It’s almost Truck day and the Red Sox players are almost ready to get started. What better time to start a review of the stats we most commonly use at Fire Brand? We’ll try to cover as many as we can and hope you’ll ask questions if you have any or feel free to comment on potential pitfalls of the different stats.
FIP is right up there with WAR as one of the most common stats people get introduced to statistical analysis with. An early and neutral attempt to value a pitchers ability. FIP or Fielding Independent Pitching is a fairly straight forward computation created by Tom Tango:
FIP=((HR*13+(BB+HBP-IBB)*3-K*2)/IP)+3.2
The resulting answer is an estimate of what a pitchers ERA would equal if his defense had been league average and he had given up a league average number of home runs. The pitcher has no* control over his defense and mostly no control over how many home runs he gives up. He can limit fly balls, but how many turn into home runs is mostly a factor of league and ball park factors.
*There is some debate about how much control a pitcher might have on his BABIP. Most studies have found some effect, but the amount is relatively small and FIP is mostly accounting for the defense.
To fix this Dave Studeman from The Hardball Times has removed a bit of the home run effect. To do this he replaced home runs with a pitchers fly balls against multiplied by the average league home runs given up per fly balls (11%). The new equation is as follows:
FIP=(((FB*.11)*13+(BB+HBP-IBB)*3-K*2)/IP)+3.2
This equation can be helpful, but has some flaws as well. While almost all pitchers average to a HR/FB near 11 percent it’s not a sure thing. Some home parks and leagues like the NL West have built plenty of pitchers who benefit by averages below the league average.
Using FIP in Context
As I stated before there is no perfect stat and FIP is not an end all pitching stat. In debating a pitcher you must identify if FIP is actually showing the true skill or is there a reason ERA might be a better measure. A good case I recently debated was Joe Saunders who has a career ERA of 4.16, but a FIP of 4.65. A swing of .50 runs is pretty big and says perhaps Saunders has a skill at controlling those factors that FIP assumes are out of his control.
If he is controlling a stat it would be BABIP, but after playing for several good teams defensively and having two extremely lucky seasons it’s tough to say he actually has an added skill. Another factor that could explain differences in FIP is LOB% (Left on Base percentage). Again a stat that could be a fault of defense, skill or luck.
FIP or xFIP are not always the answer and are not always predictive of skill, but both are easy to calculate and have a very high level of projection of future results. No pitching stat can fully test pitching “skill”, but FIP and xFIP are fair judges of talent as long as you can read the context and see potential reasons to doubt it.