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Thursday, January 31, 2008

Yin and Yang

I thought I'd finish off January with a couple of links...

  • Lovin' on Bannister. MLB Trade Rumors did a great interview with Royals pitcher Brian Bannister in three parts. Part 3 is where it gets really good as Brian reveals that he does his own statistical analysis (we already knew he was a BP reader) and gives us his take on DIPs theory. Several well-renowned analysts have already started the discussion into his insights and I'm sure we'll be seeing more in the future. What really encourages me about this is recognizing the value that thoughtful players like Bannister of Jeff Francis can provide and it makes me wonder how teams are utilizing those resources in parterning with the analytical resources they have.


  • Not so Much Insight. Kind of the anti-Bannister kind of observations were offerred by MLB.com reporter Marty Noble back in early January. In a previous article Noble used RBIs per 100 at bats to make a comparison between newly acquired catcher Brian Schneider and departed backstop Paul Lo Duca. In the response I've linked he tries to explain himself and although his main point that Schneider and Lo Duca are no longer as different offensively as some people claim is valid, there's simply no way he can get out of the hole he's dug. He has the right idea, namely that opportunities are important and rate statistics rather than counting stats are key, but of course he fails to select the right kind of opportunities to make the kinds of comparisons he's going for.

    That said, he dropped two little gems that I couldn't pass up:

    Computers have contributed to a current glut of statistics that, to a degree, distort the picture. We have so many now that we lose focus on what is most important. The objective of the game is to win, and to win a team must outscore its opponent. Nothing, therefore, is more important than runs -- both producing and preventing them.

    To what degree and to which statistics is he referring? Actually, I would argue that by translating traditional statistics into the currency of runs assuming an accurrate weighting, the vast majority of the supposed "glut" of statistics (VORP, BaseRuns, Linear Weights, defensive metrics, base running, etc.) have served to paint a more accurrate picture of "what is most important" - creating run differential that leads to winning games.

    That Lo Duca might have had a higher on-base percentage or slugging percentage means less to me than the number of runs he produced. The next time a team wins a game because it produced a higher on-base mark and scored fewer runs than its opponent, please alert me.

    Here I think there are two points of confusion.

    First, it turns out that the very combination of metrics he mentions, on-base percentage and slugging percentage (OPS), is a very strong predictor of runs produced since it accounts for the key ingredients (getting on base, moving runners, and avoiding outs) that are so problematic in looking at things like RBIs per 100 at bats which only measure one part of the equation. Additionally, by not accounting for context nor understanding how other metrics predict offensive output Noble ends up inverting the relationship between offensive production between the statistics he discusses.

    Second, in his last sentence he stumbles across the problem of scale. It is tautological to say that run differential is a perfect predictor of wins and losses at the level of an individual game. Therefore RBIs and run scored (at least for the offense) take on primary significance in that context and at that scale while OBP and SLUG are less predictive. However, once you raise the aggregation level, those counting stats take on less significance in player evaluation because a particular player's role in generating offense is about more than the tallying of the end result (an RBI or run scored) to the point where it quickly becomes the case (and well before the level of seasons) that OBP+SLUG and other derivative metrics are more indicative of offensive contribution and therefore wins and losses.

    This confusion of effects at various scales reminds me (not coincidentally because I'm now reading this book) of one of the primary themes in the writing of the late Stephen Jay Gould. He often railed against the position of ultra selectionists or adaptationists who insisted that natural selection was the exclusive driver and shaper of the pattern of life on earth. Gould contended that evolution operated differently at different levels through various mechanisms and that what worked at one level did not necessarily have power at another. For example, he argues that while natural selection works through differential reproductive success to build adaptations at the level of individual organisms (coloring, wings, claws, size, etc.) those adaptations may have little or nothing to do with survival at the higher level of species. In one of his favorite examples he liked to point out that the small size and adaptability of mammals during the age of the dinosaurs was likely the result of the domination by dinosaurs in the niches available to larger animals. However, when the meteor struck it was those "negative" traits that allowed the mammals to survive but doomed the dinosaurs.
  • Outfield Defense Redux

    I've made some changes to the SFR system for outfielders based on excellent feedback from readers and others that I discuss in today's column appropriately titled "Back to the Drawing Board". One of the things you'll notice is that my correlations for right fielders (primarily because of Brian Giles and Juan Encarnacion) with UZR for the 2003 through 2006 period are very poor. Not sure why but I noticed that Sean Smith apparently has similar issues. Overall, I like the system better and it seems to handle Manny Ramirez better and correlates pretty well with UZR overall.

    As a bonus you can now download a spreadsheet with version 1.0 of SFR for the infielders that includes 2007 minor league data.

    Baseball Prospectus Top 100

    At Baseball Prospectus today we published our top 100 prospects list as compiled by Keving Goldstein. Jay Bruce leads the field and below is the list ordered by team so you can count and debate your favorites. In terms of sheer numbers the A's, Rangers, and Red Sox each have seven prospects in the list while the White Sox, Blue Jays, Indians, Mets, Tigers, and Astros have one a piece.


    Rank/Name Pos Team
    27. Nick Adenhart rhp Angels
    38. Brandon Wood 3b/ss Angels
    59. Jordan Walden rhp Angels
    89. Hank Conger c Angels
    54. J.R. Towles c Astros
    22. Daric Barton 1b Athletics
    26. Carlos Gonzalez of Athletics
    46. Fautino de los San rhp Athletics
    50. Brett Anderson lhp Athletics
    56. Gio Gonzalez lhp Athletics
    98. Trevor Cahill rhp Athletics
    99. Chris Carter 1b Athletics
    7. Travis Snider of Blue Jays
    17. Jordan Schafer of Braves
    36. Jason Heyward of Braves
    63. Brent Lillibridge ss Braves
    70. Brandon Jones of Braves
    83. Gorkys Hernandez of Braves
    86. Jair Jurrjens rhp Braves
    31. Matt LaPorta of Brewers
    42. Manny Parra lhp Brewers
    76. Jeremy Jeffress rhp Brewers
    8. Colby Rasmus of Cardinals
    69. Chris Perez rhp Cardinals
    71. Bryan Anderson c Cardinals
    37. Geovany Soto c Cubs
    45. Josh Vitters 3b Cubs
    40. Jacob McGee lhp Devil Rays
    20. Jarrod Parker rhp Diamondbacks
    64. Gerardo Parra of Diamondbacks
    90. Max Scherzer rhp Diamondbacks
    5. Clayton Kershaw lhp Dodgers
    14. Andy LaRoche 3b Dodgers
    32. Chin-Lung Hu ss Dodgers
    66. Scott Elbert lhp Dodgers
    78. Wes Hodges 3b Georgia Tech
    29. Angel Villalona 3b Giants
    84. Henry Sosa rhp Giants
    52. Adam Miller rhp Indians
    33. Jeff Clement c Mariners
    44. Chris Tillman rhp Mariners
    55. Carlos Triunfel ss Mariners
    93. Wladimir Balentien of Mariners
    10. Cameron Maybin of Marlins
    88. Chris Volstad rhp Marlins
    51. Fernando Martinez of Mets
    28. Chris Marrero of/1b Nationals
    35. Ross Detwiler rhp Nationals
    81. Michael Burgess of Nationals
    12. Matt Wieters c Orioles
    75. Chorye Spoone rhp Orioles
    85. Radhames Liz rhp Orioles
    23. Chase Headley 3b Padres
    39. Matt Antonelli 2b Padres
    61. Matt Latos rhp Padres
    68. Carlos Carrasco rhp Phillies
    96. Joe Savery lhp Phillies
    24. Andrew McCutchen of Pirates
    43. Steven Pearce 1b Pirates
    94. Neil Walker 3b Pirates
    30. Neftali Feliz rhp Rangers
    49. Eric Hurley rhp Rangers
    58. Elvis Andrus ss Rangers
    62. Engel Beltre of Rangers
    73. Michael Main rhp Rangers
    74. Chris Davis 3b Rangers
    77. Taylor Teagarden c Rangers
    3. Evan Longoria 3b Rays
    6. David Price lhp Rays
    15. Wade Davis rhp Rays
    18. Desmond Jennings of Rays
    25. Reid Brignac ss Rays
    2. Clay Buchholz rhp Red Sox
    16. Jacoby Ellsbury of Red Sox
    53. Justin Masterson rhp Red Sox
    57. Jed Lowrie ss Red Sox
    60. Ryan Kalish of Red Sox
    95. Michael Bowden rhp Red Sox
    100.Lars Anderson 1b Red Sox
    1. Jay Bruce of Reds
    9. Homer Bailey rhp Reds
    21. Joey Votto 1b Reds
    41. Johnny Cueto rhp Reds
    13. Franklin Morales lhp Rockies
    80. Chris Nelson ss Rockies
    82. Greg Reynolds rhp Rockies
    91. Casey Weathers rhp Rockies
    92. Dexter Fowler of Rockies
    19. Mike Moustakas ss Royals
    72. Luke Hochevar rhp Royals
    11. Rick Porcello rhp Tigers
    65. Carlos Gomez of Twins
    79. Deolis Guerra rhp Twins
    97. Ben Revere of Twins
    87. Aaron Poreda lhp White Sox
    4. Joba Chamberlain rhp Yankees
    34. Ian Kennedy rhp Yankees
    47. Austin Jackson of Yankees
    48. Jose Tabata of Yankees
    67. Alan Horne rhp Yankees

    Wednesday, January 30, 2008

    Profiling a Ray

    The always fascingating Marc Normandin allowed me to horn in on his regular gig this week and contribute a little PITCHf/x analysis to his player profile of the Rays (not Devil) James Shields. Unfortunately Shields had just eight of his 31 starts recorded by PITCHf/x but still the 712 pitches does allow us to see some definite patterns. The article does not require a subscription.

    Monday, January 28, 2008

    The Hot Stove at Altitude


    The Rocky Mountain Chapter of SABR held its annual “Hot Stove” meeting on January 26th at Jackson’s All-American Grill located across the street from Coors Field in Denver. Being the Secretary of the chapter, yours truly took some notes and what follows is the synopsis.

    President Paul Parker called the meeting to order a little past 10AM and after a few brief remarks introduced trivia-master Dave Wallack. Dave lead-off the festivities by distributing a quiz loaded with Rockies and other trivia to the 32 assembled members and guests. After 10 minutes of contemplation and confused looks the quizzes were scored with the top three finishers receiving their choice of copies of Baseball Between The Numbers or a wall poster of vintage baseball cards from the 1920s. It happened that three members tied for second place and so what turned out to be a not-so-fast “lightening round” moderated by Parker and Wallack (whose questions were a little tough to say the least) was held to determine the two who would take home the remaining door prizes.

    Parker then continued the meeting by reminding members of the upcoming Denver Bears/New York Yankees Reunion fundraiser event now scheduled for May 3rd at the Denver Athletic Club. As of now the event will feature Ralph Terry, Johnny Blanchard, Ryne Duran, and Woody Held and consist of research presentations, a panel discussion, and autograph session. Later in the meeting member Matt Repplinger discussed the availability of Rockies/Dodgers tickets for that evening’s game, which will be sold at the event with a part of the proceeds benefiting the chapter. The face value of the ticket will be $38 for an Outfield Box seat down the right field line in section 116. The chapter will be selling the $38 ticket for $28, ten dollars off the face value. The group’s planned summer trips to Albuquerque, Colorado Springs, and Casper, Wyoming were also discussed.

    The meeting then continued with a research presentation by myself and Neal Williams where we presented our article “The Traffic Directors”, which will appear in the upcoming volume 36 of The Baseball Research Journal. The study focused on the attempt to quantify the contributions of third base coaches and to determine if there is a detectable skill component that can be measured. We used a subset of the base running metrics I developed for Baseball Prospectus but are augmented with the additional context of the personnel the coach had to work with. You can read the details in the BRJ or the two-part version online, but we conclude that if there is a skill component (or rather a skill difference between coaches if you prefer), it is too subtle to measure given the combination of play by play data and other influences. Attendees engaged in a short question and answer period before taking a brief break.

    After the break Parker introduced the keynote speaker, Jeff Bridich, the Rockies Director of Baseball Operations. After giving a brief rundown of his career in baseball and his opportunity to join the Rockies in 2004 as the Director of Minor League Operations, Jeff began by asking the crowd how they would grade the Rockies off-season moves thus far which included the signings of Matt Holliday, Willy Taveras, and the record-breaking contract of Troy Tulowitzki. With that opening the attendees grabbed the bull by the horns and peppered Bridich with questions ranging from the arbitration cases of Brian Fuentes, Brad Hawpe, and Garrett Atkins to this spring’s competition at second base involving Jayson Nix and Marcus Giles among others, to the health of pitcher Jason Hirsch and the prospects of catcher Chris Iannetta. As you might imagine, much time was spent dissecting the options at second base for the upcoming season and Bridich provided some interesting background on the development of Nix as he went from an offensive prospect after being drafted in 2001 to the player most likely to hurt the team defensively at second. He also indicated that the loss of Carney Lansford as a minor league hitting coach was a big blow to their organization.

    Being closely involved with the arbitration process, Bridich was able to provide excellent insight into the dynamics of the interaction between the two sides and with the three-member panel in what he characterized as often “not a friendly exchange of information”. Further, he discussed approaches to preparing arbitration cases from the club perspective including their use of some advanced metrics such as Zone Rating for measuring defense. Interestingly, he indicated that while the use of advanced metrics was certainly a part of their strategy, those metrics needed to be published and proven in the industry to the extent that they can show the panel that the metrics have some legs.

