from the Yankees to the Red Sox.  How did this happen?
BW: I was sold to the Red Sox in the early part of the 1934 season.  In Spring Training I hit around .350 and thought the job was mine, but Joe McCarthy, the Yankees manager, sold me, Dusty Rhodes, George Pipgras, and Henry Johnson to the Red Sox.  I came over to play shortstop and Bucky Walters was already there at third base.  Later on, Bucky Harris, the Red Sox manager, bought Lyn Lary.  Lyn took my spot at shortstop and I ended up taking Bucky’s spot at third base.  At this point they sent Bucky to Philadelphia, where Jimmy Wilson turned him into a pitcher.  Joe Judge, our first baseman in Boston, used to complain that Bucky and I threw to first too hard.  He used to say “Hey, don’t throw the ball so damn hard!”
ES: The next time you and Bucky played together would not be until 1939 when both of you were part of a tremendous Reds team.  How did you come to play for Cincinnati?
BW: I held out all of the spring in 1939.  I wasn’t with the Reds but rather I was playing third base for the scrub team at the University of Maryland.  I held out until a couple of days before the Reds broke spring training.  I didn’t know anybody there except for Bucky Walters, and he and I weren’t very close.  We were friendly but we weren’t extremely close.  Once the team came north to play Spring Training exhibition games against the Red Sox I joined the team.
ES: Now, going back, in 1934-
BW: -in 1934, I played third base for the Red Sox and hit .321 with 67 rbis.  I was considered by Ed Barrow, general manager of the Yankees, to be the best player in the entire American League.  Unfortunately, I injured my toe that year and was never the same again.
ES: How did you injure your toe?
BW: I was frustrated by Lefty Grove and so I kicked a bucket full of Florida water, with a sponge in it.  I fractured my big toe and developed a spur.  I also had a calcium block form on the interior part of the big toe joint.
ES: Was it ever fixed?
BW: Well, I went to see Dr. George Bennett, at Hopkins Medical Center in Maryland.  He shaved the calcium block off and removed the spur.  This was in the winter of 1935.  I was never the same ballplayer following the surgery that I was before.  I played in discomfort for seven more major league seasons.  In 1942, I played third base for the Giants.
ES: Yeah, it seems that you didn’t play the whole year either.  How did you come to be on the Giants?
BW: I had retired after 1941, telling Mr. Giles (Warren), general manager of the Reds, that I was in a lot of pain and was going to retire.  He called me one day while I was in Washington, working out of my father’s office, and said “Bill, I know you’re retired, but three clubs are interested in your services.”  I asked him which and he told me the Giants, Pirates, and Cubs.  “What are you selling me for?” I asked.  He told me he was selling me for $35,000 and added that he would give me 10% if I accepted.  Now, 10% of 35,000 is 3,500, and in 1942, 3,500 is a lot of money!  “Sell me to the Giants,” I said.  “If I sell you and you change your mind, will you give me the 3,500 back?” Giles asked me.  I told him of course I would.
Read more of this post

