(Special thanks to David Gassko for suggesting this topic and helping me understand the techniques I used. Any errors, of course, are due solely to me).

Fielding Independent Pitching (FIP) is a concept developed by Tangotiger and is similar to the Defense Independent Pitching Statistics (DIPS) created by Voros McCracken. According to the Hardball Times, "FIP helps you understand how well a pitcher pitched, regardless of how well his fielders fielded." To calculate a pitcher's FIP ERA for a given year, I normalized his stats using how many standard deviations from the mean he was in HRs, BBs, and Ks. Only pitchers with 150+ IP in a season from 1920-2005 were included.

Here was the process:

- Calculate the standard deviation (SD) for each league in each year for the following stats: HRs, BBs, and Ks (all per IP).

- Calculate how many SDs above or below the mean (or average) each pitcher was in each of those stats. HRs were park adjusted.

- Calculate the mean (or average) HRs, BBs, and Ks (all per IP) for the entire period.

- Calculate the SD for HRs, BBs, and Ks (all per IP) for the entire period (those were .0353, .1966, and .1033, respectively).

- Calculate the FIP ERA for each pitcher in each year. Since FIP ERA = Constant + 1.44*HR + .33*BB - .22*K, there are some preliminary steps (in this case HRs, BBs, and Ks are per 9 IP).

B. Each pitcher's HRs, BBs, and Ks per IP had to be adjusted in the following way. If a pitcher was 1 SD below the mean in HRs per IP in a given year, his adjusted HRs per IP became .0456 (.0809 - .0353). This was done for BBs and Ks as well.

6. Each pitcher's adjusted HRs, BBs, and Ks per 9 IP were plugged into the formula

FIP ERA = 2.667 + 1.44*HR + .33*BB - .22*K.

Here are the 25 lowest FIP ERAs from 1920-2005:

I also looked at the win value of each performance. A low ERA is good, but if it is over a low number of innings it will not help your team win many games.

To find the win value for each pitcher in each year, I used the formula which says it takes 10 times the square root of the number of runs scored per inning by both teams (found in Total Baseball, 5e). If each team scores .5 runs per inning, the total is one. The square root is 1 and 10 times that is 10, so it would take 10 additional runs over the course of a season to win one more game. Since the average ERA here was 3.696, it means that both teams scored 7.392 per 9 innings. Per inning that works out to .8213. The square root of that is .90627. 10 times that is 9.0627.

I then found how many runs each pitcher saved compared to the average. First, a pitcher's ERA was subtracted from 3.696. If a pitcher had a 2.696 ERA, then he saved 1 run per 9 IP. That would get multiplied by the pitcher's IP/9 (the equivalent number of complete games). If he pitched 225 innings, he had 25 complete game equivalents. That 25 gets multiplied by the 1 run he saves per 9 IP to get 25 runs saved. That 25 gets divided by 9.0627 to get 2.76 wins above average. Below are the top 25 seasons in wins above average.

Sources: Park factors for HRs came from SABR member Ron Selter (except for 2005 when they came from the Bill James annual Handbook)

The Sean Lahman database.

http://www.hardballtimes.com/main/statpages/glossary/

http://www.hardballtimes.com/main/printarticle/giving-up-the-long-ball/

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