    I found particularly interesting his comments on the baserunning of Willy Taveras where he noted that the Rockies are encouraging Taveras to be more liberal in his stolen base attempts, especially of third. Bridich related that when asked how many times he could have stolen third in 2007, Taveras indicated that he could have swiped third 30 or so times. While that's certainly an optimistic assessment even for a competitve player, it's certainly true that Taveras seems to have a fear of stealing third. Overall, in my baserunning framework I have him for 138 events at second base and just 3 at third over the course of his career and one of those three was actually a pickoff at second base and one came as his only stolen base attempt of 2004 (perhaps that's what instilled the fear?). Now if they could just teach him to bunt towards first base...

    If Bridich had prepared remarks, the steady stream of questions from the attendees and his thoughtful and articulate answers prevented him from getting to them. After over an hour of discussion many in the group, including Bridich, enjoyed lunch at the restaurant while the discussion continued.

    Thanks to all members and guests who participated in this stimulating morning of baseball discussion.

    Saturday, January 26, 2008

    The Moral Hazards of the Hit Batsmen

    This the final in a series of three columns I wrote for BP on the topic of hit batsmen. You can find the other two on this blog as well. It appeared on May 18, 2006



    Schrodinger's Bat:The Moral Hazards of the Hit Batsmen
    by Dan Fox

    "The designated hitter rule is like letting someone else take Wilt Chamberlain's free throws."

    --Rick Wise (1974)

    In the previous two weeks, we’ve been looking at historical hit by pitch rates and their trends, and investigating a variety of theories that have tried to explain the fluctuation of those rates. We’ve looked at a wide variety of theories that account for factors such as aluminum bats at the amateur level, changes in the strike zone, the increase in body armor, intimidation, retaliation, and even the win expectancy of the hit batsmen. While individual theories may lack explanatory power for a specific period of time, taken together they do provide insight into the sometimes opposing forces that underlie trends in baseball's complex competitive environment.

    There is one trend, however, that we failed to discuss. So this week we’ll take a look at the difference in league rates of hit batsmen since the introduction of the designated hitter in 1973. This topic has been taken up before, so we’ll start by covering some of the old ground, and then hopefully add something new to the discussion.

    Setting a Baseline
    Before we discuss what the impact of the DH on HBP rates might be, let’s lay out the raw facts that have inspired so much conjecture. The following graph shows the percentage of AL hit batsmen per 1,000 plate appearances as opposed to the NL since the DH was adopted in the American League in 1973. The shaded line is a three-year moving average.



    What this shows is that from 1973 until the mid 1990s the rate of hit batsmen in the AL was anywhere between 3% and 30% higher than in the NL. While that’s a wide range, more typical values are between 10% and 20%, with the average during the period being 17%:


    1973 9.3% 1990 19.0%
    1974 14.0% 1991 18.6%
    1975 7.8% 1992 20.0%
    1976 17.3% 1993 9.4%
    1977 17.2% 1994 -7.6%
    1978 12.5% 1995 -6.7%
    1979 8.4% 1996 2.5%
    1980 24.2% 1997 -15.9%
    1981 22.8% 1998 4.4%
    1982 3.2% 1999 10.2%
    1983 19.1% 2000 -17.6%
    1984 29.7% 2001 7.0%
    1985 21.5% 2002 7.4%
    1986 26.5% 2003 3.4%
    1987 16.7% 2004 7.7%
    1988 20.9% 2005 -5.6%
    1989 22.9%


    Around 1994, things began to change and in the following dozen years HBP rates in the NL actually surpassed those in the AL five times, including in 2005 where 9.52 batters were hit per 1,000 PA in the AL, against 10.05 in the NL.


    So in fact, there are actually two questions that we can ask about this trend. First, what accounts for the difference in rates of hit batsmen during the twenty-year period following the introduction of the DH (1973-1993), and secondly, what caused those differences to shrink in the period after 1993?

    A Moral Hazard or More Opportunity?
    As mentioned in the introduction, the topic of league differences in HBP rate have been researched in the past. Most recently, Lee A. Freeman wrote an excellent article titled "The Effect of the Designated Hitter Rule on Hit Batsmen" in Volume 33 of The Baseball Research Journal. In it, Freeman provided a short synopsis of the previous work, citing articles in the journal Economic Inquiry in 1997 and 1998, as well as a follow-up in a 2004 issue of the Journal of Sports Economics.

    Prior to Freeman’s paper the two theories that had been bandied about to explain the difference (at least from 1973 until the mid 1990s) were the "moral hazard theory" and the "lineup composition theory." The former theory argues that because American League pitchers needn’t fear retaliation with the presence of the DH, they are more apt to hit opposing batters since they don’t bear the costs of their actions directly. The latter theory also argues from a cost-benefit basis, although differently--AL pitchers hit more batters because the cost in terms of run scoring when hitting a DH is so much less than hitting a pitcher. This follows from the fact that the designated hitter is much more likely to be an offensive producer than your typical weak-hitting full-time hurler.

    As a variation of the lineup composition theory, Freeman contended that more hit batsmen in the AL can be explained largely (but not totally, as he rightly cautions against single-theory explanations) simply by more "true" hitters coming to bat in the AL. In his words:


    American League pitchers are not given the opportunity during a game to 'ease up' their delivery to the opposing pitcher. As a result, AL pitchers are likely to 'want' or 'need' to pitch inside to more batters during the course of a game, thereby increasing the chances of these batters being hit by a pitch.

    Through an analysis of average HBP per season and per team, both before and after the introduction of the DH, Freeman concludes that there is no statistical significance (at the .001 or .005 levels) to the differences in hit batsmen across the two leagues once you adjust the averages for the fact that in the AL approximately 12.5% more true hitters come to the plate in the DH era.

    What this analysis lacks, as admitted by Freeman himself, is a more granular accounting for the differences in the number of "true" hitters, and instead relies on a quick and dirty approximation. Using Retrosheet data, we can address that weakness in the study.

    The following table shows the percentage of plate appearances consumed by each fielding position, along with the HBP per 1,000 plate appearances for both the AL and NL in the period 1973-1993.


    <----AL----> <----NL----->
    HBP / HBP /
    POS PAPct 1000 PAPct 1000
    ------------------------------------
    P 0.0% 0.0 6.8% 2.2
    C 10.1% 6.3 10.4% 4.9
    1B 11.1% 4.9 11.3% 4.8
    2B 10.9% 5.0 11.2% 4.7
    3B 10.8% 5.3 11.1% 5.7
    SS 10.3% 4.8 10.8% 3.7
    LF 11.2% 6.2 11.4% 5.0
    CF 11.4% 5.2 11.5% 4.7
    RF 11.0% 5.6 11.3% 4.3
    DH 11.2% 6.1 - -
    PH 2.0% 4.9 4.2% 3.7

    TOTAL 5.5 4.5


    In total, AL hitters were hit at a rate 20.8% higher than NL hitters.

    As you can see, in the AL designated hitters consumed 11.2% of the plate appearances, and were hit at a rate of 6.1 times per 1,000 PA. Both totals are among the highest for AL hitters. So, while the DH might be the equivalent of someone else taking Wilt's free throws, the price the DH pays is some additional pain.

    On the other side of the fence, NL pitchers consumed just 6.8% of the plate appearances, and were hit just 2.2 times per 1,000 PA. Interestingly, although the percentage of plate appearances for AL pitchers is rounded to 0%, they actually came to the plate 79 times, mostly as the result of games where the AL team lost their DH as a result of the DH assuming a defensive position per rule 6.10.

    So, rather than seeing Freeman's 12.5% more "true" hitters in the AL, in actuality AL pitchers see around 7% more true hitters when you subtract the pitchers from the NL totals. However, Freeman also noted that pinch-hitters are often used for pitchers in the NL, and this is borne out by the fact that pinch-hitters came to the plate more than twice as often in the NL (4.2%) than in the AL (2.0%). Freeman also speculated that pinch-hitters are not as likely to get hit since they are often weaker hitters than players in the regular lineup (it should be noted that as reported in The Book, there is also a "pinch-hitting penalty" that drags down performance). The lesser rate of hit batsmen for pinch hitters is verified by the data. So, assuming that the NL rate of pinch-hitting was the same as the AL rate, and throwing the remainder of the NL pinch-hitters into the bucket of poor hitters with the pitchers, we can estimate that the AL pitchers see approximately 9% more true hitters than pitchers.

    The difference between Freeman's estimate and the actual numbers lies in the fact that the vast majority of pitchers hit ninth, Dontrelle Willis being the most recent occasional exception. Hitting from the last slot in the order, pitchers therefore come to the plate less frequently than position players.

    To adjust for that, given the data in the above table, we can now make an estimate for the true differences in hit batsmen by controlling for pitcher plate appearances. One simple way to do this is to estimate what would happen if all pitcher and pinch-hitter plate appearances in the NL were consumed by a true hitter whose rate of getting hit was relatively as high as a designated hitter's in the AL. This means that 11% of the NL plate appearances (6.8% + 4.2%) will be assigned a new HBP rate based on the difference between a DH and the rest of the positions in the AL. To do so we'll first calculate the ratio of the DH rate (6.1) to the non-DH rate (5.4) as 1.13. If we assume that true hitters in the NL consuming those plate appearances would have produced 13% more hit by pitches than the non-pitchers and pinch-hitters (which turns out to be 5.4 HBP/1000 PA), then the average for the NL would jump 30% from 4.5 hit batsmen per 1,000 PA to 4.8. As a result, instead of a 20.8% advantage for the AL during the period, the true advantage is around 13.6%.

    So while accounting for a different lineup composition in the AL helps level the playing field, it obviously doesn't account for the entire difference, as Freeman concluded. We're still left with around two-thirds of our original difference between the leagues. Does that mean we're left with the moral hazard theory to explain the remaining difference?

    Readers familiar with this subject will note that this cursory analysis lines up nicely with the fine work done by J.C. Bradbury and Douglas Drinen in a paper titled "Identifying Moral Hazard: A Natural Experiment in Major League Baseball" (warning: .pdf). In that paper, using data from 1989-1992 compared against 1969 plus 1972-1974, the authors conclude that:

    "Controlling for variables that proxy batter quality, pitcher quality, retaliation, and game situation we find that the DH rule increases the likelihood that any batter will be hit during a plate appearance between 11 and 17 percent. This explains approximately 60 to 80 percent of the differential in the hit batsmen rate between leagues."

    But there are also two additional theories to consider.

    If you look back at the previous articles in this series you'll notice that the rate of hit batsmen in the AL actually surpasses that of the NL prior to the introduction of the DH. In fact, beginning in 1967, the rate of AL hit batsmen to NL went as follows:


    1967 11.5%
    1968 18.1%
    1969 -1.5%
    1970 10.1%
    1971 8.3%
    1972 11.0%


    During this six-year period the differences in the AL rate with the pitcher hitting were not much different than those immediately after the introduction of the DH. What this indicates is that hit batsmen were already more frequent in the junior circuit. Perhaps some of this remaining difference lies elsewhere.

    As mentioned last week, one of the factors that may influence hit batsmen is the definition (both written and as interpreted) of the strike zone. There is of course anecdotal evidence that the strike zone varied in the two leagues primarily as the result of AL umpires using the old-style "balloon" chest protector that forced them to stand more upright and therefore call more high strikes. And although by around 1983 AL umpires were also using the inside chest protector popularized by Bill Klem, they may have retained their traditional strike zone for some years. But still, outside of concocting what Stephen Jay Gould would call a "just-so story," there is no clear connection between high strikes and hit batsmen. A related hypothesis might be that the AL, being known as more of a curveball league, induced more hit batsmen since curveballs are inherently more difficult to control than fastballs. But both of these theories are difficult to quantify.

    A more straightforward idea is that one or two individuals skewed the numbers for this time period, accounting for the remaining difference between the leagues. This follows the dictum that when what you're measuring has inherently low frequencies, you should always be aware of a small number of samples having a large influence on the data.

    As most readers have already guessed, when you're talking about hitters and HBPs during this period, Don Baylor and Chet Lemon are two players who immediately spring to mind. Both played their entire careers in the AL, with Baylor suiting up for the Orioles, A's, Angels, Yankees, Red Sox, and Twins from 1970-88, and Lemon for the White Sox and Tigers from 1975-90. Baylor was hit 257 times in 8,888 plate appearances (defined simply as hits plus walks plus HBP for this analysis) from 1973 through 1988, for an astounding rate of 28.9 per 1,000 PA--tops during the period and ranking him 15th for players since 1901. Lemon was hit 151 times in 7,768 PA for a rate of 19.4. If these two players' rates are adjusted down to the average for the period, the overall rate for the AL drops from 5.5 to 5.3 and therefore accounts for about 4% of the remaining difference.

    In summary then, from an initial difference of nearly 21% in the rate of hit batsmen between the two leagues in the 1973-1993 period, just over 7% can be accounted for by the presence of more true hitters in the lineup and another 4% by two hitters who were exceptionally "gifted" at getting plunked. This still leaves ample room for the moral hazard theory, a theory that incorporates differences in the two leagues relating to strike zone or styles of play, or a combination of all of the above to operate.

    Evening the Score
    The second question introduced above is related to the disappearance of the difference in rate of hit batsmen between the two leagues, beginning in 1994. Since that time, the National League has actually topped the American League in five of the twelve years, as shown in the previous table.