When Non-Pitchers Attack

Trailing 18-0 as the eighth inning came to a close, the Arizona Diamondbacks knew that their chance of coming back had passed its statute of limitations.  When the ninth inning rolled around, and the likes of Rick Helling, Mike Morgan, Eddie Oropesa, and Bret Prinz had already appeared, Bob Brenly decided to give one hopeful his pitching debut.  Mark Grace.  Brenly called upon Grace to pitch the final inning of this September 2nd, 2002 game in order to rest a weary bullpen in a situation that had become meaningless.  What happened next will be etched in the baseball part of my mind forever: Grace began impersonating pitchers on his team, namely Mike Fetters, illiciting much laughter out of the severely depleted fan base as well as his colleagues. 
Grace induced flyouts off the bats of Jeff Reboulet and Wilson Ruan before surrendering a first-pitch home run to Dave Ross.  The dinger turned out to be the first of Ross’s career and you couldn’t help but smile at Grace’s mock yelling angrily at him as he circled the bases.  Tyler Houston then flew out to end the inning and the DBacks lost 19-1.
Non-pitchers taking the mound seems to be an event so rare in nature that it can help quell the disgust at our team for being blown out;  or, for the team experiencing the huge lead, it can become quite the comical moment as pressure ceases to exist when up by 15+ runs.  Despite this, it could potentially produce embarrassing results if a certain non-pitcher happens to strike batters out.  Perhaps not as embarrassing as it would have been if Pat Maholm gave up a single to Billy Crystal but, if I’m a major league hitter, I’m very likely to get razzed if Jeff Cirillo comes into pitch and strikes me out.
Well… if you replace “a major league hitter” with Craig Counsell the previous sentence takes on the form of a factual description of a ninth inning event on August 20th, 2007.  Ahead 9-0, Bob Melvin thought it appropriate to give his oft-used bullpen a break, and handed the ball to the veteran infielder.  Maybe Counsell had been trying to act like a leadoff batter, getting himself into a longer at-bat in order to show his teammates Cirillo’s repertoire, because an epic 7-pitch matchup followed.  After a called strike and a swinging strike, Jeff wasted two pitches, evening up the count at 2-2.  Counsell fought back, fouling the next two pitches off, but Cirillo came back and struck him out swinging on the next pitch.
Counsell is not the only one who has ever fallen victim to a strikeout at the hands of a non-pitcher and I decided to research more instances of this occurring.  Luckily, Sean Forman informed me of a page in the Frivolities section at Baseball-Reference that kept track of non-pitchers pitching, or else this would have taken quite some time.  Below are the more recent players that have been struck out by non-pitchers; since it will come in story and not list form the non-pitcher and strikeout victim will be bolded.
Tim Bogar had made a relief pitching appearance on June 10th, 2000, giving nothing up in his one inning, while throwing 12 pitches/9 strikes.  The Astros called on him again two weeks later, June 24th.  After surrendering a leadoff home run to J.T. Snow, Bogar struck out Felipe Crespo on three straight swing and misses.
Wade Boggs came into pitch in two different years: 1997 with the Yankees and 1999 with the Devil Rays.  No, that isn’t a messup, they were still the Devil Rays back then.  He struck out one batter in each of his appearances.  In 1997, victim #1 was Angels catcher Todd Greene, and in 1999, victim #2 was none other than the venerable Delino DeShields.
In 1991, Cubs outfielder Doug Dascenzo made three pitching appearances, striking out one batter in two of them.  Against the Cardinals he struck out pitcher Willie Fraser, which I guess is not as difficult as someone like DeShields, but is still a strikeout.  Against the Pirates, later on in the year, he struck out pinch-hitter Joe Redfield.  Also of note: he got Barry Bonds to flyout.
Mets legend Matt Franco struck two batters out in multiple 1999 appearances.  With two outs in the ninth inning, against the Braves, Matt came into spell John Franco.  After giving up a Gerald Williams home run and an Otis Nixon triple, he struck out Andruw Jones swinging.  A little over a month later, against the Dodgers, Franco struck out super-mega-pinch-hit star Dave Hansen.
In 1990, current Red Sox skipper Terry Francona struck out Stan Javier.
Gary Gaetti made three pitching appearances throughout his career, but none more memorable than July 3rd, 1999, when he struck out the immortal Kevin Sefcik.
In 1998, another super-mega-pinch-hit star, Lenny Harris, pitched a scoreless inning against the Reds; in the process he struck out Brent Mayne.  Mayne did make a pitching appearance of his own but sadly did not strike anyone out. 
Though not necessarily recent, Dave Kingman struck out three Dodgers in a 1973 game in which he pitched two innings.  His victims: Steve Yeager, Joe Ferguson, and Bill Russell.  Earlier in the year he struck out Darrel Chaney of the Reds.
In 2001, Tim Laker struck out Jose Valentin.  I’m not counting this, though, because Laker was named in The Mitchell Report.  Clearly, magical performance elixirs are the only reason this K exists.
Also in 2001, Mark Loretta struck out reliever Chris Nichting and outfielder Ruben Rivera of the Reds in the same inning.
On June 19th, 1987, third year player Paul O’Neill had one wild appearance against the Braves: Lasting two innings, he gave up two hits, three runs, while walking four and striking out two.  His victims were Ken Griffey (the dad) and pitcher Jeff Dedmon.
Former Pirates backup catcher Keith Osik pitched in one game in 1999 and one in 2000, striking out one in each.  In 1999 he struck out fellow backup catcher Paul Bako.  Osik’s membership to the Below Average Backup Catchers Union was promptly revoked.  In 2000, John Rodriguez of the Cardinals fell victim.
In 2001, Desi Relaford struck out reliever Jose Antonio Nunez in an at-bat that I would bet neither Relaford nor Nunez even remembers.
With two outs in the eighth on May 2nd, 1993, Kevin Seitzer relieved Kelly Downs and struck out Carlos Martinez to end the inning.
On July 31st, 1998, Mark Whiten of the Indians pitched the eighth inning against the Athletics in which he struck out the side!  Mike Blowers, Miguel Tejada (he was two years older though so it’s different), and Mike Neill (who?) were no match for the powers of the “Light-hittin'” one.
And lastly, as a member of the Rockies in 2002, Todd Zeile struck out Wilson Ruan.
Wow.  I don’t know if you realized it or not but the first example of a non-pitcher pitching in this article involved Wilson Ruan and so did the last.  That was entirely unintentional and what we in the filmmaking community refer to as a “happy mistake.”  I never thought I would ever write an article bookended by Wilson Ruan.  My personal favorite non-pitcher pitching moment was Grace’s, but what are yours?

