There are a number of different things to get out of the way before the meat and potatoes of this post. Most importantly, the idea for this fun little exercise came from the article "How Good Is Your #4 Starter?" by Jeff Sackmann and the follow-up "More Fun With Rotation Numbers." He used ERA to calculate his numbers and I will have another post soon utilizing ERA. For this post, however, I am using FIP, or Fielding Independent Pitching. FIP attempts to measure a pitcher's worth through the outcomes for which he is directly responsible during a game: home runs, hit batsmen, bases on balls, and strikeouts. In this way, defense largely is taken out of the equation. Thus, FIP is not affected in the same way ERA would be for a pitcher if he had eight David Ortiz's on the field with him.
The formula I use is (HR*13+(BB+HBP)*3-K*2)/IP + 3.2 = FIP. In actuality, the constant should be slightly larger than 3.2, depending on the league, but since I don't know exactly how much larger, I used 3.2 for simplicity's sake. Since it affects everyone in the NL, no one is given an unfair advantage.
In order to determine the numbers for each team's rotation spots, I figured the ideal rotation would give a team 33 starts by their #1 and #2 pitchers and 32 starts by the other three (San Diego and Colorado both had an extra start by their #3 starter for my calculation). Using this idea, I took the weighted average of the team's top 33 starts by FIP to determine the FIP for rotation spot #1, and so on for the other four spots.
Example, to determine the #1 spot for the Brewers, I would see that Yovani Gallardo had 17 starts with a 3.49 FIP, Manny Parra had 2 starts with 3.87 FIP and Ben Sheets had 24 starts with a 4.07 FIP. Sheets' starts are split between the #1 and #2 spot and you get
- #1 FIP = (17*3.49+2*3.87+14*4.07)/33 = 3.76
The SFIP column stands for "Starter FIP" for each team, i.e., the FIP put up only by starting pitchers in games they started. The NL averages were computed by simply taking the average of each team's FIP in each spot. The NL FIP was computed by applying the FIP formula to the raw numbers of HR, HBP, BB, K and IP throughout the league. The STDEV column is the standard deviation of the team's five rotation spots. The smaller the number, the closer together the five spots are and the more "even" a team's rotation is. This is fallible, in the sense that a team with a great ace will appear to have an uneven rotation even if the #4 and #5 starters really aren't that bad.
Finally, as Jeff said in his follow-up article:
These calculations don't hold the key for any breakthrough new approach to roster construction, but they do illustrate some of the ways in which good (or lucky) teams are different from bad ones.Now that the explanation is out of the way, on to the table!
|San Diego Padres||3.82||2.80||3.38||3.54||4.37||5.67||1.11|
|Los Angeles Dodgers||4.22||3.59||3.90||4.02||4.37||5.55||0.76|
|San Francisco Giants||4.28||3.55||3.77||4.43||4.81||5.03||0.64|
|New York Mets||4.59||3.80||4.29||4.72||4.82||5.54||0.65|
I guess the old adage "pitching wins championships" didn't hold especially true in the NL this year as Chicago and Arizona were the only teams to be much above league average in FIP from their starters and they were still very close to the mean. Another thing I noticed that kind of surprised me was how mediocre Florida's starters were. Granted a team losing 90 games generally won't have very good starters in the first place, but I was shocked to find out they only got 37 starts all season from a pitcher winding up with an ERA below 5.00 as a starter (27 from Sergio Mitre, 6 from Anibal Sanchez and 4 from Ricky Nolasco). Furthermore, they only got 42 starts from a pitcher with an FIP under 5.00. That's perversely impressive.
Regardless, simply seeing the numbers might not strike your fancy. Let's look at which starters came closest to each rotation spot's average, in order to give some context.
First, here are the starters that were "aces" (3.69 or lower FIP) in 20 or more starts:
- Jake Peavy, 34 starts, 2.80 FIP
- John Smoltz, 32, 3.17
- Brandon Webb, 34, 3.20
- Chris Young, 30, 3.39
- Tim Hudson, 34, 3.42
- Greg Maddux, 34, 3.54
- Roy Oswalt, 32, 3.55
- Brad Penny, 33, 3.59
- Tim Lincecum, 24, 3.59
- Aaron Harang, 34, 3.67
Let's see who fits the mold as a #2 starter (~4.25 FIP):
- Chris Capuano, 25 starts, 4.16 FIP
- Tom Gorzelanny, 32, 4.20
- Rich Hill, 32, 4.28
- Oliver Perez, 28, 4.30
Our #3 starters (~4.69 FIP):
- Paul Maholm, 29 starts, 4.56 FIP (everyone between Maholm and Davis had less than 20 starts)
- Doug Davis, 33, 4.68 FIP
- Micah Owings, 27, 4.78
- Braden Looper, 30, 4.79
Alright, we're headed to the back half of the rotation. The #4 starters (~4.98 FIP):
- Jason Marquis, 33 starts, 4.94 FIP
- Jamie Moyer, 32, 5.00
- Anthony Reyes, 20, 5.02
- Dontrelle Willis, 35, 5.09
Finally, we've reached the land of the damned--er, I mean the #5 starters (~5.83 FIP):
- Livan Hernandez, 33 starts, 5.73 FIP
- Byung-Hyun Kim, 22, 5.76
- Adam Eaton, 30, 5.93
- Mike Bacsik, 20, 6.38
To recap, the National League average rotation would look like this:
- Aaron Harang
- Rich Hill
- Doug Davis
- Jamie Moyer
- Byung-Hyun Kim/Adam Eaton
I'll be putting up a similar post using ERA soon. I think this sort of number-crunching is interesting, if not especially useful.