    What can account for this dramatic shrinking of differences between the two leagues?

    First, let's take a look at the same table for the years 1994-2005 as we did for the preceding years.


    <----AL----> <----NL----->
    HBP / HBP /
    POS PAPct 1000 PAPct 1000
    ------------------------------------
    P 0.4% 1.4 5.9% 3.3
    C 10.1% 11.1 10.5% 12.8
    1B 11.1% 10.7 11.2% 10.5
    2B 11.0% 10.6 11.5% 13.1
    3B 10.8% 9.3 11.1% 9.8
    SS 10.9% 10.3 11.1% 8.5
    LF 11.2% 8.9 11.3% 10.5
    CF 11.3% 8.5 11.5% 10.0
    RF 11.0% 9.8 11.3% 10.7
    DH 10.4% 10.2 0.5% 12.2
    PH 1.6% 8.4 4.2% 10.0

    TOTAL 9.9 10.3


    What you'll notice is that the NL has outpaced the AL since 1994 despite leading in a minority of those seasons. This data set now includes interleague games, so a DH is listed in the NL column, and pitchers in the AL with the rate of hit batsmen for NL DHs even higher than that for the NL, and the rate for AL pitchers lower than in the NL. Of course, both leagues saw massive increases in their rates reflected as well.

    In a follow-up paper (another .pdf) also published in 2004 Bradbury and Drinen conclude that during the entire history of the DH, batters were about 8% more likely to be hit in games where the DH was played accounting for around half of the difference between the leagues. However, when looking only at 1994-2005 data and breaking down the data into games played with the DH and those without we find the following:


    <----DH----> <---NO DH---->
    HBP / HBP /
    POS PAPct 1000 PAPct 1000
    -------------------------------------
    P 0.0% 0.0 6.2% 2.8
    C 10.1% 10.0 10.5% 11.0
    1B 11.1% 9.6 11.2% 9.0
    2B 11.0% 9.6 11.5% 11.2
    3B 10.8% 8.4 11.1% 8.4
    SS 10.8% 9.1 11.1% 7.5
    LF 11.2% 8.1 11.3% 9.0
    CF 11.3% 7.8 11.6% 8.5
    RF 11.0% 8.8 11.3% 9.2
    DH 11.2% 9.0 - -
    PH 1.4% 7.9 4.3% 8.6

    TOTAL 8.9 8.8


    Here there is only a 1% overall difference. If one were to "correct" the data to account for lineup composition, as we did with the 1973-1993 data, you would find that games in which the DH was not in force produced 8.1% more hit batsmen per 1000 plate appearances than games without the DH. Truly, this is a large shift, for which we can offer three possible explanations.

    First, as with the 1973-1993 data, we may be seeing the influence of one or several extreme players. It just so happens that during this period the NL has been blessed with a trio of the most-frequently hit batters in the history of baseball in Jason Kendall (except 2005), Craig Biggio, and Fernando Vina (except 1995-1997 and 2004). A clue to their contribution can be seen in the previous table, where the rates for second baseman and catchers are conspicuously high in the NL. Overall, their rates during that time…


    PA HBP HBP/1000
    ---------------------------
    Kendall 5908 197 33.3
    Vina 4633 154 33.2
    Biggio 7930 245 30.9


    Don Baylor has nothing on these guys.
    If we adjust these three players' rates down to the league average for the period it drops the overall NL rate 4.3%, down to 9.8, just under the AL rate. Even so, this doesn't fully account for the fact that, given the lineup composition theory, we should see even fewer hit batsmen in the NL.

    A second theory, and one proposed by Bradbury and Drinen in their follow-up paper, targeted the expansions of 1993 and 1998 as possible factors. Although discussed in the first article in this series, this theory does accurately predict a larger increase in HBP in the NL than in the AL in 1993-1994 because of the asymmetrical nature of the expansion draft. In 1993, the HBP rate rose 7.3% in the AL and 21.6% in the NL, and for 1994 it was -6.0% and 11.6%. In the years following 1994 the rate increases evened out. But even so, one wouldn't think that NL pitchers would go on hitting more batters even after the affects of expansion were absorbed as they did in 1997 and 2000.

    The final theory, and one also proposed by Bradbury and Drinen, is that the implementation of the "double-warning rule" (8.02(d)) in the winter of 1993 had an immediate impact. Essentially, this rule raised the costs for teams hitting opposing batters, and placed that cost squarely on the pitcher and manager, both of whom can be immediately ejected from the game. One result is that AL pitchers now have a greater fear of hitting batters in retaliation lest they be ejected, thereby lowering their rate of hit batsmen. At the same time, it could be argued (as Brady and Drinen do) that NL pitchers have less fear of retaliation under the double-warning rule, since they know that the opposing team dare not hit them or their teammates or suffer the cost. The combination of more fear by AL pitchers and less fear by NL pitchers could together be responsible for essentially erasing the gap between the leagues.

    Take Your Base
    One of the reasons so many of us love baseball is that while it is seemingly simple, it is also a very human activity with naturally endless complexity. In this series of articles, I hope that we've highlighted some of that complexity in a statistically small but interesting part of the game. But while I for one love big-picture analysis, there's nothing more exciting than getting caught up in the one-on-one confrontations between pitcher and batter that are really the source of our ruminations.

    Friday, January 25, 2008

    Chat Transcript 1/25

    Thanks to everyone who showed up at the chat today. Lots of questions on SFR and defense in general that were very interesting. You can find the transcript here and as always you can use this post for follow-ups.

    Rocky Mountain SABR 2008 Hot Stove Meeting

    For anyone in the Denver and surrounding area you'll be interested to learn that the next meeting of the Rocky Mountain chapter of the Society for American Baseball Research will be held Saturday January 26, 2008. The public is welcome and if you want to know what to expect you can take a look at last year's minutes.

    We'll kick off at 10:00 AM at Jackson's All-American Grill directly across the street from Coors Field at 20th and Blake in downtown Denver.


    Our featured speaker will be Jeff Bridich, the Rockies' Director of Baseball Operations. Jeff is Harvard alumnus and was a catcher and outfielder on the Harvard baseball team serving as a tri-captain in his 2000 senior year. He formerly worked in the Office of the Commissioner for Major League Baseball where he worked closely with teams facilitating, reviewing and approving minor league contracts and transactions. Jeff became the Rockies Director of Minor League Operations in 2004 before being promoted to his current position in October of 2005.

    In addition RMSABR member Dave Wallack will lead-off with some trivia and members Dan Fox and Neal Williams will present their article on third base coaches titled "The Traffic Directors" that will appear in the next edition of SABR's Baseball Research Journal due to be published this month.

    Please join us for what will certainly be a stimulating morning of baseball discussion.

    Thursday, January 24, 2008

    Chat Tomorrow 1/25

    Just a quick note that I'll be chatting at Baseball Prospectus tomorrow at 1:30PM Eastern time for 90 minutes or so. You can submit questions beforehand here. See you then.

    SFR v1.0

    As promised in yesterday's post about Peter Gammons, today's Schrodinger's Bat on BP walks through the official release of version 1.0 of Simple Fielding Runs (for infielders anyway) and its similarities to UZR and the Plus/Minus system. As a bonus you can now download the 2005 through 2007 data in Excel to play with the numbers to your heart's content. Oh, and the 2007 minor league leaders and trailers are also discussed.

    Wednesday, January 23, 2008

    Gammons and Cyberspace

    A nice column yesterday by Peter Gammons on the impact of the Internet on the sports as well as the political culture (similar to another column he wrote back in 2006). Two quotes in the column in particular caught my eye (other than the mention of this blog, Baseball Prospectus, and The Hardball Times albeit sadly not in that order) that deserve a few comments.

    First, Gammons says:

    I make no bones about my strong feelings about the human element. Pure numbers cannot do justice to character and drive and energy. They cannot measure the impact Robin Yount had on teammates when he ran down the first-base line at the same breakneck speed (one scout had nearly 90 Yount games in a six- or seven-year period and claimed he never got Yount faster than 3.9 seconds, or slower than 4.0).

    What a wonderful anecdote and one that relates to what I found when looking at the baserunning exploits of Yount in last week's column. To summarize, Yount was the only player who was a career leader (from 1956-2007 anyway) in multiple of the five baserunning metrics. Overall Yount contributed +54 theoretical runs ranking him 13th in total number of runs. However, he was first in advancing on hits (EqHAR) at +39 runs and first in advancing on fly balls (EqAAR) at +17 runs. He did this despite costing his team 7 runs in stolen bases (EqSBR) and a half run in advancing on passed balls, balks, and wild pitches (EqOAR).

    Below you'll find Yount's career baserunning statistics.


    Year Opps EqGAR Opps EqSBR Opps EqAAR Opps EqHAR Opps EqOAR Opps EqRuns
    1974 24 0.8 15 -3.0 19 1.0 38 2.1 203 1.2 299 2.1
    1975 42 -0.9 17 0.1 37 -0.2 42 1.1 317 0.1 455 0.3
    1976 33 0.6 31 -3.9 49 -0.7 42 2.2 311 -0.6 466 -2.2
    1977 39 0.0 24 -0.5 49 0.5 63 0.4 397 -0.1 572 0.4
    1978 27 -0.4 21 0.5 32 0.4 41 0.9 278 -0.7 399 0.7
    1979 30 0.9 23 -1.1 47 2.5 43 2.6 311 2.0 454 6.9
    1980 39 1.2 27 0.7 46 1.7 46 2.5 353 0.0 511 6.0
    1981 26 -0.2 5 0.1 30 0.8 29 1.5 199 0.0 289 2.2
    1982 46 0.9 17 0.9 60 2.5 47 3.5 399 0.3 569 8.0
    1983 29 -0.8 15 -0.4 53 0.9 47 3.3 343 -0.8 487 2.3
    1984 43 -0.7 18 1.1 56 0.9 64 2.6 386 -0.1 567 3.8
    1985 20 -0.2 15 -0.7 24 0.1 51 3.5 252 -0.8 362 1.9
    1986 40 0.7 20 0.6 42 1.8 47 1.8 367 -0.4 516 4.6
    1987 39 0.0 26 -2.2 50 1.0 32 1.3 406 0.9 553 1.1
    1988 25 0.2 24 2.4 49 -0.6 45 1.1 397 0.1 540 3.2
    1989 29 1.5 21 1.6 53 0.5 61 0.4 402 -0.9 566 3.1
    1990 23 0.7 21 -1.6 46 2.1 52 2.6 360 0.6 502 4.4
    1991 16 0.5 9 -1.2 43 0.5 39 2.1 277 -1.2 384 0.7
    1992 32 0.0 20 -0.7 47 0.9 44 2.3 311 -0.6 454 1.9
    1993 16 0.3 11 0.4 30 0.2 48 1.5 258 0.4 363 2.7
    618 5.3 380 -6.8 862 16.7 921 39.4 6527 -0.5 9308 54.1



    Yount managed to turn in a positive run value in EqHAR in each of his 20 seasons - a rare feat to say the least.

    I was also interested by this comment in Gammons' piece.

    Bill James is trying to define clutch, what made George Brett so different, or sets David Ortiz, when healthy, apart in swagger and presence. You can present me with 4,765 pages of anti-Derek Jeter material; it won't work, I watch him too much.

    Although he mentions in the column that he was reading The Hardball Times apparently he didn't let Tom Tango's excellent piece titled "With or Without Derek Jeter" sink in. In that article Tom uses Retrosheet data to demonstrate without a doubt (at least to me) that Jeter is among the worst fielding shortstops of his generation by showing that when Jeter is on the field, regardless of the other context which Tom does a great job of neutralizing, fewer batted balls are turned into outs. Period. And one would think that should be the bottom line when evaluating defense.

    In tomorrow's Schrodinger's Bat at Baseball Prospectus I go one more round with the fielding system dubbed Simple Fielding Runs (SFR) that I developed for use with Retrosheet style play by play data. In the article I compare SFR to UZR (Ultimate Zone Rating) as well as John Dewan's Plus/Minus system. Not coincidentally both Plus/Minus and SFR rate Derek Jeter as the worst shortstop in baseball from 2005 through 2007 and of course UZR is no fan either. For my part, here are Jeter's SFR numbers since 2002 (ExR is expected runners, Rn is actual runners, and Balls are the number of balls allocated to Jeter's area of responsibility).


    Year Balls ExR Rn Diff SFR
    2002 461 14 10 4 3
    2003 479 119 139 -20 -15
    2004 637 154 151 3 2
    2005 721 183 195 -13 -9
    2006 625 163 174 -11 -8
    2007 615 168 194 -26 -20
    3538 800 863 -64 -47


    So over the course of six seasons Jeter is worth -47 runs by handling 64 fewer balls than would have been expected.

    What I find interesting about Gammons' comment (and his take on Jeter is of course not a rare one and so I'm not just picking on Gammons) is the almost absolute faith in observation over other evidence when the evidence from every analytical tool available concurs as to the quality of Jeter's defense. Perhaps people are simply wired differently with some inherently more skeptical of what they see (or think they see) and therefore more willing to let other kinds of input shape their opinions. I'll admit it's kind of a mystery to me.

    Tuesday, January 22, 2008

    The Catch

    Saw a link to this photo come across the SABR listserv with the author wondering whether this really does depict "The Catch" made by Willie Mays in game one of the 1954 World Series. I hadn't seen this photo before and if anyone has any comments on it I'll pass them along.



    And for those interested in the background of "The Catch", here's a snippet from the Ken Burns documentary featuring George Will and Bob Costas.