Visual WPA Results

Two weeks ago I discussed a version of WPA in which intuitive scouting would aid in the in-depth division of contributions between batter/runner and pitcher/fielder.  Though not a new or revolutionary technique I felt it was worth bringing up to serve as a potential measure of the human aspects not currently found in the WPA statistic.  Essentially, if those against stats like WPA feel that its results are tainted due to a lack of division amongst the true efforts in each play–situations like a tremendous fielding or baserunning play being solely credited to the respective pitcher and hitter–then incorporating said division would theoretically produce different and more accurate results.
Making Judgments
In conducting this analysis I used the 4/21-4/22 series between the Phillies and Rockies.  Though I definitely agree with Pizza Cutter’s assertion that a group of different eyes determining the credit or debit division is a better idea, the judgments here were left up to my own eyes.  In no way did I attempt to cherrypick any data to prove a point; this was merely done to investigate an idea.  I watched every play with eyes that have seen a ton of baseball games, often watching plays a few times.
Comparing Results
The key in comparing results is understanding that we cannot jump from Point A to Point C.  The current WPA does not divide contributions; if we compared those figures to the in-depth play divisions common sense suggests drastically different results will be found.  Before going in-depth WPA needs to be adjusted to divide credit or debit between, at the very least, errors.  With this in mind I broke the analysis into two steps: First, just separating contribution amongst amazing/bad plays unfairly credited or debited fully to the wrong person; and secondly, dividing contribution on a deeper level, gauging things like outfielder distance, strength of some arms, would your average runner reach third base, etc.  For instance, Chase Utley’s web gems in this series would be included in Step 1 as well as Step 2 whereas something like properly determining the debit recipient on a Wily Taveras stolen base would apply solely to Step 2.  This way, we can compare the current WPA to Step 1 and then Step 1 to Step 2; this comparitive system will be more effective in determining just how different the results may be.
Results
Here are the links to the Fangraphs WPA for these two games, as well as a PDF showing the total WPA for the series:

Here are the links to the VisPA results:

Analysis
Of the 170 plays in this two game set, a total of fourteen were effected by the Step 1 and 26 were altered via Step 2.  Despite only 15% of the plays requiring some type of adjustment there were noticeable shifts in the WPA of certain players.  Chase Utley, for instance, came in at +.454 via standard WPA; both his VisPA1 and VisPA2 were +.589.  Because of his tremendous fielding plays he increased somewhat significantly.  Pat Burrell, on the other hand, had a standard WPA of +.674; his VisPA1 was +.512 while his VisPA2 was +.333.  Due to poor fielding and certain plays benefiting from heads up baserunning on the part of others, Burrell’s standard WPA significantly decreased from WPA to VisPA1 and dropped off even more from VisPA1 to VisPA2.  Here is a file showing all three types of WPA for everyone in this series:

Something I ended up doing, which I’m curious to hear thoughts on, was treat a certain play in a fashion similar to inherited runners.  It was an error made by Pat Burrell that put two men on prior to Yorvit Torrealba hitting a 3-r homer.  If Burrell makes that play, the inning ends; since he didn’t, and three runs scored on the home run, I charged him with 1/3 of the WPA debit on that play.  This is not necessarily something I fully advocate but something to consider and generate feedback on.  It was only one play in this short series so the end result isn’t too significant.  There were no instances of an umpire effecting the outcome of a play with a bad call and no signs of wrongdoing by the third base coaches either.  Some plays were divided based on the difficulty level of properly executing; others, as in Utley’s web gems, were awarded entirely to the fielder.
Based on standard WPA, the most valuable player of this series was Pat Burrell.  Using VisPA1, and in this case VisPA2, Chase Utley is the most valuable player.  If you asked anybody that watched the series who they would pick as the MVP it would likely be unanimous in Utley’s favor. 
This just reinforces that much more can be gathered from mixed methods in sabermetrics.  For all we know, over the course of a season, everything could even itself out to the point that standard WPA is 90%+ accurate.  I’m still very intrigued by the idea of putting something together across the web to track this for an extended period of time.  Even if the results end up cancelling each other out in the aforementioned scenario I feel like we owe it to ourselves to try.  After all, by using a group of eyes to evaluate the proper debit and credit on specific plays meriting said division, we will incorporate human aspects of the game not found in a play-by-play file or game log, and in turn offer a more accurate measurement of what we are seeking to measure.

