Defense independent pitching statistics

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"Dips" redirects here. For other uses, see dip.

In baseball, defense-independent pitching statistics (DIPS) measure a pitcher's effectiveness based only on plays that do not involve fielders: home runs allowed, strikeouts, hit batters and walks. Those plays are under only the pitcher's control in the sense that fielders have no effect on their outcome.

Several sabermetric methods use only these "defense-independent" pitching statistics to evaluate a pitcher's ability. The logic behind using only these statistics is that there is little to no difference in the abilities of Major League pitchers to influence the rate of hits against them on balls hit into the field of play. In other words, defense-independent statistics such as walks and strikeouts are determined almost entirely by the pitcher's ability level. But defense-dependent statistics, such as the rate of hits allowed on balls put into play (other than home runs), are almost entirely the result of luck and the skills of the defensive players on the field.

In 1999, Voros McCracken became the first to detail and publicize these effects to the baseball research community.[1] Until the publication of a more widely read article in 2001, however, most of the baseball research community believed that individual pitchers had an inherent ability to prevent hits on balls in play.[2] McCracken reasoned that if this ability existed, it would be noticeable in a pitcher's 'Batting Average on Balls In Play' (BABIP). His research found the opposite to be true: that while a pitcher's ability to cause strikeouts or allow home runs remained somewhat constant from season to season, his ability to prevent hits of balls in play did not.

To better evaluate pitchers in light of his theory, McCracken developed "Defense-Independent ERA" (dERA), the most well-known defense-independent pitching statistic. McCracken's formula for dERA is incredibly complicated, with a number of steps.[3] DIPS ERA is not as useful for knuckleballers and other "trick" pitchers, a factor that McCracken mentioned a few days after his original announcement of his research findings in 1999, in a posting on the rec.sport.baseball.analysis Usenet site on November 23, 1999."Also to [note] is that, anecdotally, I believe pitchers with trick deliveries (e.g. Knuckleballers) might post consistently lower $H numbers than other pitchers. I looked at Tim Wakefield's career and that seems to bear out slightly."[4] In later postings on the rec.sport.baseball site during 1999 and 2000 (prior to the publication of his widely-read article on BaseballProspectus.com in 2001), McCracken also discussed other pitcher characteristics that might influence BABIP.[5] In 2002 McCracken created and published version 2.0 of dERA, which incorporates the ability of knuckleballers and other types of pitchers to affect the number of hits allowed on balls hit in the field of play (BHFP).[6] [7]

The controversy over DIPS was heightened when Tom Tippett at Diamond Mind published his own findings in 2003. Tippett concluded that the differences between pitchers in preventing hits on balls in play were at least partially the result of the pitcher's skill.[8] Tippett analyzed certain groups of pitchers that appear to be able to reduce the number of hits allowed on balls hit into the field of play (BHFP). Like McCracken, Tippett found that pitchers' BABIP was more volatile on an annual basis than the rates at which they gave up home runs or walks. It was this greater volatility that had led McCracken to conclude pitchers had "little or no control" over hits on balls in play. But Tippet also found large and significant differences between pitchers' career BABIP. In many cases, it was these differences that accounted for the pitchers' relative success. Many subsequent studies have been done, with varying conclusions.

Despite recent criticism, the work by McCracken and others on DIPS is regarded by many in the sabermetric community as the most important piece of baseball research in many years. McCracken's work showed that this effect is smaller than the conventional wisdom had assumed.

DIPS ERA was added to in 2004.[9]

[edit] Alternate Formulae

A simpler formula, known as Defense-Independent Component ERA (DICE),[10] was created by Clay Dreslough in 2001 and can be calculated using simple math:

DICE=3.00 + \frac{13HR + 3(BB + HBP) - 2K}{IP}

In that equation, "HR" is home runs, "BB" is walks, "HBP" is hit batters, "K" is strikeouts, and "IP" is innings pitched. That equation gives a number that is better at predicting a pitcher's ERA in the following year than the pitcher's actual ERA in the current year.

Tom Tango, an internet sabermetrician, at approximately the same time independently derived a similar formula, known as Fielding Independent Pitching,[11] which is very close to the results of dERA and DICE.

FIP=\frac{13HR + 3BB - 2K}{IP}

In that equation, "HR" is home runs, "BB" is walks, "K" is strikeouts, and "IP" is innings pitched. That equation gives you a number that is nothing close to a normal ERA, so the equation used is more often (but not always) this one:

FIP=\frac{13HR + 3BB - 2K}{IP}+3.20

That equation gives a number that is much closer to a potential pitcher's ERA.

The Hardball Times, a popular baseball statistics website, uses a slightly different FIP equation, instead using 3*(BB+HBP) rather than simply 3*(BB) where "HBP" stands for batters hit by pitch.

[edit] See also

[edit] Footnotes

  1. ^ http://groups.google.com/group/rec.sport.baseball.analysis/msg/b450fe58c05a5a82?hl=en&lr=
  2. ^ Baseball Prospectus | Articles | Pitching and Defense
  3. ^ Defense Independent Pitching Stats Part II
  4. ^ http://groups.google.com/group/rec.sport.baseball.analysis/browse_thread/thread/f9f708f94ccb8696/b450fe58c05a5a82?lnk=st&q=+voros+%EE%8A%B7nse-independent-pitching-stats#b450fe58c05a5a82
  5. ^ http://www.baseballthinkfactory.org/files/newsstand/discussion/vorosmccracken_me_being_arrogant_again/P100/ in item 188
  6. ^ BBTF's Primate Studies Discussion :: DIPS Version 2.0
  7. ^ Defense Independent Pitching Stats, Version 2.0 Formula
  8. ^ Diamond Mind Baseball
  9. ^ http://sports.espn.go.com/mlb/statistics ESPN.com's Sortable Stats
  10. ^ Sports Mogul | Official Site for Baseball Mogul and Football Mogul | Online Multi-Player Games for Fantasy, Rotisserie and Computer Sports Fans
  11. ^ http://www.tangotiger.net/drspectrum.html
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