    Sunday, January 20, 2008

    Running and Tulo

    Just a head's up for those interested that I posted responses to a few reader questions on BP's Unfiltered blog in response to last week's Schrodinger's Bat column.

    Also just read the six-year deal with a club option for 2014 that Troy Tulowitzki signed with the Rockies. At $30M the deal seems like a good one for the Rockies, especially the club option that would take him through his age 28 season and buy out his second year of free agency. Certainly investing in any young player involves risk (and perhaps more so for hitters in Colorado) but in Tulowitzki the upside for the club is substantial because of his contributions on both sides of the ball. As for his fielding I had him at +18.6 runs using my Simple Fielding Runs (SFR) system, ranking second behind only Omar Vizquel.

    Thursday, January 17, 2008

    Willie, Mickey, and Hank

    My column this week on Baseball Prospectus titled "For the Sake of Completeness" ties up some loose ends with the baserunning framework by showing the results from more or less all Retrosheet years (1956-2007). To that end I not only look at the aggregate leaders and trailers and discuss the merits of Lou Brock and Dave Parker but also develop a new rate statistic that incorporates four of the five metrics. This new rate (Equivalent Base Running Rate or EqBRR) is a more "pure" measure of baserunning and using this I develop an aging curve for baserunning as a whole and by position and finally examine baserunning as a skill and its persistance across career halves.

    You'll need to read the column to get the details but in researching the article I took a look at more than a few old-timers and so I thought I'd share the baserunning exploits of Willie Mays, Hank Aaron, and Mickey Mantle.

    First, the Say Hey Kid.


    Year Opps EqGAR Opps EqSBR Opps EqAAR Opps EqHAR Opps EqOAR Opps EqBRR
    1956 22 0.3 36 1.3 30 -1.8 21 3.1 189 -1.0 298 2.0
    1957 24 -0.1 46 -1.1 43 -2.5 30 2.6 276 1.1 419 0.0
    1958 29 0.0 41 3.3 51 1.0 35 0.1 341 1.6 497 5.9
    1959 21 -0.3 37 1.1 27 1.0 54 3.3 308 1.1 447 6.2
    1960 20 -0.3 40 -0.7 35 1.9 45 1.6 308 -0.2 448 2.3
    1961 30 0.7 29 -2.2 38 0.4 37 2.5 308 0.4 442 1.7
    1962 26 0.4 25 1.0 44 2.2 53 0.5 313 -0.2 461 3.9
    1963 37 0.5 19 -2.1 34 2.0 50 -0.2 357 1.3 497 1.6
    1964 24 0.2 28 0.5 38 2.0 39 2.7 317 0.0 446 5.4
    1965 22 0.2 16 0.0 20 0.6 36 -0.7 284 1.5 378 1.5
    1966 23 -0.7 8 0.2 24 -0.9 34 -0.6 292 -0.5 381 -2.5
    1967 16 -0.6 7 1.2 19 0.7 38 2.5 235 0.9 315 4.7
    1968 17 0.8 18 -0.3 35 1.7 49 -0.4 269 0.4 388 2.3
    1969 15 0.0 8 -0.6 23 0.3 26 0.3 228 -1.0 300 -1.1
    1970 12 0.1 6 0.1 26 0.7 29 1.9 308 0.6 381 3.3
    1971 26 1.4 24 2.0 34 -0.1 33 0.8 308 0.5 425 4.6
    1972 22 0.3 9 -1.8 30 -0.8 21 0.9 144 0.4 226 -0.9
    1973 12 0.0 1 0.1 10 0.1 18 -1.4 80 0.1 121 -1.1
    398 2.9 398 2.0 561 8.5 648 19.4 4865 7.0 6870 39.9



    Mays finished 23rd in aggregate EqBRR (and of course his 1951-1955 seasons are missing) and led the league in 1958 although doing better in 1959 and pretty well in 1964 and somewhat surprisingly 1971 thanks to some high percentage base stealing. In terms of pure baserunning Mays contributed 19% more runs than an average runner which is a little on the high side for centerfielders. He seemingly was pretty good at advancing on fly balls (EqAAR), fairly average on grounders (EqGAR) and held up his own both in advancing on hits (EqHAR) and balks, passed balls, and wild pitches (EqOAR).

    Next, we have Hammerin' Hank.


    Year Opps EqGAR Opps EqSBR Opps EqAAR Opps EqHAR Opps EqOAR Opps EqBRR
    1956 32 -0.6 3 -1.7 30 0.5 32 0.6 234 0.6 331 -0.7
    1957 28 0.7 3 -1.5 37 -1.6 42 0.3 328 1.1 438 -1.0
    1958 44 1.1 4 -0.2 49 -0.5 48 1.7 321 0.3 466 2.4
    1959 25 -0.1 8 1.4 47 1.3 52 3.2 355 -0.6 487 5.2
    1960 24 1.3 23 -0.6 33 -0.6 31 1.8 228 0.2 339 2.2
    1961 23 -0.7 31 -0.4 32 1.4 37 1.2 274 1.7 397 3.2
    1962 34 -0.6 21 -1.2 34 0.6 39 0.8 296 -0.5 424 -0.9
    1963 21 0.5 39 2.7 51 0.2 45 3.7 359 -0.4 515 6.7
    1964 30 0.7 26 1.6 25 0.1 42 0.7 278 1.6 401 4.6
    1965 12 -0.2 29 -0.1 27 1.0 38 1.5 281 2.0 387 4.3
    1966 25 -0.3 24 1.5 39 1.8 53 1.6 323 0.3 464 4.8
    1967 28 1.6 24 0.1 38 1.6 45 1.3 297 -0.9 432 3.7
    1968 14 0.2 32 1.9 25 -2.7 36 1.6 226 -0.4 333 0.6
    1969 15 -0.5 21 -2.7 29 0.7 38 2.3 263 0.0 366 -0.2
    1970 21 -0.5 11 1.5 28 0.0 43 -0.5 277 -0.7 380 -0.2
    1971 15 -0.5 2 0.0 30 0.1 44 -0.7 262 -0.1 353 -1.2
    1972 18 -0.4 3 0.5 36 0.7 42 -0.1 265 -0.2 364 0.5
    1973 6 0.2 2 -0.4 19 -0.2 31 -0.7 174 -0.2 232 -1.2
    1974 12 0.3 1 0.1 17 0.1 20 -3.1 121 -0.5 171 -3.1
    1975 19 -1.0 1 -0.4 38 0.0 29 0.0 237 -0.5 324 -1.9
    1976 8 -0.1 1 -0.7 11 -0.6 11 -1.1 79 -0.4 110 -2.9
    454 1.1 309 1.4 675 4.1 798 16.1 5478 2.5 7714 25.2



    Hank does pretty well overall and was well above average runner from 1958 through 1967. He apparently slowed considerably after that though which depressed his career total substantially. Had he simply treaded water those final few years he would have been at something like +35. He led the league in 1963 with his +6.7 runs and was consistently effective in advancing on hits (EqHAR).

    Finally, The Mick.


    Year Opps EqGAR Opps EqSBR Opps EqAAR Opps EqHAR Opps EqOAR Opps EqBRR
    1956 24 0.1 13 0.7 44 -0.3 49 1.0 376 1.1 506 2.5
    1957 27 -0.4 20 1.4 49 -0.9 61 1.1 399 0.4 556 1.7
    1958 37 -0.1 23 1.9 49 0.2 57 2.9 375 0.1 541 5.0
    1959 22 -0.3 26 1.9 31 1.0 43 2.2 286 -0.9 408 4.0
    1960 26 -0.3 21 -0.3 46 -0.2 49 1.7 299 1.8 441 2.7
    1961 26 0.1 15 0.5 58 0.7 47 0.6 369 0.9 515 2.8
    1962 23 -0.7 8 1.5 39 0.1 44 0.6 290 0.6 404 2.0
    1963 13 -0.2 4 -0.9 9 -0.1 12 1.0 93 -0.4 131 -0.6
    1964 29 -0.2 9 -1.5 28 1.1 35 1.7 254 -0.9 355 0.1
    1965 12 -0.2 6 -0.2 22 -0.5 26 -0.2 173 -0.3 239 -1.4
    1966 11 -0.3 2 -0.4 20 0.3 20 -1.4 168 0.3 221 -1.4
    1967 20 -0.2 4 -1.3 33 -0.2 27 -1.0 237 -0.4 321 -3.0
    1968 23 -0.6 7 0.1 26 0.7 34 0.1 268 -0.3 358 0.0
    293 -3.3 158 3.5 454 1.9 504 10.3 3587 1.9 4996 14.4



    After 1962 Mantle's knees didn't hold up and that is reflected in his running. Before that, though he was above average and inline with most centerfielders contributing plus runs from 1956 through 1962. Interestingly, he always did poorly on advancing on ground outs (EqGAR) but could seemingly take the extra base on hits (EqHAR).

    Wednesday, January 16, 2008

    Wednesday Links

    Just a couple of notes for a Wednesday...

  • Jayson Stark had a nice live blog post on the hearings yesterday for those of use who had to work. Some pretty good perspective I think and in answering questions he brings up a few other issues worth thinking about.


  • Former BP'er Keith Woolner has a nice bio on the Science Magazine site that goes through his background leading up to his current position as Manager of Baseball Research and Analysis for the Indians. Very cool.


  • Mike Fast writes a wonderful PITCHf/x primer on MVN that explains what you need to know about f/x in seven easy steps.
  • Monday, January 14, 2008

    A Podsednik Nugget?

    As many of you know John Dewan publishes a "Stat of the Week" on the ACTA publishing site. These are often inciteful but I'm a little perplexed by the stat for last Friday January 11th which will appear in the upcoming book from ACTA Sports, The Bill James Gold Mine, available in February 2008..


    In that nugget he notes that...

    "Scott Podsednik has proven quite effective as a leadoff man. Until last year. Every year prior to 2007 Pods' teams have scored significantly more runs when he led off an inning than when others have led off."

    This is accompanied by a table that illustrates how in 2007 the team scored -.01 runs fewer per inning when Podsednik led off than when his teammates did so.

    While I haven't done exhaustive research on this I do know that Podsednik went from being a leadoff hitter in previous years to batting further down in the order in 2007. In fact, here are his plate appearances by lineup position since 2003.


    Year/Pos 1 2 3 4 5 6 7 8 9
    2003 279 291 2 27 11 2 1 15
    2004 703 8 2
    2005 564 2 2
    2006 574 2 1 11 3
    2007 89 19 3 2 27 95


    Clearly a large part of the difference is due to the fact that the two and three hitters in the order are guaraneteed to bat when Podsednik leads off an inning from the leadoff spot in the order as opposed to when he's in the 6th or 7th hole. A little follow-up would be to see whether on average when a leadoff hitter leads off an inning it typically raises scoring by at least +0.25 runs as in the case of Podsednik in previous seasons or whether his totals actually indicate that he was a hinderance in the leadoff spot (as might be guessed by his career .338 OBP). It's also the case that lineup balance will play a role since it could be the case that the two, three, and four hitters for the White Sox were relatviely more potent than the rest of the lineup when compared with other teams.

    In any case this Stat of the Week, while interesting, doesn't really show what it purports.

    Saturday, January 12, 2008

    Strike Zones, Trilobites, and a Vicious Cycle

    Last week I ran the first in a series of three columns I wrote on hit batsmen. Today it's time for the second in the series originally published In May of 2006. Enjoy.




    May 11, 2006
    Schrodinger's Bat: Strike Zones, Trilobites, and a Vicious Cycle
    by Dan Fox

    "If they knocked two of our guys down, I'd get four. You have to protect your hitters."
    --Don Drysdale

    "I hated to bat against Drysdale. After he hit you he'd come around, look at the bruise on your arm and say, 'Do you want me to sign it?'"
    -- Mickey Mantle

    In our last installment of Schrödinger’s Bat we began an investigation of hit batsmen by looking at the big-picture trends in the rate of hit batsmen since 1901. That exploration led to summarizing various theories that have been proposed over the years to explain the fluctuation of rates, including the physical hazard theory, the offensive context theory, the intimidation theory, the expansion theory, the new strike zone theory, and finally the aluminum theory. From among that group, we can say that the last one seemed to make sense for the recent upward trend that began circa 1985.

    Although I promised that this week we’d scrutinize the differences in hit batsmen rates since the introduction of the designated hitter in 1973, and discuss the theories proposed to explain it, last week’s column generated such a large volume of email that I thought it would be worth spending one more column on the big picture before moving on to the DH era.

    Big Picture Trends Redux
    Let’s start off by addressing a few of the more prevalent reader questions regarding the bevy of big picture trends discussed last week. Indicative of the questions received was this one from reader Marc Stone, where Marc touches on two aspects of HBP trends that the article overlooked.

    Nice job, Dan, but you left out one very useful comparison: how do changes in HBP compare to changes in BB rates and, to a lesser extent, K rates and pitches per PA.

    Reader Ryan Tippetts echoed the second part of that question by noting:

    My immediate thought, specifically regarding recent upward trends, was the modern trend of increased pitches per AB. Might it be as simple as because a batter sees more pitches he has more opportunities to be hit by a pitch?

    Thanks to Ryan and Marc, and to all the other readers who had similar comments. I have to admit that neither looking at walk and strikeout rates nor at pitches per plate appearance in comparison with the rate of hit batsmen had occurred to me. But of course all three suggestions make a lot of sense:


    • If pitchers are walking more batters at the same time they’re hitting more of them, that may be indicative of worse control (the “wildness theory”).