This Week in News and Sabermetrics: 4/6-4/12

Welcome to the first edition of TWINS – This Week in News and Sabermetrics.  This will be a weekly article recapping the goings on in the baseball world, ranging anywhere from top games of the week or oddest stats to frontrunners for awards based on my formulas and links to great articles.  Expect one of these bad boys every Saturday.  If anybody has suggestions for additions they would like to see feel free to post them in the comments.  Without further delay:
Interesting Bits of Tid
Well, the Tigers finally won a game after starting the season 0-7 and worrying the moustache off of Jim Leyland (not in a literal sense).  Unfortunately, any hope of a winning streak was put to rest when Tim Wakefield took the mound the next night.  Two weeks into the season the team expected to score 1,000 runs in 162 games (6.17/gm for anyone wondering) has scored 28 runs in 9 games (not 6.17/gm for anyone wondering).  To show how bad things have been Placido Polanco even made errors in consecutive nights.
Staying in the AL, Travis Buck of the Athletics started the season by going 0-21, with 9 strikeouts, and a .043 OPS… out of the leadoff spot.  He was about as effective as Travis Buckley–the other guy that appears when you type “Travis Buck” into Baseball Reference–but then remembered how to hit.  In his next three games Buck went 7-16, with 6 doubles, 4 RBIs, and a 1.284 OPS.
MVP Predictor
I came up with a pretty simple formula to see who would win the MVP should the season end at any given point.  The formula is: (OPS+ / 2) + VORP + VB.
OPS+ compares production to the rest of the league; VORP offers how important a player proved to be in accounting for runs than a replacement level player; VB is a Victory Bonus, just like in the James Cy Young Predictor, that awards points to a division leader.  In this case, +10 for first place and +6 for second place.  It’s simple but effective in determining how important a player statistically performed.  It does not take into account the more human factors of the game but the MVP is usually awarded to the best hitter on the best team; this formula measures that. 
I will be revising this throughout the season I am sure but for now it will work fine.  Here are the top five in the NL:

  1. Kendall, MIL, 135.7
  2. Ramirez, FLA, 130.9
  3. Burrell, Phi, 123.5
  4. Pujols, StL, 120.9
  5. Upton, Ari, 107.2

And the AL:

  1. Pierzynski, CHW, 131.4
  2. Scott, BAL, 126.7
  3. Crede, CHW, 123.2
  4. Dye, CHW, 120.0
  5. Drew, BOS, 114.8

Cy Young Predictor
In The Neyer/James Guide to Pitchers Bill James presented a formula that could, with pretty good accuracy, predict the eventual Cy Young Award.  For a description of the formula, click here.  Though I altered his formula in previous articles to account for old-time players, his works great here.  Here are the top five in the NL:

  1. Jake Peavy, SD, 23.3
  2. Brandon Webb, ARI, 19.6
  3. Micah Owings, ARI, 18.8
  4. Ben Sheets, MIL, 18.6
  5. Jason Isringhausen, StL, 18.4

And the AL:

  1. Daisuke Matsuzaka, BOS, 23.2
  2. Zach Greinke, KC, 22.2
  3. Edwin Jackson, TB, 22.0
  4. Chien-Ming Wang, NYY, 20.3
  5. Brian Bannister, KC, 19.9

Beane Count
Over at ESPN.com Rob Neyer created a really cool stat I had never heard of until earlier this month, titled Beane Count.  The stat measures all of the contributions Athletics GM Billy Beane looks for in players and evaluates the teams that best fit his desires.  The total is found by adding the team rank in home runs hit, walks, home runs allowed, and walks allowed.  Interestingly enough, as of right now, both the Chicago White Sox and Chicago Cubs lead their respective leagues–and by significant margins.
Cain Watch
Many readers here should know that I have some crazy manlove for Matt Cain, despite having no allegiances to the Giants, and really cannot stand how unlucky he gets on the mound.  In 2007 he went 7-16, though my Adjusted W-L system had him pegged at 16-7; my SP Effectiveness System even scored him a +50, just meeting the cutoff for a #1 pitcher.  Each week I will look at his starts and see if the unlucky trend continues.

  • #1, 4/1/08, 5.2 IP, 3 H, 0 R, 0 ER, 4 BB, 5 K, ND.  Records an AQND because it was an Adjusted Quality Start.  Game Score of 64.  From what I saw and heard he was squeezed and really should have only walked two batters.
  • #2, 4/7/08, 4.1 IP, 7 H, 5 R, 4 ER, 5 BB, 5 K. Loss.  Does not record an AQS and legitimately deserved to lose.  Unlike his first start he was not terribly squeezed and this was not a good start by any means.

Game Scores of the Week
Bill James created the Game Score statistic to measure the exact quality of a pitched game.  Info on the easy to calculate figure can be found here.  For the record, a GSC of 50 or higher is good.  Below are the top three game scores of the week of 4/6-4/12.

