2011 Pac-12 FIP Findings

Last year on my old blog, the WSU Baseball Blog, I set out to create an FIP constant for the Pac-12. Compiling the numbers was easy but a tad bit time consuming. I then defined FIP and published my findings on the blog; other than my draft day coverage no article I wrote ever there ever had more page views. Since it was such a hit last year I figured I'd go ahead and do it again this year!

After the jump I will describe FIP (and why we like it here more than ERA), show you the formula for finding FIP, present my results from the 2011 season and talk about what it all means.

FIP is shorthand for Fielding Independent Pitching, w use FIP instead of ERA here because it is a more accurate way to analyze pitchers (over a large sample size). ERA takes things into consideration that are not of the pitchers control, things such as batted balls falling into play at a higher than league average rate and overall defensive ability of the pitchers team.

When we look at FIP we are using a metric placed on the same scale as ERA so they're easy to compare, but FIP simply analyzes the pitcher in a vacuum. Essentially trying to determine the pitchers run impact on their team through actions that can be directly attributed to the pitcher and no one else.

So, what can pitchers control? When you get down to it pitchers can only really control home runs allowed, walks, HBP, and strikeouts. Some would argue that ability to limit extra base hits can be attributed to a pitchers ability to "aim" their pitches, but that's a different discussion for a different post.

FIP can be thought of as a predictive metric as well as an analytical one, as it much better predicts future pitcher performance than ERA while also being useful when analyzing a pitchers past body of work. xFIP is the best predictive metric for future pitching performance but is currently impossible to calculate at the college level.

To calculate FIP we use the following formula:

The only problem we run into with college baseball stats is that this constant is not created by anyone (that I know of) so we are unable to properly use FIP until we get that constant. So last year and this year I decided to go about finding that constant.

In MLB there is usually a separate constant derived for both the AL and NL, because pitching is simply different in each league. So instead of derive a constant for all of college baseball I decided it would be best to create one for the Pac-12, so the constant we use here is based off the results of 11 teams pitching staffs, totaling a sample size of 138 pitchers.

When you do not already have a constant you do the following to derive one:

• Calculate league average ERA
• Calculate league average FIP using the same formula as above, without the constant
• Subtract league average FIP from league average ERA to get the FIP constant

Without looking at my actual spreadsheet (linked below and in this chart) I have superficial results for you here:

Year	League Average ERA	League Average FIP	FIP Constant
2010	5.05	1.32	3.72
2011	5.02	0.94	4.08

Since we know FIP analyzes pitchers in a vacuum, therefore removing batted ball data from the equation, we can take away two things from this above chart.

1. ERA across the two years I've been looking at this data stayed nearly exactly the same, dropping only 0.03. If you simply look at this number alone one would assume pitching success was equal in the two years analyzed, however this would be wrong. What this means is that batted balls in play fell for hits at either equal, or in this case higher, rate to the year prior.
2. League average FIP plummeted from 2010 to 2011, dropping a whole 0.38, a significant amount. This tells us that pitching drastically improved from 2010 to 2011, the only reason ERA stayed constant over that period is because an abnormally high amount of batted balls fell into play for hits in 2011, inflating the league's average ERA.

In MLB the FIP constant generally hovers around 3.2, making last years 3.72 high and this years 4.08 incredibly high.
I'll be along sometime in the next few weeks with analysis of these numbers, particularly focusing on WSU pitchers and other conference pitchers who either significantly underperformed or overperformed. 
If you would like to explore all of the numbers across the Pac-12 for 2011 you can click here to view my spreadsheet.