    • If strikeouts are strongly correlated with hit batsmen, then perhaps a more aggressive hitting style (the “free swinger theory”), or the intimidation of the HBP, or even changes in the strike zone are playing a role.

    • If pitchers are throwing more pitches overall, it does indeed provide more opportunity for hitters to get plunked (the “opportunity theory”) which in the end may be all that is required.


    To see whether the wildness or free swinger theories shed any light on the question of changes in HBP rates over time, we can add unintentional walks and strikeouts per 1,000 plate appearances for each league to the graph we showed last week:



    What you’ll notice is that up until around 1970, there appears to be some correlation between walk rate and HBP rate. Unfortunately, the correlation is the inverse of that which the wildness theory would predict. As walk rates increased from around 1920 through the late 1940s the rate of hit batsmen fell. As walk rates declined, the frequency with which batters were hit increased.

    In other words, one might be inclined to conclude that there is a more or less constant rate at which pitchers put batters on for free via the HBP or unintentional walk, at least based on the graph from 1901 through 1970. While that’s an attractive idea, and akin to the offensive context theory discussed last week, you can’t simply add the two rates, since hit batsmen are so much less frequent than walks--as evidenced by the fact that in order to get both on the graph, the scale of HBP is per 1,000 PA while that for walks is per 100 PA. As a result, the number of runners that pitchers put on for free is driven almost entirely by the number of walks.

    In any case, there appears to be no correlation over the past 35 years, as walk rates have been fairly steady, while the number of hit batsmen has increased dramatically.

    On the other hand, the free-swinger theory appears more promising. Strikeout rate does correlate pretty strongly with the HBP rate since around 1950, and in the 1910-1925 period as well. In fact, from 1950 through 2005 the correlation coefficients are a very healthy .72 and .69 for the American and National Leagues respectively, which can be interpreted to mean that strikeout rates explain around 50% (.702) of the variation in HBP rates (or vice versa).

    But as every statistics professor drums into the heads of his students, correlation is not necessarily causation, and before 1950 the correlation is much weaker--in fact, for the preceding 25 years the two rates were moving in opposite directions. As a result, one might argue that the free-swinger theory holds since 1950 because the normative hitting style became more aggressive, resulting in hitters diving over the plate more frequently, which in turns results in more hit batsmen. Under this interpretation, during the 1970-1984 period, free swinging was less in vogue, and pitchers reacted with fewer brushback pitches, resulting in fewer HBP.

    An alternative theory noted by reader JMHawkins that would fit the same set of facts holds that an expanding strike zone, especially on the outside corner, forces hitters to stand closer to the plate and dive over it more frequently, resulting in more batters being hit. The expanded zone also happens to induce more strikeouts, so strikeout rate and HBP rate aren’t causally related, but both are related to this third factor. There is undisputed evidence that the strike zone expanded in 1963, and anecdotal evidence that the low outside corner became an increasingly rewarding target for pitchers in the last 20 years or so. As umpires reigned in the zone after the redefinition in 1969 and the increased scrutiny around 2001, both strikeouts and hit batsmen fell. This “fluctuating strike zone theory” then explains why strikeout and HBP rate seem to mirror each other.

    In either case, we’d still need a theory to account for the preceding 25 years, when strikeouts rose and hit batsmen fell, although under the above theory it appears that those 25 years from 1925 to around 1950 are the exception and not the rule.

    To be honest, I was initially most hopeful about the opportunity theory. It's pretty well known that the number of pitches per plate appearance has been on the rise, so it makes intuitive sense, but when we try to look at this theory, we run into the problem that we don’t have complete play-by-play data--and hence pitch counts--for most of baseball's history. Despite the recent and very welcome additions to the work being done at Retrosheet we are still missing the vast majority of the data required to complete the picture from 1901 through 2005; the 49 seasons that Retrosheet provides are often missing pitch sequence data.

    Some alert readers (aka, the real stat geeks) may also be thinking that perhaps we could use pitch count estimators in order to estimate the number of pitches, and hence the rate at which batters are hit per pitch. Unfortunately, the basic estimators that are in use rely on constant multipliers for strikeouts and walks to estimate the number of pitches, and we’ve already taken those into account in the graph above. More complex estimators rely on estimates of balls-in-play rate (the percentage of pitches on which balls are put into play, which varies by league and year), which we don’t have historically. There are other factors that could also influence the result which models have difficulty capturing.

    However, we can look at data we do have, and that's as far back as 1988. You’ll recall that during the 1988-2005 period HBP rates have more than doubled. What we find, however, is that during that time the number of pitches per plate appearance has risen only around 5%. So it doesn’t look like the opportunity theory explains at least the most recent upward trend.


    Year P/PA
    1988 3.60
    1989 3.63
    1990 3.64
    1991 3.71
    1992 3.68
    1993 3.68
    1994 3.75
    1995 3.75
    1996 3.75
    1997 3.76
    1998 3.70
    2000 3.75
    2001 3.72
    2002 3.73
    2003 3.74
    2004 3.76
    2005 3.73


    What do Trilobites and Jason Kendall Have in Common?
    Although the free-swinger and fluctuating strike zone theories (or some combination thereof) provides some insight, and the opportunity and wildness theories perhaps less so, the most often cited theory by readers not discussed in last week’s column is the “body armor theory.” A succinct explanation was provided by reader Jeff Bullington:

    This would only affect the recent rise, but what about the increased use of body armor? Would this be the 'contra-intimidation theory'?

    As Jeff noted, this is the polar opposite of the intimidation theory and holds that as hitters began to wear more and more protective gear, they’ve been less afraid of getting hit, allowing them to stand closer to the plate and be more aggressive about hanging in. It follows logically that pitchers would respond by upping the ante in an effort to move batters off the plate, and reclaim their rightful territory.

    This idea is akin to the evolutionary arms race between predator and prey, whereby one species evolves stronger protection in response to selection pressure from predators as has been speculated for trilobites, which in turn leads to selection pressure on predators to evolve accordingly.

    As arguments go, this is a particularly difficult one to measure quantitatively. What we can certainly see that the use of protective gear--such as hard elbow and shin pads--has increased in the past 20 years. One only has to look at the protection worn by Craig Biggio, or Jason Kendall and consider his recent run-in with John Lackey to understand how that protection might affect the game. It’s probably not a coincidence that coming into 2006, Biggio's 273 HBPs rank second all-time, and Kendall ranks 8th with 197.

    That said, in 2002 Major League Baseball began enforcing rules that limited the use of protective gear to players with medical exemptions, such as the one employed by Barry Bonds, which allows him to wear his elbow armor. The rules also limited the size of the various pads and devices worn.

    Whether coincidentally or not, the recent Kendall incident notwithstanding, the rate of hit batsmen has stabilized since that time. This was also immediately after the rate had reached its apogee in 2001, when the AL set its all-time record in hit batsmen per 1,000 plate appearances and the NL its highest total since 1901.


    AL NL
    2001 10.67 9.92
    2002 9.90 9.17
    2003 10.21 9.86
    2004 10.40 9.60
    2005 9.52 10.05


    We can also note that although helmets have been mandatory for MLB players since 1956, ear flaps have only been enforced for players who reached the majors after 1983. Ear flaps do coincide with the recent upward trend, and although one can imagine there would be an attendant psychological boost for the hitter, it’s more difficult to believe that this relatively minor change would have had that large of an immediate impact. After all, players already in the league were allowed to use the old-style helmets, so the change was gradually phased in, and the head is the part of the body hit with the least frequency.

    But this does provide the opportunity to sneak in a quick trivia question: Who was the last player to wear a helmet without an earflap in a game and in what year? (Wait for it, we'll get to the answer at the bottom of the column.)

    So, whether or not body armor and the introduction of the ear flap is responsible for the twenty-year upward trend in HBP rates or not, an argument can be made that the crackdown on body armor has played a role in retarding the arms race.

    A Vicious Circle?
    Finally, reader Jake Slemp wrote to say that whatever the cause of an increasing or decreasing trend in hit batsmen, it would likely be self-sustaining and reinforcing. His reasoning:

    After all, hit batsmen beget more hit batsmen within the same game, which often beget still more in subsequent games between the two teams…which beget more in those games, etc.


    In other words, even a small increase in hit batsmen might form a feedback loop based on retaliation. This situation is often described in economic terms as a virtuous (if the results are favorable) or a vicious (if they are negative) circle, where each cycle continues the trend in the current direction until stopped by some outside force.

    To look at this “vicious circle theory,” we can use play-by-play data for 2001 through 2005 to examine the distribution of games by the number of hit batsmen. We can then compare the actual distribution with what would be expected if the hit batsmen were distributed randomly (in a binomial distribution) given the overall rate of HBP and the average number of plate appearances per game. What we find when we do so is as follows:


    HBP Games Expected
    7 1 0
    6 1 1
    5 10 10
    4 118 71
    3 455 394
    2 1626 1610
    1 3980 4325
    0 5953 5732
    6191 6412


    As you can see, the number of games where zero through two batters are hit are all pretty much in line with what would be expected. However, we do see that the frequency of three and especially four batters hit in a game surpass the numbers you'd expect, and there are fewer games with a single batter hit than expected. And of course this list provides the opportunity for a second trivia question: What teams were involved in the lone seven hit batsmen game of the past five years? (Again, answer appears at the bottom.)

    What this confirms is that retaliation is a likely factor in hit batsmen. Games where we would otherwise expect two batters to be hit can quickly turn into games where three or four are hit. We already knew that intuitively, but what we need to know is whether or not increased retaliation is responsible for the increasing number of hit batsmen.

    To look at this, we can calculate the expected number of games with various numbers of hit batsmen over four successive periods, starting in 1985.


    Actual vs 1985-1989 1990-1994 1995-2000* 2001-2005
    Expected
    5+ 850% 246% 322% 104%
    3 - 4 162% 125% 119% 123%
    0 - 2 100% 100% 99% 99%

    * Does not include 1997-1999.

    As we saw with the 2001-2005 period, in all periods there are just about the expected number of games with zero, one, or two HBP. However, there are always more games than expected with three or four batters hit, and lots more with five or more hit.

    While this confirms that retaliation within games is probably a persistent feature of hit batsmen, it doesn’t appear as if blatant retaliation has increased over the past twenty years. Keep in mind, the HBP rate has doubled during that time frame. If anything, it would appear there are slightly fewer beanball wars now than in the past, perhaps as a result of the double-warning rule put into effect in 1994. Note that this conclusion holds even if you assume that the increase in games with three or more hit batsmen is completely due to wildness (after all, it’s certainly true that when a pitcher hits one batter he’s more likely to hit another simply due to control problems).

    What this doesn’t rule out is the idea that teams now employ a more subtle form of retaliation, whereby they will wait to take revenge in a subsequent series, and where the retaliation doesn’t escalate out of control. As a result, it would be possible that retaliation and escalation are to blame for the recent increase in hit batsmen, but it seems unlikely.

    However, even if retaliation is not the cause of the increasing rate of hit batsmen, the body armor theory may provide the starting point for the vicious circle that was interrupted by the new rules, starting in 2002.

    Error on the Side of Caution
    If nothing else, I hope that we’ve highlighted that in an activity as complex as baseball, there are usually many factors that contribute to the big-picture trends that we see. That’s true for hit batsmen as well as the more visible trends, like the offensive upsurge of the last dozen years or so. If there is a lesson to be learned here, it’s probably that we should all be more cautious of simple explanations and easy answers.

    Let’s wrap up with a couple of corrections from last week.

    First, when discussing the expansion theory I noted that expansion would have a tendency to dilute talent in both leagues. While that’s true to some extent, I was reminded by our own Christina Kahrl that actually the 1992 expansion draft was the first time players from both leagues were available in an expansion draft. Prior to that, for example in 1977, the expansion teams could only choose unprotected players from their own league. And in that 1992 draft, AL teams were able to protect more players than NL teams; it was not until the 1997 draft that all teams were able to protect the same number of players.

    Second, I noted last week that Ray Chapman was the only professional player ever fatally injured in a game. Reader Bill Johnson pointed out that Chapman was the only major-leaguer to be fatally injured by a beanball. Several minor leaguers were killed in the 1950s and 1960s including Otis Johnson in 1951.
    ---

    Okay, so you waited, here are a couple of answers. For the first trivia question, Tim Raines never wore an earflap in a 23-year career that spanned from 1979 through 2002. As quoted in a MLB article documenting it, he did not wear one because, being a switch hitter, he didn’t want to carry two helmets.

    The answer to the second question: June 7, 2001 the A’s visited Anaheim to take on the Angels. In that game Jason Giambi was hit by Scott Schoeneweis following a first-inning home run by Frank Menechino. In the third inning, Schoenweis then hit Menechino (one wonders if accidentally) and later in the inning also hit Olmedo Saenz. Barry Zito subsequently hit Tim Salmon in the 6th. Almost certainly not coincidentally, Schoeneweis again hit Menechino leading off the 8th. Later in that same inning, Mike Holtz entered the game and promptly plunked Eric Chavez for good measure. And just to round things out Scott Spiezio was hit by Mark Guthrie in the bottom of the 8th. Ouch.