  • Ben Sheets, April 6th: 9 IP, 5 H, 0 R, 0 ER, 0 BB, 8 K – 85 GSC
  • Edwin Jackson, April 10th: 8 IP, 2 H, 0 R, 0 ER, 4 BB, 6 K – 80 GSC
  • Wandy Rodriguez, April 7th: 7.1 IP, 3 H, 0 R, 0 ER, 0 BB, 6 K – 78 GSC

Weekly Oddibe Award
The Oddibe Awards are given to the hitter with the slash stats (BA/OBP/SLG) closest to the league average and are named after Oddibe McDowell, whom RJ Anderson of Beyond the Box Score determined to have the career slash line closest to the league average from 1960-2006.  As of this week the league average slash line is .257/.327/.403.  Should the season for some odd reason end today, the 2008 Oddibe Award recipient would be – Orlando Hudson, Ari: .270/.325/.405.
If the Season Ended Today
Speaking of whether or not the season ended today I think it will be interesting to look at the playoff matchups each week if it did end.  This way we can see which teams were in it all year as opposed to burning out or surging in. Note – this was done at 11:16 PM EST, so the As had played while the Angels were still playing.

  • Baltimore Orioles (AL East) vs. Chicago White Sox (Wild Card)
  • Kansas City Royals (AL Central) vs. Oakland Athletics (AL West)
  • Arizona DBacks (NL West) vs. Winner of Tiebreaking Game between CHC/MIL
  • Florida Marlins (NL East) vs. St. Louis Cardinals (NL Central)

In Case You Missed It
Here are some great sabermetrics articles from this past week:

The Visual WPA Project

Across the statistical spectrum a major debate has raged for quite some time: the statistical analysts vs. the scouts. Both thinks one another is wrong and bases decisions off of faulty methods. Though small portions of each side embraces the other the large majority does not. For this very reason WPA—Win Probability Added—has gotten some heat from those against baseball statistical analysis.
Essentially, WPA tracks the contributions of an individual to the win or loss of his team. It adds the accumulative differences in Win Expectancy percentages to determine who helped or hindered what specific percent of their team’s efforts.
To find the Win Expectancy of any game state, look in the Toolshed section of The Book or visit Christopher Shea’s Win Expectancy Finder online. For a great article on WPA, read Studes’ “The One About Win Probability.”
When I described WPA to a friend of mine—one on neither side of the analysis war—he responded with: “Yeah, but they’re human. Certain numbers like that cannot track true effort.”  While I disagree that a number cannot accurately track effort I do feel the current WPA could potentially improve to track even more effort; or properly divvy up the effort to take into account these more human qualities. His comment made me wonder what would happen were we to combine our intuitive scouting as fans with a statistic like WPA; as in, would the results be so different than what we currently have?
If those in opposition to numbers really feel that human aspects of the game make such a drastic difference that an anarchic overthrow of WPA would be necessary then it seems to be a good idea to test that theory out. In conducting a study like this we would basically be measuring certain game aspects previously determined to be immeasurable with a stringent set of criterion.
Logistics
TangoTiger helped me harness this idea when it was discovered I was preparing to write an article he had previously written.  He informed me that his thoughts echoed those of my friend—the numbers might be improved upon combining percentages with intuitive scouting. The visual WPA would work much like the current statistic only there would be certain plays or situations with which we could apply our opinion of effort or contribution.
In May 2007, the Phillies were playing the Marlins and Rod Barajas made an absolutely boneheaded play. Hanley Ramirez was rounding third base and Pat Burrell’s throw creamed Ramirez in a race; by the time Barajas had the ball Ramirez was still one-fourth of the way from home plate. Despite this, Barajas, for whatever reason, did not block the plate or attempt a tag until Ramirez slid. Ramirez ended up being safe. In terms of WPA pitcher Brett Myers was debited the full amount but Barajas clearly deserves some of the blame. This is an example of a situation that only watching the game would be able to determine those deserving of credit or debit.
Though the Barajas situation falls into the category of separating fielders from pitchers in the contribution department, there are also the ever so frequent non-error errors. We’ve all seen these plays wherein a fielder should be able to get to a ball but it gets through infield or drops in the outfield. Errors are not charged in these specific plays however we know they should have been made. Why should the pitcher be fully debited for allowing a single when we intuitively understand that the play should have been made?
Other examples where a Visual WPA would benefit us are:

  1. Runner on first legging it out to third on a single, or scoring on a double when we intuitively feel he has no shot.
  2. Pitcher with a slow wind-up should be debited on an SB, not a catcher, whereas someone like Roy Oswalt (fast windup) would have more of an effect on a runner stealing.
  3. Separating a bad judgment or decision by a 3B Coach from the runner thrown out at a base he perhaps had no legit shot at reaching.
  4. We’ve all seen examples of Harry Kalas’s famous line: “Right down the middle for a ball.” If a pitcher strikes a better out but the ump fails to call the strike we should debit the umpire a bit because he incorrectly lengthened the inning.

