Defense independent pitching statistics

In baseball, defense-independent pitching statistics (DIPS) (also referred to as fielding-independent pitching, or FIP) is intended to measure a pitcher's effectiveness based only on statistics that do not involve fielders (except the catcher). These include home runs allowed, strikeouts, hit batters, walks, and, more recently, fly ball percentage, ground ball percentage, and (to a much lesser extent) line drive percentage. By focusing on these statistics and ignoring what happens once a ball is put in play, which – on most plays – the pitcher has little control over, DIPS claims to offer a clearer picture of the pitcher's true ability.

The most controversial part of DIPS is the idea that pitchers have little influence over what happens to balls that are put into play. Some people believe this has been well-established (see below), primarily by showing the large variability of most pitchers' BABIP from year to year. However, there is a wide variation in career BABIP among pitchers, and this seems to correlate with career success. For instance, no pitcher in the Hall of Fame has a below-average career BABIP.

Origin of DIPS

In 1999, Voros McCracken became the first to detail and publicize these effects to the baseball research community when he wrote on, "I've been working on a pitching evaluation tool and thought I'd post it here to get some feedback. I call it 'Defensive Independent Pitching' and what it does is evaluate a pitcher base[d] strictly on the statistics his defense has no ability to affect..."[1] Until the publication of a more widely read article in 2001, however, on Baseball Prospectus, 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 prevent home runs remained somewhat constant from season to season, his ability to prevent hits on 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 very 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 Usenet site on November 23, 1999, when he wrote: "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 site during 1999 and 2000 (prior to the publication of his widely read article on 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]


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 Tippett also found large and significant differences between pitchers' career BABIP. In many cases, it was these differences that accounted for the pitchers' relative success.

However, improvements to DIPS that look at more nuanced defense-independent stats than strikeouts, home runs, and walks (such as groundball rate), have been able to account for many of the BABIP differences that Tippet identified without reintroducing the noise from defense variability.[9]

Despite other criticisms, the work by McCracken on DIPS is regarded by many in the sabermetric community as the most important piece of baseball research in many years. As Jonah Keri wrote in 2012, "When Voros McCracken wrote his seminal piece on pitching and defense 11 years ago, he helped change the way people—fans, writers, even general managers—think about run prevention in baseball. Where once we used to throw most of the blame for a hit on the pitcher who gave it up, McCracken helped us realize that a slew of other factors go into whether a ball hit into play falls for a hit. For many people in the game and others who simply watch it, our ability to recognize the influence of defense, park effects, and dumb luck can be traced back to that one little article".[10]

DIPS ERA was added to's Sortable Stats in 2004.[11]

Alternate formulae

Each of the following formulas uses innings pitched (IP), a measure of the number of outs a team made while a pitcher was in the game.[12] Since most outs rely on fielding, the results from calculations using innings pitched are not truly independent of team defense. While the creators of DICE, FIP and similar statistics all suggest they are "defense independent", others have pointed out that their formulas involve innings pitched (IP). Innings pitched is a statistical measure of how many outs were made while a pitcher was pitching. This includes those made by fielders who are typically involved in more than two thirds of the outs. These critics claim this makes pitchers' DICE or FIP highly dependent on the defensive play of their fielders.[13]


A simple formula, known as Defense-Independent Component ERA (DICE),[14] was created by Clay Dreslough in 1998:

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.[15]


Tom Tango independently derived a similar formula, known as Fielding Independent Pitching,[16] which is very close to the results of dERA and DICE.

In that equation, "HR" is home runs, "BB" is walks, "K" is strikeouts, and "IP" is innings pitched. That equation usually gives you a number that is nothing close to a normal ERA (this is the FIP core), so the equation used is more often (but not always) this one:[17]

where C is a constant that renders league FIP for the time period in question equal to league ERA for the same period. It is calculated as:

where lgERA is the league average ERA, lgHR is the number of home runs in the league, lgBB is the number of walks in the league, lgK is the number of strikeouts in the league, and lgIP is the number of innings played in the league.

The Hardball Times, a popular baseball statistics website, uses a slightly different FIP equation, instead using 3*(BB+HBP-IBB) rather than simply 3*(BB) where "HBP" stands for batters hit by pitch and "IBB" stands for intentional base on balls.[18]


Dave Studeman of The Hardball Times derived Expected Fielding Independent Pitching (xFIP), a regressed version of FIP. Calculated like FIP, it differs in that it normalizes the number of home runs the pitcher allows, replacing a pitcher's actual home run total with an expected home run total (xHR).[19]

where xHR is calculated using the league average home run per fly ball rate (lgHR/FB) multiplied by the number of fly balls the pitcher has allowed.

Typically, the lgHR/FB is around 10.5%, meaning 10.5% of fly balls go for home runs. In 2015, it was 11.4%.[20]


Baseball Prospectus invented this statistic, which takes into account balls in play and adjusts for balls in play. For example, if a pitcher has a high xFIP, but also induces a lot of ground balls and popups, his SIERA will be lower than his xFIP. The calculations for it are as follows:

See also


  1. "Google Groups". Google Groups. Retrieved 2020-08-23.
  2. Voros McCracken, "Pitching and Defense: How Much Control Do Hurlers Have?,", January 23, 2001.
  3. "Defense Independent Pitching Stats Part II".
  4. "Google Groups". Google Groups. Retrieved 2020-08-23.
  5. "BBTF's Newsblog Discussion :: vorosmccracken: Me Being Arrogant Again". Baseball Think Factory. 2007-11-16. Retrieved 2020-08-23.
  6. "BBTF's Primate Studies Discussion :: DIPS Version 2.0".
  7. "Defense Independent Pitching Stats, Version 2.0 Formula".
  8. "Baseball Articles". Diamond Mind Baseball.
  9. "GB%, LD%, FB% | Sabermetrics Library".
  10. Jonah Keri, "Fantasy Fiesta: Pitching Stock Tips," Grantland, June 7, 2012.
  11. "2020 MLB Stat Leaders". ESPN.
  12. For an extended overview of the development of DIPS and alternative formulas, see Dan Basco and Michael Davies, "The Many Flavors of DIPS: A History and an Overview," Society for American Baseball Research, Baseball Research Journal, Fall 2010, Vol. 32, Issue 2. [retrieved 2-26-2013]
  13. "Granny Baseball: Fielding Independent Pitching (FIP) Isn't Fielding Independent". June 10, 2010.
  14. "Sports Mogul | Official Site for Baseball Mogul and Football Mogul | Online Multi-Player Games for Fantasy, Rotisserie and Computer Sports Fans". Archived from the original on 2007-05-28. Retrieved 2006-02-13.
  15. "Defense-Independent Component ERA (DICE) Calculator (Baseball)". Captain Calculator.
  16. "Archived copy". Archived from the original on 4 August 2004. Retrieved 13 January 2022.{{cite web}}: CS1 maint: archived copy as title (link)
  17. "FIP". Fangraphs. Retrieved 25 August 2016.
  18. FIP — Hardball Times Glossary.
  19. "xFIP". Fangraphs. Retrieved 25 August 2016.
  20. "Fangraphs - Pitching League Stats - Batted Ball". Fangraphs. Retrieved 25 August 2016.
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