    Thursday, January 10, 2008

    Pulling for Teddy Ballgame

    My column today at BP deals with the history and of defensive shifts and delves into a little data on The Splendid Splinter's propensity to pull as well as an analysis of the most pull-happy modern players. I was inspired to take up the topic after spending several enjoyable hours digesting the essays in The 2008 Hardball Times Annual. As you might imagine I'm partial to the "Analysis" section and although I wasn't particularly impressed with one of the essays, for the thinking fan the material in the ten essays is well worth the cost of the book.

    And while I appreciated Tom Tango's work on catcher defense and an exhaustive look at what can be learned about Derek Jeter's defense from Retrosheet, John Walsh's investigation of platoon splits, David Gassko's new take on the vexing subject of managerial contributions, and John Beamer's walk through a Markov Model for the 2007 season, it was a section of the essay "Of Home Runs and Free Agents" by Greg Rybarczyk of Hit Tracker fame that caught my eye. In that article Greg has a section titled "'Did Anyone Order a Center fielder?' Case Study: All Batted Balls by Torii Hunter and Andruw Jones," in which, as the title implies, he takes an in-depth look at the balls in play for these two players, and in doing so mentions the idea of employing an infield shift against Jones. For those interested Greg has posted data from that article at SOSH.

    Great stuff and once again THT has put together a very fine collection of analytical and historical essays coupled with a look back at 2007.

    Wednesday, January 09, 2008

    Congrats to the Goose!

    When I was about 11 years old I found a list of addresses for current and former ball players in the back of a magazine. I proceeded to write very kind letters to each address and send away pictures I'd cut out of magazines, newspaper clippings, and yes, baseball cards when I had them. One of those addresses belonged to Goose Gossage and several weeks later the card was returned with his (presumably although I'm not holding my breath as to its authenticity) signature.

    Since then I've always had a soft spot for the Goose (except during the 1984 playoffs of course) and considering that he's also a native of our adopted home in Colorado Springs not to mention arguably one of the top three relievers in the history of baseball (Hoyt Wilhelm and Mariano Rivera are at the top followed closely by Bruce Sutter, Rollie Fingers, and Dennis Eckersley), I was gratified to see him get elected with 85.8% of the vote.

    It's too bad The Hawk couldn't have made it as well but he did eclipse his 2006 vote total and has risen to 65.9% making it likely he'll eventually make it. But I'd have to agree with Joe Sheehan (BTW, there are some nice moments on Hall of Fame debates with Joe, Steve Phillips, and Keith Law on ESPN that you can see here) that once Jim Rice is in (in my opinion not a Hall of Famer), there won't be any reasonable argument for keeping Dawson out.

    Beautiful Theories and Ugly Facts

    Another golden oldie from the Baseball Prospectus archives originally published on May 4, 2006



    Schrodinger's Bat: Beautiful Theories and Ugly Facts
    by Dan Fox
    May 4, 2006

    “The great tragedy of Science--the slaying of a beautiful hypothesis by an ugly fact.”

    --British biologist Thomas H. Huxley (1825-1895)

    On April 22nd, Rockies setup man Jose Mesa drilled Giants shortstop Omar Vizquel in the back with his first pitch. The next day, Giants starter Matt Morris hit both Matt Holliday and Eli Marrero in the first eight pitches he threw and was tossed from the game, along with manager Felipe Alou and pitching coach Dave Righetti. That was followed by the customary warnings to both teams, in observance of the practice that Major League baseball adopted in 1994.

    Later in the game, Jeff Francis hit Steve Finley and was not ejected, much to the consternation of what was left of the Giants coaching staff. Of course, under the double warning rule, the umpires still have discretion over whether to eject a pitcher after the warnings have been issued; a discretion that yours truly thinks is not exercised nearly as often as it should be. Finally, Ray King plunked Vizquel again in the 8th, and was ejected along with Rockies skipper Clint Hurdle.

    The Mesa/Vizquel feud dates back to 1998, when the two were still teammates with the Indians and Vizquel celebrated a spring training home run off of Mesa by doing a cartwheel afterwards. Things went downhill after the 2002 publication of Vizquel’s book Omar! My Life On and Off the Field, wherein Vizquel said of Mesa’s performance in Game Seven of the 1997 World Series:

    "The eyes of the world were focused on every move we made. Unfortunately, Jose's own eyes were vacant. Completely empty. Nobody home. You could almost see right through him. Not long after I looked into his vacant eyes, he blew the save and the Marlins tied the game.”

    Well, at least no one can accuse Vizquel of being the model teammate.

    Mesa then vowed to hit Vizquel every time he faced him, and he did exactly that on June 12, 2002, in the 9th inning of a 7-3 game when Mesa was pitching for the Phillies. And he hit him the next time the two faced each other, which was two Saturdays ago in Denver.

    Mesa is now appealing a four-game suspension handed down by Bob Watson. I kid you not, Rockies GM Dan O’Dowd said on the Rockies radio pre-game show on April 29th that he was surprised Mesa was suspended, and that he didn’t think Mesa was throwing at Vizquel. I know GMs like to stand by their players, but really…

    Putting the emotions and politics aside, of the more than 14,600 games that have been played since the beginning of the 2000 season, the April 23rd game marks the 138th time that four or more batters have been hit in the same game. Pondering that fact led me to take up the topic of hit batsmen in this week’s column.

    A Pair of Trends
    To lead off, it’s always good to have a historical perspective. In that vein, I offer the following graph that shows the number of hit batsmen per 1,000 plate appearances in both the American and National Leagues since 1901.



    There are several interesting aspects to this graph that lead us to ask two primary questions.

    First, you’ll notice that the number of hit batsmen has fluctuated fairly widely over time, with a high of 10.67 per 1,000 plate appearances in the American League in 2001 to a low of 2.82 in the American League in 1947. The rate at which batters were hit decreased steadily from the turn of last century through the late 1940s, and then increased for the next twenty years to a peak in 1968. It then decreased again until the early 1980s, but from 1985 it rose quickly through 2001, to a rate where it has since leveled off.

    We humans love causal explanation for apparent trends like this, so the first question that comes to mind is: just what is it that can explain these changes over time?

    Secondly, as you can see, batters have historically been hit at slightly different rates in the two leagues, with the American League seeing more hit batsmen from 1909 through 1928, and the National League then doing so until 1950. The leagues then traded the title back and forth until 1970 when the AL would lead for more than 20 years until the strike-shortened 1994 season. Since that time the back and forth has returned, with the AL leading seven times and the NL five. The second question then is: what are we to make of these differences between the leagues?

    In the remainder of this week’s column we’ll tackle the first question related to the overall historical trends, and leave the second--which deals with league differences--for next week.

    The Big Picture Trend
    There have been a number of theories proposed attempting to explain the historical trends we see in the rate of hit batsmen. Let’s look at them.

    On August 16, 1920 Carl Mays of the Yankees hit Ray Chapman of the Indians in the head with a pitch. The next day, Chapman died and became the only professional player ever fatally injured in a game. Although Mays was vilified in some quarters, dirty balls were also held responsible; as a result, umpires began to replace balls that had been dirtied much more often in-game.

    At first reflection, any baseball fan might assume that this tragic event would have had an immediate impact on the way the game was played, with the result being that more pitchers were afraid to throw inside, which would reduce the number of hit batsmen. Additionally, fewer soiled balls in play would theoretically allow for their being spotted more easily by hitters, which might allow them to duck, dive, or dodge the inside pitch. In either case, we’ll call this the “physical hazard” theory to explain the reduction in hit batsmen.

    While it’s a nice theory, you can see from the graph that the longer trend in the reduction of batters hit had been operative in the American League since 1911, and in the National League stretching all the way back to 1901. In fact, contrary to the theory that the Chapman beaning may have had a dampening effect, a closer examination of the period between 1919 and 1925 reveals that hit batsmen per 1,000 plate appearances actually briefly went up the year following the beaning (1921) through 1923, before resuming its downward trend.


    AL NL
    1919 6.80 6.28
    1920 6.49 5.76
    1921 6.76 5.12
    1922 7.22 5.62
    1923 7.35 5.62
    1924 6.94 4.99
    1925 5.67 4.90


    So the physical hazard theory seems to have little validity. From this, one might then reason that if that monumental event didn’t signal a change then it’s unlikely that any other isolated incident or play would have, either.

    So what about a broader theory that takes into account a cost/benefit valuation of hitting batters? For example, it could be the case that pitchers adjusted their frequency of hitting opposing batters based on their recognizing the costs of doing so. In times where runs are scarce, hitting a batter would cost relatively more than when runs are plentiful, since there is a greater probability that the batter would have been put out had they not been hit. The result is that there would be fewer hit batsmen in depressed offensive environments, and more in inflated environments. Sounds like a reasonable idea and we’ll dub it the “offensive context theory.”

    We can test this theory by taking a look at the cost of hitting a batter in terms of the Win Expectancy Framework (WX) for both the American and National Leagues since 1901. The framework allows us to estimate how much a hit by pitch is worth in terms of wins and we can then graph the results for both leagues.



    As you might have guessed, the increase in Win Expectancy for each hit batsman was high in the Deadball Era at over 3%, and then decreased from the early 1920s until the late 1930s as offensive levels rose, reaching a low point just over 2.6%. The values then began to climb again, reaching over 3% in the 1960s, and after a brief spike in 1989 fell as offensive levels rose again.

    So, does the offensive context theory hold water? If you were to overlay these two graphs you would find little in common. For example, the rate of hit batsmen in the Deadball Era declined steadily, even though the cost remained fairly constant until the offensive explosion of 1920. Offensive levels then began to decline in the late 1930s, making the cost of hitting a batter rise, although we find that hit batsmen rates continued to decline into the late 1940s. And again, as the cost of hitting batters rose in the 1950s and from 1993 on, more batters were being hit. In fact, the WX value of a hit by pitch turns out to have almost zero correlation with the rate at which batters are hit. Another beautiful theory spoiled by some ugly facts.

    Okay, offensive levels don’t seem to drive HBP rates, but what if an increased rate of hitting batters has the effect of depressing offense, and vice versa? We’ll label this the “intimidation theory.” After all, offensive levels rose as batters were being hit less often throughout the 1920s, and run-scoring dropped as batters were being hit more often in the 1960s. Many former players, especially those who had the “pleasure” of facing Don Drysdale and Bob Gibson, tend to favor this theory.

    Unfortunately, the intimidation theory has the same underlying problem as the one that preceded it. While the examples cited in the previous paragraph seem to make sense, the theory fails to explain why hit batsmen declined throughout the Deadball Era, and why in the offensive eras of the 1950s and post-1993 the rate of hitting batters has actually increased.

    Another theory that is popular, and one that we’ll tackle in next week’s column, is that since 1973 and the introduction of the designated hitter, hit batsman have been on the rise since the pitcher does not himself face the consequences of hitting opposing batters. This is the so called “moral hazard theory.” A quick glance at the first graph militates this idea, however, since the HBP rate actually began to decline in 1969, and continued to do so through the first eleven years of the DH. In addition, the rate rose and fell in both leagues, rather than affecting only the AL as you would expect.

    A couple years ago, J.C. Bradbury of the excellent blog Sabernomics along with Doug Drinen studied the issue of HBP differences using play-by-play data. One of the conclusions they came to was that talent dilution as the result of the 1993 expansion draft contributed to the rise in hit batsmen post 1993. The theory is that a greater percentage of pitchers with less experience produce more accidental hit batsmen. At first glance this “expansion theory” makes a lot of sense. Take a look at the following table that lists each expansion event along with the rates the year prior to as well as the first year of the expansion.


    Pre Post Diff
    AL 1960 5.76 AL 1961 5.22 -0.54
    NL 1961 5.48 NL 1962 6.11 +0.63
    AL 1976 5.18 AL 1977 5.42 +0.24
    NL 1992 5.48 NL 1993 6.66 +1.18
    NL 1997 9.02 NL 1998 8.38 -0.64
    AL 1997 7.78 AL 1998 8.77 +0.99


    In all but two instances, the rate of hitting batters went up in the league to which baseball added teams. It should be noted that in the first four expansions the league that did not expand also saw their rate increase, which you might expect since expansion in one league also dilutes talent in the other.

    What this table doesn’t show--though it's captured in the graph--is that the overall trends in each case were not really affected. When expansion came to the AL in 1961 and the NL in 1962 hit batsmen were already on the rise. When the AL expanded in 1977 the rates were declining and continued to do so after 1977. In both 1993 and 1998 the rates had already been increasing since 1985, and so while expansion may have egged on the increase, it clearly wasn’t the only factor. In other words, expansion did not signal a change in direction of trends that were already underway. As a result, it doesn’t appear that the expansion theory can be invoked as a general explanation and in any case can’t be invoked to shed any light on the trends prior to 1961 when both leagues had eight teams.

    Finally, there have been articles in the popular press over the past few years that argue that a confluence of factors is responsible for the increasing rate at which batters are being brushed back. For example, a 2003 article from USA Today argued that a 2000 directive from Major League Baseball to change how umpires called strikes (in order to conform more closely to the rule-book definition) was the primary culprit. The “new strike zone theory” contends that adhering to the traditional definition has resulted in calling more strikes on the inside corner, and that pitchers are taking advantage of the fact, with hitters being plunked more often as they dive out over the plate in an attempt to hit what used to be strikes off the outside corner. Unfortunately for the new strike zone theory (at least as a single explanation), the increase in batters being plunked can be traced to almost 15 years before the “new” strike zone was implemented.

    In addition, if you’re looking for single causes, one might imagine that the double-warning rule instituted in 1994 would have a dampening effect on hit batsmen. After a warning, pitchers might be wary of throwing at or near guys when they would almost certainly be ejected. However, although the rate went down slightly in 1994 in the AL, it did not in NL, and after that continued its upward trend.