And these are just a few of the examples of situations that would benefit from intuitive scouting.
Separating the contributions between batter/runner and fielder/pitcher has been studied before but I am proposing a use of our own intuition as fans in order to make these separations instead of a concrete set of numbers or measurable criteria. For instance, a runner legging it out to third on a single when we normally think he would have to stop at second base would be left to our intuition. We would be using our knowledge of the runner, the position of the outfielder, the throwing arm of the outfielder, and the importance of the situation in order to make our judgment.
If David Ortiz legs it out to third base in the first inning of a 0-0 game we may be inclined to split the WPA between he and the hitter by giving Ortiz 1/3 of the increase and the hitter 2/3. If the same situation occurs in the bottom of the 9th in a game in which the Red Sox trail 2-1 we may be much more inclined to give Ortiz 2/3 and the hitter 1/3. This allows us to separate contributions based on how we feel and our own scouting abilities. Essentially it lets us determine if scouting and the more human/gutsy/Eckstein-esque plays really effect or make much of a difference on what the statistics tell us.
Opinions vs. Measures
One of the big gripes here is that an opinion of mine with regards to a runner legging out an extra base may be completely different than someone else. This, however, is the beauty of baseball and how scouting works; scouts will differ in opinions on the same player. Though statistics are generally immobile scouting and intuition can shift. It is scary when presenting a potential concept like this—one that includes a combination of fact and opinion—but the idea is to see if we will truly produce different results; or at least results different enough to show that the immeasurable human aspects of the game really do make certain numbers less useful.
Conclusion: A Call to Arms
I am going to test this out with a three-game series in order to compare the differences and if anybody would like to help, by conducting their own three-game test, please e-mail me. If we can get a bunch of series logged, and if we see there are potentially big differences, there may be good reason to try this out over an extended period of time.  Ultimately, if the results are deemed significantly different than we can say that these game aspects only evident by watching a game truly make a difference.  At the very least we will be garnering a more accurate version of an already accurate statistic.  I will post my initial results of the three-game series next week.

Cain Watch #1

SIDENOTE – THE ODDIBE AWARDS have been updated to include the averages for individual seasons, so some players have changed.  Click the link to re-view the results. 
Something I will be doing throughout the season is tracking the unluckiness of Matt Cain. Per my Net Luck Rating statistic, which determines luck or a lack of luck through the recorded decisions and no-decisions, Cain’s 2007 season was the unluckiest of this decade. He recorded a 7-16 W-L record but, based on his peripheral statistics and the frequency of well-pitched games, he would have an Adjusted W-L of 16-7; he was also determined to be a #1 SP in my SP Effectiveness System with a +50.
Since his team is going literally nowhere this year it is safe to assume that his efforts will once again be wasted. So, each week I will be breaking down his starts in order to show that the eventual 5-21 record he posts is going to be extremely non-indicative of his quality and performance.
START #1 – 4/1/08 vs. Dodgers
It could not be more appropriate for his first start to come on April Fool’s Day. Cain went 5.2 IP, 3 H, 0 R, 0 ER, 4 BB, 5 K. He pitched effectively though I wish he would have been able to go the extra 0.1 IP to get to 6+. This makes me rethink the definition of the AQS and desire to include games of 5-5.2 IP as long as 0 runs scored. Otherwise it would not technically be fair. Cain pitched a great game here and did not allow a run yet he would not be credited an AQS; however, if he went just one more out he would have. There are not too many examples of situations like this but if it keeps up I’ll have to slightly alter the definition to include one more variable.
Cain really never found himself in imminent danger (bases loaded, no outs) despite walking four. Through the first three innings he faced just one batter over the minimum–thanks to an Andre Ethier single–but retired everyone else. In the fourth inning, after retiring Russell Martin and Ethier, Jeff Kent doubled. Cain proceeded to throw a wild pitch allowing Kent to advance to third base and followed it with a walk to Andruw Jones. He then struck James Loney out looking to end the inning. Through four innings he had given up 2 hits, walked 2, and struck out 4.
In the fifth he had a 1-walk-2-3 inning which seems to be somewhat of a staple for Cain; instead of 1-2-3 innings he will allow one baserunner that will never advance and face just four batters. After inducing a pop-up from Russell Martin, in the sixth, Ethier again singled. Jeff Kent then struck out and Cain found himself one out away from six shutout innings. Andruw Jones followed with a walk, and then, well, Larry Bowa went absolutely insane.
Following Bowa’s Daniel-Day Lewis performance a likely-iced Cain walked James Loney to load the bases. His day had come to an end. Bochy lifted him for Jack Taschner–on a non-sequitur, isn’t it much more fun calling him Jumping Jack Taschner? Anyways, Jumping Jack Taschner struck Matt Kemp out to end the potential threat but, as usual, Cain’s great performance would go unheralded in the W-L column. While a performance like this last year may have garnered Cain a loss (yeah, that’s how unlucky he was) at least this was a no-decision. See, maybe the Giants ARE improving.

