Baseball - Understanding Statistics Part Five

Having covered the primary pitching statistics in the ERA, WHIP, BAA and the 'luck' statistics in the BABIP, we move on to the last two statistics that handicappers may use to gauge a pitcher’s performance: the recently devised FIP and xFIP statistics which are freely available at The Hardball Times and Fangraphs site. xFIP stands for Expected Fielding Independent Pitching and is defined by the Hardball Times as:

FIP and XFIP

”xFIP: Expected Fielding Independent Pitching: an experimental stat that adjusts FIP and "normalizes" the home run component. Research has shown that home runs allowed are pretty much a function of flyballs allowed and home park, so xFIP is based on the average number of home runs allowed per outfield fly. Theoretically, this should be a better predictor of a pitcher's future ERA. “

Below is the definition of FIP as defined by the Hardball Times.

”FIP: Fielding Independent Pitching, a measure of all those things for which a pitcher is specifically responsible. The formula is (HR*13+ (BB+HBP)*3-K*2)/IP, plus a league-specific factor (usually around 3.2) to round out the number to an equivalent ERA number. FIP helps you understand how well a pitcher pitched, regardless of how well his fielders fielded.”

In simple terms, the theory is that the FIP statistic lends itself to factors that pitchers can control (Ks, BBs, HBP, HRs) and eliminates the factors that are out of their control (what happens on balls in play, whether an outfield fly ball turn into a Home Run). But whilst FIP is a general statistic on all things pitchers can control, the xFIP takes all the statistics a pitcher responsible for but adjusts the home run component to the league average thus making the assumption all pitchers allow the a similar number of home runs per flyballs.

As a statistic, the FIP and xFIP has flaws and does not take into consideration the DER (Defensive Efficiency Ratio) and like the BABIP, knuckleballers look to have an advantage as they have offspeed pitches and actively encourage contact thus misleading handicappers with its homogenised application. There are no adjustments for park factors as pitching in PETCO Park is vastly different to pitching at Citizens Bank Park given their differing dimensions.

When analysing FIP statistics, we use the ERA to compare against the FIP and xFIP in order to gauge probabilities. This is useful tool when trying to seek out undervalued and overvalued pitchers. This also helps us to deduce the standard of defensive support he has received from his fielders. As a rule when comparing FIP to ERA – if you subtract the ERA from his FIP and come up with a high negative number, that would be a sign that the pitcher pitched better than his ERA indicated and that his defence and/or bullpen let him down. Whilst that may seem simplistic, you have to remember to combine other statistics such as BABIP, K/9, BB/9 to rationalise the interpretation you choose to take. If a pitcher has a lower ERA then his FIP, that could be interpreted as a lucky season and he could regress to his FIP numbers.

The xFIP statistics is gaining credibility with a lot of handicappers who believe it represents a pitcher’s pure ability but xFIP has flaws in its theory. You could argue basic statistics like groundball/flyball ratio, or flyball percentage are better predictors of future HR rate then the xFIP. Just to be clear, an xFIP below actual ERA suggests that the pitcher has been unlucky, whereas an xFIP above actual ERA suggests that the pitcher has been lucky. One thing the xFIP accounts better is in the home run component.

Sabermetricians believes the history of home runs allowed per flyballs among pitchers stands at a constant 10-11% and will stand the test of time, thus instead of an individualistic component in FIP, the xFIP is viewed as a much better indicator of a pitcher’s ability. It doesn’t matter if a pitcher has kept home runs down during the course of the current season the regression to the mean assumption is made. I.e. A pitcher who has yet to give up a home run in the first two months of the season will regress to the mean and give up his “fair share” of homers.

Jered  Weaver

But like all statistics, the xFIP on its own does not factor in the human element. It doesn’t tell us whether pitchers like Jered Weaver, Matt Cain and John Lackey has flyball tendencies or differentiate between the likes of Wang, Lowe, Webb who are all noted sinkerballers.

Whilst there is substance in the statistics, the fact that xFIP apply a general formula to all types of pitchers sit uncomfortably with myself. The BABIP, you could argue has the same demerits regarding its validity but BABIP does not focus on one particular style of pitching. It notes all balls that are in play, a line drive, a groundball, a home run and a flyball. As noted above, pitchers are individuals with differing characteristics in their mechanics, pitches, and repertoires.

For example, with the xFIP based on a standardised HR/FB component, it doesn’t tell us the human element. On one hand you have pitchers who can regularly induce weaker flyballs because their repertoire of pitches are built to induce those kinds of outs. For example, if a pitcher throws a high fastball and contact is made, the most likely result is an infield popup. On the other hand you have pitchers who cannot prevent their flyballs from being a home run, because their repertoire does not have enough variance to unbalance hitters or because they pitch in a bandbox they call home. Unlike BABIP, the league average is uncertain with lack of multi-year sample sizes. The xFIP can be both helpful and misleading and whilst it is still in its early stages of use, an established number has yet to be established in terms of benchmark.

Every high or low xFIP can be explained through the type of pitcher producing those numbers and shouldn't be generalised. In between you'll have pitchers with deeper repertoire with evenly ratios of groundballs and flyouts who can induce outs in any number of ways.

Since it is still in its early stages compared to the traditional methods such as ERA, WHIP, it is worth keeping an eye on FIP and xFIP stats throughout the season. You may just spot a formula yourself and become the next Bill James!!

Giant_Causeway