    Another factor mentioned in the article, however, appears to be more promising. First, the article speculates that a generation of pitchers accustomed to pitching to hitters with aluminum bats don’t go inside as often, since doing so is less effective when hitters can still fist a ball on their hands for a hit using a bat that doesn’t shatter. As a result of this “aluminum theory,” hitters have adjusted to looking for pitches over the outside corner, and therefore dive at the ball and stand closer to the plate. When this style of hitting is coupled with pitchers who, at the professional level, finally do try and pitch inside but do poorly at it, you end up with lots more batters being hit.

    What is satisfying about this theory is that it accounts for the recent rise in HBP rates in both leagues and seems to have timing on its side. Although the first patent for a metal bat was granted in 1924, Worth didn’t introduce the first aluminum bat until 1970, and it wasn’t until the late 1970s that bats by Worth (and, especially, Easton) significantly increased the popularity of aluminum bats. Seeing the rates begin to climb five to ten years later would seem to therefore be in line.

    Systemic Theories
    In the end, theories like the aluminum bat theory are the kinds of systemic explanations that seem to be needed to explain shifts in the game such as those related to hit batsmen. Instead of looking for single incidents such as the physical hazard or strike zone theories, or very subtle causes like the offensive context or intimidation theories, what we should probably be looking for are systematic changes in how the game is played, changes that may even originate well before players reach the professional level. While I don’t have any immediate answers for the forty-year decline in the first part of last century, or the increase during the following twenty years, I think those lines of inquiry will prove to be more promising, and the theories they produce less likely to be the victim of a few inconvenient facts.

    Sunday, January 06, 2008

    Will Raines Run into the Hall?

    Probably not but Dan Rosenheck of the New York Times makes a case today in his Keeping Score column titled "Raines Could Slide Safely Into the Hall on First Try" based in part on my baserunning metrics. From everything I've read and am hearing Raines will garner roughly 50-55% of the vote and will fall short of the 75% required for induction into the Hall of Fame announced next Tuesday.

    From all accounts it appears Goose Gossage is in, Bert Blyleven is likely (on that score I heard an Sports Illustrated writer interviewed on MLB.com the other day crediting Rich Lederer and the internet for boosting Blyleven's candidacy in the past few years although he mistakenly associated Rich with Baseball Musings and not Baseball Analysts) and Jim Rice and Andre Dawson are very close. In my opinion Rice is not a Hall of Famer and I'll admit that I'm not unbiased on Dawson since I have a soft spot for "The Hawk" having watched him so much and rooted for him so often as a member of the Cubs in the 1980s.

    But in getting back to Raines Rosencheck makes the point that Raines, primarily by virtue of his extremely high stolen base percentage in an era where stolen base percentages were lower, contributed over 100 runs or 10 additional wins with his legs when measured by Equivalent Baserunning Runs (EqBRR) which is a total of all five of the core baserunning metrics. Here are his numbers sans 1999.


    Year Team Opps EqGAR Opps EqSBR Opps EqAAR Opps EqHAR Opps EqOAR Opps EqBRR
    1979 MON 3 0.1 2 0.4 1 0.0 0 0.0 11 0.2 17 0.6
    1980 MON 1 0.0 6 0.1 7 -0.2 2 0.0 17 -0.1 33 -0.2
    1981 MON 31 1.0 84 5.8 26 0.3 20 -0.8 224 0.9 385 7.3
    1982 MON 55 3.3 97 5.7 50 -0.2 32 1.2 392 0.1 626 10.1
    1983 MON 71 0.9 113 7.6 66 1.8 46 2.7 466 0.6 762 13.6
    1984 MON 49 -0.8 86 9.2 56 -1.7 48 1.8 431 -1.1 670 7.3
    1985 MON 41 1.6 82 9.4 72 0.8 55 -0.6 476 0.0 726 11.2
    1986 MON 46 -1.4 81 9.2 52 0.7 38 0.4 416 0.1 633 9.0
    1987 MON 31 -0.5 57 7.2 41 0.3 48 2.5 390 0.9 567 10.4
    1988 MON 29 0.1 40 2.4 35 0.1 27 0.0 256 0.7 387 3.2
    1989 MON 40 0.8 49 1.4 48 2.1 34 1.2 326 -1.6 497 3.9
    1990 MON 20 0.6 63 -0.2 35 1.1 36 1.1 260 0.9 414 3.5
    1991 CHA 45 0.6 66 -0.6 47 -0.4 55 1.5 403 0.6 616 1.7
    1992 CHA 41 0.3 50 5.3 66 1.5 75 3.0 437 0.1 669 10.1
    1993 CHA 47 1.2 29 0.6 36 1.4 30 0.7 303 1.1 445 5.0
    1994 CHA 21 -0.2 13 2.1 35 0.0 38 1.7 268 -0.7 375 3.1
    1995 CHA 23 -0.1 15 1.1 53 -0.6 48 0.4 388 -0.9 527 -0.1
    1996 NYA 10 -0.4 11 0.7 22 0.2 29 0.4 153 -0.7 225 0.2
    1997 NYA 23 0.2 13 -1.0 24 0.8 23 1.5 173 1.6 256 3.1
    1998 NYA 14 0.2 11 0.0 21 -0.1 33 -0.8 192 0.5 271 -0.3
    1999
    2001 BAL 0 0.0 0 0.0 0 0.0 0 0.0 2 0.0 2 0.0
    2001 MON 12 0.0 1 0.1 6 -0.2 8 -0.4 75 -0.1 102 -0.6
    2002 FLO 5 0.1 0 0.0 3 0.1 8 -0.7 62 0.6 78 0.1
    658 7.6 969 66.5 802 7.7 733 16.8 6121 3.8 9283 102.5


    The interesting thing about Raines is that he contributed with his legs so consistently for so long not turning in a sub-par season until 1995 at the age of 35. In fact, at the age of 33 he contributed 10.1 runs primarily by stealing 45 of 51 bags for the White Sox in 1992 and turning in his best season advancing on hits and contributing +3 runs. At his peak (1982-1987) Raines contributed +10.3 runs on average over a six year span and average +7.4 runs over a 15-year span from 1981-1993. He led the league in EqBRR in 1981, 1982, 1983 and 1992. Of course 1981 should be pro-rated and in a full season that +7.3 translates to more like +10. While his peak contribution and the overall run value of his baserunning in and of itself doesn't make him a Hall of Famer, when combined with his overall productivity and when noted in comparison to players like Wade Boggs it certainly casts him a better light.

    There's no doubt Raines did well on the bases but how did he stack up against the other great runners of his era? Let's start with Rickey Henderson.


    Year Team Opps EqGAR Opps EqSBR Opps EqAAR Opps EqHAR Opps EqOAR Opps EqBRR
    1979 OAK 34 -0.2 45 0.2 35 -0.4 26 0.0 222 -0.3 362 -0.8
    1980 OAK 60 0.8 135 -0.6 51 2.1 72 2.7 477 -0.6 795 4.4
    1981 OAK 31 2.4 87 -3.6 46 0.1 40 0.7 309 1.0 513 0.6
    1982 OAK 47 4.1 176 -0.2 43 0.9 29 2.6 352 0.9 647 8.3
    1983 OAK 35 0.9 132 7.8 56 1.3 41 0.1 345 1.6 609 11.7
    1984 OAK 37 0.9 86 2.4 57 2.1 51 3.9 368 0.9 599 10.2
    1985 NYA 44 2.6 97 9.8 70 1.0 48 3.1 404 2.3 663 18.8
    1986 NYA 47 0.8 115 3.8 49 1.8 31 0.6 329 2.3 571 9.2
    1987 NYA 34 -0.6 51 2.3 37 -1.1 26 1.8 236 -0.4 384 2.0
    1988 NYA 51 2.3 114 9.0 50 1.3 51 -2.0 384 3.8 650 14.4
    1989 NYA 25 0.0 41 -0.9 14 -0.2 28 0.1 141 1.2 249 0.1
    1989 OAK 24 0.3 62 3.6 40 0.2 30 1.5 148 1.2 304 6.8
    1990 OAK 44 0.7 82 4.9 45 -0.1 63 1.1 373 -0.2 607 6.5
    1991 OAK 38 -0.1 79 1.6 43 -0.6 43 2.8 324 -1.0 527 2.6
    1992 OAK 53 0.2 58 1.6 49 -1.0 34 2.9 312 -0.7 506 2.9
    1993 TOR 14 -0.7 24 3.1 21 0.1 17 0.4 100 0.6 176 3.6
    1993 OAK 32 -0.3 39 1.7 44 0.5 40 -0.8 226 0.3 381 1.5
    1994 OAK 34 -0.8 31 0.3 38 0.9 43 2.6 259 0.4 405 3.4
    1995 OAK 41 -0.3 46 -0.5 31 -0.4 34 0.5 256 -0.1 408 -0.9
    1996 SDN 55 -0.6 55 -2.3 48 -1.1 61 2.5 402 0.8 621 -0.7
    1997 SDN 19 0.0 35 1.0 40 0.2 39 1.7 192 -0.4 325 2.5
    1997 ANA 4 -0.2 10 -0.5 4 0.2 8 0.5 16 0.2 42 0.2
    1998 OAK 38 -0.5 74 1.9 41 -1.1 50 0.3 363 0.5 566 1.1
    1999
    2000 SEA 27 0.1 43 -2.3 32 1.3 26 0.3 212 -0.1 340 -0.7
    2000 NYN 16 0.4 7 -0.6 8 0.2 8 -0.6 37 0.1 76 -0.5
    2001 SDN 22 -0.3 33 0.3 36 -0.1 39 0.9 267 0.3 397 1.2
    2002 BOS 20 -0.3 12 -1.0 19 -1.1 22 1.2 161 0.1 234 -1.1
    2003 LAN 4 0.1 4 0.0 5 -0.4 5 0.0 45 0.0 63 -0.3
    930 11.7 1773 42.9 1052 6.7 1005 31.2 7260 14.6 12020 107.1


    Overall Henderson contributed five additional runs while playing in about 500 more games. In his peak seasons (1982-1988) Henderson was at +10.6 runs and averaged +7.6 from 1982 through 1993. He led the league in EqBRR in 1984, 1985, and 1988. Interestingly both Raines and Henderson were productive runners through the 1994 season which for Raines was his age 34 season and for Henderson age 35.

    As noted by Rosencheck Henderson, although the career leader in stolen bases, actually contributed more in other areas like advancing on hits and passed balls etc. than did Raines. The following table compares the four elite baserunners of the 1980s in terms of percentage of career totals in each of the five metrics.


    Name EqGAR EqSBR EqAAR EqHAR EqOAR
    Raines 7.4% 64.9% 7.5% 16.4% 3.7%
    Henderson 11.0% 40.0% 6.2% 29.1% 13.6%
    Wilson 5.9% 52.3% 12.8% 23.8% 5.3%
    Coleman 11.0% 55.9% 6.3% 15.3% 11.6%


    Raines and Vince Coleman got the most out of their stolen bases while Henderson advanced on hits more frequently, Henderson and Coleman advanced on ground outs, and Willie Wilson did so on fly balls.

    Moving on, let's look at Willie Wilson.


    Year Team Opps EqGAR Opps EqSBR Opps EqAAR Opps EqHAR Opps EqOAR Opps EqBRR
    1976 KCA 0 0.0 0 0.0 0 0.0 0 0.0 8 0.0 8 0.0
    1978 KCA 16 1.6 59 1.6 25 -0.1 19 1.9 169 0.3 288 5.3
    1979 KCA 46 2.1 99 9.2 39 0.7 46 2.8 333 0.9 563 15.7
    1980 KCA 49 0.5 93 10.0 75 4.2 61 3.9 463 0.5 741 19.1
    1981 KCA 29 -0.3 42 3.6 56 -0.6 40 0.5 309 0.5 476 3.7
    1982 KCA 46 -0.6 48 1.2 50 1.2 39 1.6 382 0.2 565 3.6
    1983 KCA 42 1.9 69 7.0 42 -0.6 39 1.4 340 1.5 532 11.2
    1984 KCA 38 1.7 55 5.1 49 2.1 48 0.8 340 -0.1 530 9.7
    1985 KCA 39 1.2 58 4.3 50 1.7 31 -1.1 315 -0.5 493 5.6
    1986 KCA 25 0.1 44 2.4 50 1.2 36 0.0 337 -1.0 492 2.7
    1987 KCA 60 0.4 69 7.1 47 0.6 36 3.9 369 0.7 581 12.6
    1988 KCA 35 0.2 42 2.2 43 0.8 48 3.8 309 1.8 477 8.8
    1989 KCA 18 -0.7 33 1.3 36 1.9 35 1.9 230 0.6 352 5.0
    1990 KCA 14 -0.7 30 1.3 30 0.5 28 1.7 175 0.0 277 2.8
    1991 OAK 18 -0.3 25 0.9 24 -0.1 19 1.0 185 -0.5 271 1.0
    1992 OAK 22 0.1 36 -0.6 33 -0.3 28 0.7 246 0.2 365 0.1
    1993 CHN 25 -0.3 9 0.2 16 0.7 17 1.0 122 0.5 189 2.1
    1994 CHN 3 -0.5 1 0.2 4 0.1 4 0.1 19 -0.1 31 -0.2
    525 6.4 812 56.9 669 13.9 574 25.8 4651 5.7 7231 108.7


    Wilson recorded the highest single-season total in my database that goes back to 1970 with his +19.1 for the AL Champion Royals in 1980 and he average +9.1 runs from 1979 through 1988. His peak was spread out a little and he led the league in 1979 and 1980. Overall he has the highest career EqBRR value at +108.7 and so for an overall package just in terms of baserunning Wilson is probably the best of the bunch in the 1980s.