The Oddibe Awards

This is a slightly modified excerpt from my upcoming book, Bridging the Statistical Gap, to be released towards the end of April/beginning of May.
A friend of mine, RJ Anderson of Beyond the Box Score, recently sent me the introduction to a book he is currently writing to look over.  While reading I could not help but notice an extremely fascinating statistical tidbit and RJ graciously allowed me to conduct further research regarding his findings.  Using the Lahman Database he had taken all of the offensive seasons from 1960-2006 and, after tallying the counting stats (H, AB, 2B, etc.), calculated the average slash statistics (BA/OBP/SLG) of major league hitters in that span.  The average major league hitter from 1960-2006 put up a slash line of .259/.326/.395.
He then set parameters in the spreadsheet and was able to find the player with career numbers that most closely matched these slash statistics.  The player?  Oddibe McDowell.  McDowell’s career .253/.323/.395 was closer to the average than anyone else in that timespan.
While RJ then went onto discuss the collegiate and major league career of Sir Oddibe I decided to apply this theory to individual seasons.  I found the average slash lines for each year from 1981-2007 and found the players most closely resembling those lines.  Since Oddibe’s career line came the closest I have named my yearly award after him.  Therefore, the award for the most average offensive player, via slash stats, in a given year, will be hereby known as “The Oddibe Award of Excellence in Average Performance.”
This way anybody with a small sample size of statistics would be disqualified from inclusion; the slash parameters were originally smaller but widening them became a necessity when it was determined that so few people came within 5-7 points of each.  Some players would be within 1-2 points in BA and OBP but were 10-15 points off in SLG, and other variations of the same type of discrepancy.  If multiple players were essentially equivalent I went for those with the higher number of AB’s.  If multiple players were close and no clear-cut winner emerged I simply measured how far off they were in each of the three stats; I went for consistency meaning that a player within four points of all three would be more average than one who was equal in two stats but twelve points off in the third.
With that being said, here are the winners of the annual Oddibe Awards from 1981-2007:

YEAR PLAYER TEAM BA/OBP/SLG
1981 Rich Dauer BAL .263/.317/.369
1982 Alan Trammell DET .258/.325/.395
1983 Alan Bannister CLE .265/.323/.393
1984 Ben Ogilvie MIL .262/.327/.384
1985 Bill Madlock PIT .251/.323/.388
1986 Rudy Law KC .261/.327/.388
1987 Robby Thompson SF .262/.328/.415
1988 Ozzie Virgil ATL .256/.313/.372
1989 Ken Caminiti HOU .255/.316/.369
1990 Gary Ward DET .256/.322/.392
1991 Luis Rivera BOS .258/.318/.84
1992 Jay Bell PIT .264/.326/.383
1993 Cory Snyder LAD .266/.331/.397
1994 Orlando Merced PIT .272/.343/.412
1995 Bret Boone CIN .267/.326/.429
1996 Travis Fryman DET .268/.329/.437
1997 Dan Wilson SEA .270/.326/.423
1998 Mike Bordick BAL .260/.328/.411
1999 Damion Easley DET .266/.346/.434
2000 Chad Curtis TEX .272/.343/.427
2001 Steve Cox TB .257/.323/.427
2002 Michael Barrett MON .263/.323/.418
2003 Robert Fick ATL .269/.335/.418
2004 Orlando Hudson TOR .270/.341/.438
2005 Brandon Inge DET .261/.330/.419
2006 Curtis Granderson DET .260/.335/.438
2007 Jhonny Peralta CLE .270/.341/.430

2008 ODDIBE GOES TO…?
With so many projection systems out there it just seemed natural to check who might qualify for the prestigious average award this season. And, as opening day really gets underway today (triple-rhyme) let’s examine this year’s Oddibe candidates, using StatSpeak alum Sean Smith’s CHONE projections.
1) Chris Burke – .256/.330/.392
2) Franklin Gutierrez – .259/.317/.404
3) Jacque Jones – .260/.318/.402
4) Chase Headley – .252/.335/.392
5) Brandon Inge – .249/.325/.405
We’ll all have to keep our Oddibe-eyes out for this one!