    Finally, here are Vince Coleman's career totals.


    Year Team Opps EqGAR Opps EqSBR Opps EqAAR Opps EqHAR Opps EqOAR Opps EqBRR
    1985 SLN 43 1.2 147 10.7 41 0.7 51 0.6 383 -1.4 665 11.8
    1986 SLN 57 0.0 135 11.0 35 0.3 32 0.9 368 4.2 627 16.4
    1987 SLN 59 2.5 142 7.1 60 1.2 56 2.4 406 0.8 723 14.1
    1988 SLN 44 0.3 119 4.1 37 0.9 45 0.9 370 -0.2 615 6.0
    1989 SLN 59 1.0 84 3.5 47 -0.3 49 1.2 373 0.2 612 5.6
    1990 SLN 38 0.5 100 2.7 34 -0.2 39 0.6 306 1.3 517 4.9
    1991 NYN 28 0.8 54 -2.5 28 0.9 22 0.7 181 1.2 313 1.1
    1992 NYN 20 1.9 37 -0.5 21 1.1 19 1.2 172 0.4 269 4.1
    1993 NYN 31 1.6 53 -0.8 33 0.1 27 1.0 216 0.2 360 2.1
    1994 KCA 34 -0.6 64 3.2 24 0.5 31 1.3 244 0.4 397 4.8
    1995 SEA 10 -0.5 26 -0.6 20 -0.6 11 0.4 91 0.3 158 -1.0
    1995 KCA 28 -0.9 36 0.2 19 -0.3 25 0.1 133 0.5 241 -0.4
    1996 CIN 5 -0.1 14 1.0 10 0.2 8 -0.7 59 0.1 96 0.5
    1997 DET 0 0.0 0 0.0 0 0.0 0 0.0 1 0.0 1 0.0
    456 7.7 1011 39.1 409 4.4 415 10.7 3303 8.1 5594 70.0


    Coleman obviously had a peak that was more brief than the others and average +14.1 runs from 1985 through 1987 and led the league in 1986 and 1987. By 1995 at age 33 he was no longer a productive runner as he finished his career bouncing around from Kansas City, to Seattle, Cincinnati, and Detroit. Overall he contributed 30 fewer runs than the others.

    When you look at these guys in terms of EqBRR per 550 opportunities they stack up this way:


    Wilson 8.3
    Coleman 6.9
    Raines 6.1
    Henderson 4.2

    Thursday, January 03, 2008

    SFR in the Infield - AL West

    Last but not least, the AL West infielders in SFR. Mark Ellis was the overall leader for 2007 at +27 runs


    Ex
    Name Team POS Balls Runners Runners SFR
    John Lackey ANA 1 25 2 1 0.8
    Kelvim Escobar ANA 1 18 2 1 0.6
    Jered Weaver ANA 1 20 2 2 0.2
    Jeff Mathis ANA 2 21 1 0 1.1
    Casey Kotchman ANA 3 254 36 28 6.8
    Kendry Morales ANA 3 30 4 4 0.2
    Robb Quinlan ANA 3 59 8 9 -0.8
    Erick Aybar ANA 4 142 34 28 4.4
    Howie Kendrick ANA 4 364 91 88 2.0
    Chone Figgins ANA 4 26 7 8 -0.9
    Maicer Izturis ANA 4 134 35 37 -2.1
    Maicer Izturis ANA 5 127 28 25 2.4
    Brandon Wood ANA 5 31 5 6 -0.4
    Robb Quinlan ANA 5 15 3 4 -0.9
    Chone Figgins ANA 5 265 59 64 -4.6
    Erick Aybar ANA 6 45 12 14 -0.3
    Orlando Cabrera ANA 6 644 176 180 -3.2
    -----------------------------------------------------------------------
    Joe Blanton OAK 1 28 3 0 2.1
    Dan Haren OAK 1 19 2 1 0.8
    Chad Gaudin OAK 1 23 2 2 0.0
    Joe Kennedy OAK 1 23 3 4 -0.6
    Jay Marshall OAK 1 19 2 3 -0.9
    Lenny DiNardo OAK 1 21 2 6 -2.7
    Jason Kendall OAK 2 19 2 2 -0.1
    Kurt Suzuki OAK 2 16 1 2 -0.4
    Nick Swisher OAK 3 103 15 12 2.8
    Daric Barton OAK 3 35 6 4 1.6
    Dan Johnson OAK 3 193 27 27 0.1
    Todd Walker OAK 3 18 3 3 -0.1
    Mark Ellis OAK 4 695 170 134 27.0
    Marco Scutaro OAK 4 58 15 12 1.9
    Eric Chavez OAK 5 261 53 44 7.4
    Jack Hannahan OAK 5 119 27 25 1.3
    Marco Scutaro OAK 5 109 22 25 -2.3
    Bobby Crosby OAK 6 432 120 118 -1.0
    Donnie Murphy OAK 6 137 41 45 -1.2
    Marco Scutaro OAK 6 173 47 51 -2.2
    -----------------------------------------------------------------------
    Horacio Ramirez SEA 1 24 2 0 1.8
    Miguel Batista SEA 1 28 3 2 0.9
    Jarrod Washburn SEA 1 22 3 2 0.4
    Sean Green SEA 1 17 2 3 -0.6
    Felix Hernandez SEA 1 30 3 4 -0.7
    Kenji Johjima SEA 2 34 1 2 -0.4
    Ben Broussard SEA 3 87 13 15 -2.2
    Richie Sexson SEA 3 241 35 39 -3.2
    Jose Lopez SEA 4 640 159 151 5.8
    Jose Vidro SEA 4 30 7 9 -1.9
    Willie Bloomquist SEA 4 69 17 24 -5.7
    Willie Bloomquist SEA 5 45 11 11 -0.2
    Adrian Beltre SEA 5 482 98 103 -4.4
    Willie Bloomquist SEA 6 68 18 17 1.2
    Yuniesky Betancourt SEA 6 651 178 187 -4.8
    -----------------------------------------------------------------------
    Jamey Wright TEX 1 16 1 1 0.3
    Robinson Tejeda TEX 1 17 2 2 0.0
    Willie Eyre TEX 1 16 2 2 -0.3
    Kevin Millwood TEX 1 18 1 2 -0.4
    Kameron Loe TEX 1 34 3 6 -2.3
    Gerald Laird TEX 2 40 3 3 -0.1
    Mark Teixeira TEX 3 150 23 18 3.3
    Frank Catalanotto TEX 3 22 3 2 1.0
    Brad Wilkerson TEX 3 101 16 16 -0.1
    Jarrod Saltalamacchia TEX 3 55 9 11 -1.6
    Ian Kinsler TEX 4 600 152 138 10.6
    Jerry Hairston TEX 4 56 14 12 1.9
    Desi Relaford TEX 4 38 10 12 -1.5
    Ramon Vazquez TEX 4 49 13 17 -3.0
    Jerry Hairston TEX 5 19 4 4 0.2
    Hank Blalock TEX 5 109 25 26 -0.7
    Ramon Vazquez TEX 5 196 42 44 -1.7
    Travis Metcalf TEX 5 149 32 35 -2.1
    Matt Kata TEX 5 20 4 10 -4.1
    Ramon Vazquez TEX 6 58 17 12 3.7
    Michael Young TEX 6 670 188 191 -4.7

    Wednesday, January 02, 2008

    SFR in the Infield - AL Central

    Today we'll stroll through the AL Centeral and look at their infielders in terms of Simple Fielding Runs (SFR). Keep in mind that this list only includes players who were assigned 15 or more balls in their virtual area of responsibility.


    Ex
    Name Team POS Balls Runners Runners SFR
    Jon Garland CHA 1 37 4 2 1.3
    Javier Vazquez CHA 1 30 3 2 0.7
    John Danks CHA 1 16 2 1 0.6
    Mark Buehrle CHA 1 37 4 4 -0.2
    Jose Contreras CHA 1 30 3 8 -3.5
    A.J. Pierzynski CHA 2 38 2 1 0.4
    Paul Konerko CHA 3 295 42 40 1.6
    Darin Erstad CHA 3 55 7 6 1.2
    Pablo Ozuna CHA 4 17 4 5 -0.8
    Alex Cintron CHA 4 41 10 14 -2.9
    Tadahito Iguchi CHA 4 369 89 97 -5.9
    Danny Richar CHA 4 218 57 66 -6.9
    Joe Crede CHA 5 149 31 24 5.1
    Pablo Ozuna CHA 5 21 4 7 -2.1
    Angel Gonzalez CHA 5 74 16 20 -3.0
    Alex Cintron CHA 5 48 11 15 -3.3
    Josh Fields CHA 5 266 58 66 -5.8
    Alex Cintron CHA 6 68 17 18 -0.9
    Juan Uribe CHA 6 703 186 187 -4.3
    -----------------------------------------------------------------------
    Fausto Carmona CLE 1 38 3 1 1.5
    Jake Westbrook CLE 1 28 3 1 1.5
    C.C. Sabathia CLE 1 27 2 3 -0.6
    Paul Byrd CLE 1 25 3 4 -1.0
    Victor Martinez CLE 2 25 1 3 -1.3
    Travis Hafner CLE 3 22 4 2 1.3
    Victor Martinez CLE 3 58 9 8 0.5
    Ryan Garko CLE 3 253 38 44 -4.8
    Asdrubal Cabrera CLE 4 160 41 38 2.1
    Mike Rouse CLE 4 37 9 7 1.4
    Josh Barfield CLE 4 533 135 137 -1.2
    Chris Gomez CLE 5 24 5 4 0.8
    Casey Blake CLE 5 417 90 89 0.7
    Andy Marte CLE 5 51 10 12 -2.0
    Mike Rouse CLE 5 23 5 8 -2.0
    Mike Rouse CLE 6 40 11 8 1.7
    Asdrubal Cabrera CLE 6 31 9 8 1.5
    Jhonny Peralta CLE 6 725 197 212 -10.7
    -----------------------------------------------------------------------
    Nate Robertson DET 1 27 3 0 2.1
    Justin Verlander DET 1 17 2 0 1.1
    Chad Durbin DET 1 17 2 2 -0.2
    Jeremy Bonderman DET 1 19 2 4 -1.7
    Fernando Rodney DET 1 16 2 4 -1.8
    Ivan Rodriguez DET 2 43 2 0 1.2
    Carlos Guillen DET 3 52 8 4 2.4
    Marcus Thames DET 3 45 7 6 0.6
    Sean Casey DET 3 232 34 34 0.0
    Omar Infante DET 4 57 14 13 0.4
    Neifi Perez DET 4 21 5 5 0.4
    Placido Polanco DET 4 564 140 142 -1.9
    Ryan Raburn DET 4 42 11 17 -4.2
    Brandon Inge DET 5 496 107 95 9.3
    Omar Infante DET 5 33 7 6 0.6
    Ramon Santiago DET 6 94 25 22 2.5
    Omar Infante DET 6 34 8 10 -1.4
    Neifi Perez DET 6 52 15 20 -4.3
    Carlos Guillen DET 6 565 157 176 -16.9
    -----------------------------------------------------------------------
    Brian Bannister KCA 1 20 2 0 1.3
    Odalis Perez KCA 1 19 2 1 0.6
    Gil Meche KCA 1 24 2 4 -1.1
    Jason LaRue KCA 2 16 0 0 0.3
    John Buck KCA 2 34 2 4 -1.3
    Ross Gload KCA 3 174 26 21 3.5
    Ryan Shealy KCA 3 99 15 11 2.8
    Alex Gordon KCA 3 39 6 3 2.2
    Billy Butler KCA 3 24 4 4 0.3
    Mark Grudzielanek KCA 4 410 103 97 4.9
    Esteban German KCA 4 154 37 37 -0.1
    Fernando Cortez KCA 4 16 4 5 -0.6
    Alex Gordon KCA 5 403 84 85 -0.9
    Esteban German KCA 5 79 18 22 -2.8
    Tony Pena KCA 6 658 178 175 15.0
    Jason Smith KCA 6 66 17 16 -0.1
    -----------------------------------------------------------------------
    Johan Santana MIN 1 27 3 1 1.4
    Carlos Silva MIN 1 29 3 2 0.7
    Scott Baker MIN 1 16 2 3 -0.7
    Boof Bonser MIN 1 18 2 3 -0.9
    Joe Mauer MIN 2 16 0 0 0.1
    Justin Morneau MIN 3 325 46 43 2.3
    Luis Castillo MIN 4 338 82 82 0.1
    Luis Rodriguez MIN 4 47 11 12 -0.4
    Nick Punto MIN 4 101 25 27 -1.0
    Alexi Casilla MIN 4 208 55 62 -5.4
    Nick Punto MIN 5 282 53 43 7.9
    Jeff Cirillo MIN 5 37 8 3 3.7
    Luis Rodriguez MIN 5 72 14 10 3.0
    Tommy Watkins MIN 5 21 4 3 1.1
    Brian Buscher MIN 5 60 13 19 -4.5
    Jason Bartlett MIN 6 634 174 166 4.0
    Nick Punto MIN 6 118 32 38 -5.4