Liveblogging ‘Moneyball’ Underway

Fed up with the misconceptions and generalizations surrounding ‘Moneyball’ I decided to spend a whole day re-reading the book and live-blogging my experience.  What will follow is a chapter-by-chapter recap explaining what does and does not happen based on these misconceptions.  Newer chapters will appear at the top.  At the end I will re-organize everything. 
9:37 PM – Conclusion
Well, what started at 11:37 will come to an end; a 10-hr (though I was done at 9:33 and just waited until 9:37) liveblog on a book reading.  Overall, there was more mentioned about Chad Bradford’s religion in this book than there were overt references to scouting being irrelevant.  All Lewis (not Beane) did was discuss how Beane (not Lewis) decided to change things around due to their financial limitations.  They were never going to have a large payroll so it made no sense to continue drafting the players old-time scouts coveted.  These players would demand higher signing fees/bonuses and take the A’s to the cleaners when it came time for arbitration. 
Finding talent in places nobody else looked is not an idea to shoot down; it’s an idea to embrace, at the very least for its logistics.  If you want to be like Joe Morgan and completely write off the notion that there may be better ways to evaluate talent, go ahead and stick to your guns; but to call these methods of exploiting marketing inefficiencies stupid is, well, stupid itself.
Moneyball does not call scouting ridiculous nor does it point out any of the positives that come with scouting; it treats scouting as an outdated end-all method and points out that, for a team with a financial situation such as the Athletics, there may be better ways to evaluate talent.  Moneyball does not say that all player decisions need to rely on OBP; it points out, quite logically, that players with better OBP’s have historically been more likely to aid their team while simultaneously being undervalued.  Overall, Moneyball is not a book about using sabermetrics as a means to run your team but rather a way to succeed and attempt to ensure future success in ways that others would never think.  If you do not agree with statistical analysis, fine, but look no further than the Athletics 2000-2006 W-L records and standings position to realize that Beane may be doing something correctly.
8:37 PM – Chapter Twelve: The Speed of the Idea
This chapter, the final chapter, explores the major differences between the regular season and post-season as it relates to baseball in general and not just the Athletics.  Lewis refers to Palmer and Thorn’s The Hidden Game of Baseball to explain that the difference in skill is about 1 run per game whereas the difference in luck is about 4 runs per game.  The playoffs would be a whole different motha’ and Billy Beane openly admitted that his strategy was designed to get a team into the playoffs – after that it was all luck.
Rent-a-player at the time Ray Durham noted how all playoff games were 2-1 or 1-0–very close games.  In the division series, the Athletics ended up scoring more runs than they averaged in the regular season (5.5 to 4.9).  Joe Morgan stated that the Athletics could not win in the playoffs because they could not manufacture runs.  Clearly they manufactured runs.  DePodesta chalked their failure up as allowing 4.0 runs in the regular season and 5.4 in the playoffs.  On top of that, Tim Hudson–their usual unflappable ace–had two terrible outings.  The offense realistically had little to do with it, but rather their pitching.
The chapter closes with a discussion of Beane’s off-season move of trading Art Howe to the Mets as well as what appeared to be a changing of the guard in at least Toronto; DePodesta’s righthand man Ricciardi was hired within 5 minutes of his GM interview.  Ricciardi then brought along Keith Law and they rebuilt the Blue Jays.  DePodesta attests to hoping that other teams continued to consider their methods ridiculous because it would give them more time before they caught on; this would make the rare strategy more commonplace and new exploits in inefficiencies would need to be found.
I’m going to wait a couple of hours to gather my overall thoughts for the conclusion but I hope this, at the very least, sheds some light on what does and does not happen in Moneyball
8:04 PM – Chapter Eleven: The Human Element
Okay, the food did come.  And, I was almost brought to tears when I watched the warm-ups for the Sixers-Nuggets came and saw Allen Iverson get a standing ovation.  Though I write for a baseball blog, basketball has been an equally important part of my life and  I was one of few people that cherished every game I got to see him play; most took it for granted that his play was “normal.”
This chapter starts with our first real “conversation” with Billy Beane and ends with the description of a tremendous game.  In the beginning, Lewis is with Beane, talking about then 24-yr old Eric Chavez.  Beane strongly contends that Chavez has the potential to be an all-time great.  He compares Chavez at 24 to Barry Bonds, Alex Rodriguez, and Jason Giambi at 24; Chavez had comparable numbers to A-Rod and better numbers than Bonds and Giambi.  In Chavez’s defense when compared to A-Rod, Beane states that “Chavvy is the best defensive third-baseman in the game.  A-Rod’s not the best defensive short-stop.”
Personally, I remember A-Rod as a pretty damn good short-stop.  I see where Beane was going with this but Alex Rodriguez has always been one of those “special” players; Chavez started his career in a very promising fashion but I (maybe I’m wrong, maybe not) never really considered him anything more than a good-great player.  Not to say there is something wrong with that but guys like A-Rod, Pujols, Bonds (please, no cliche steroids reactions) were clearly of a different ilk than someone like Chavez.
The most ironic line of the chapter comes towards the end of the comparison.  Beane says – “Health permitted, his career is a lock.”
Then it gets into Chad Bradford and his religious views.  I didn’t really care about Bradford’s upbringing and I care even less that he reads the bible.  Luckily it then moves into a beautiful description of what turned out to be Athletics 20th win in that 20-game win streak.  They led 11-0 and somehow gave all of those runs back to the last-place Royals, before Scott Hatteberg unknowingly hit a walk-off home run.  My description wasn’t as beautiful, I admit, but my sanity levels are slowly decreasing.  I can’t even remember at this point if I made the joke about Scott Hatteberg’s OBP and seeing numbers.
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