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05-16-2019
11:54 AM

Monica Abbott led all pitchers of the the National Pro Fastpitch (NPF) league with 17 wins during the 2017 season. Since Abbott's team -- the Scrap Yard Dawgs -- only won 31 games that year, Abbott was apparently worth 55% of her team's wins.

Of course, that can't be right. Although people in softball (and baseball) routinely assign team wins to individual pitchers, it is incorrect to think a pitcher is the sole reason why a team wins (or loses). So that leaves us with a question.

How many wins do pitchers in softball really produce? Similar to what has been done for hitters in softball, this question can be answered by looking at the box score statistics.

The process for pitchers begins with the concept of Fielding Independent Pitching Earned Run Average (FIP ERA). As detailed in Sports Economics, Earned Run Average (ERA) is not the best measure of a pitcher's performance. Because earned runs depend on the fielders around the pitcher, a pitcher's ERA is not simply about the pitcher's performance. The better (or worse) the fielders around the pitcher perform the better (or worse) will be a pitcher's ERA.

The problem with ERA was originally noted by Voros McCracken. And McCracken also devised a better approach. This approach -- as detailed in Chapter Eight of Sports Economics -- was adapted to data from the NPF. The specific model involves regressing a pitcher's ERA on defensive independent statistics -- specifically strike outs, walks, hit-by-pitch, and home runs -- and one defensive dependent measure. This last measure was Hits per Ball in Play (HperBIP), which is calculated as follows:

HperBIP = [Hits – Home Runs]/[Outs + Hits – Strike Outs – Home Runs]

The data employed to estimate this model included every pitcher in the NPF from 2004 to 2018 who had at least 50 innings pitched in a single season. In all, there were 221 pitcher observations. The results -- reported in the table below -- indicate that 89% of the variation in pitcher's ERA is explained by these factors.

To construct the FIP ERA, we simply multiply each pitcher's defensive independent statistic by the corresponding coefficient. We then use the average value for HperBIP in the aforementioned player sample to construct each player's FIP ERA.

The following example for Monica Abbot's 2017 season illustrates the process. In column (2) we have the value of each statistics for Monica Abbott in 2017 and in the third column are the coefficients from the aforementioned model. Multiplying these two columns -- and then summing these values -- gives us Abbott's FIP ERA. As one can see, Abbott's FIP ERA was 1.47; or a bit worse than her actual ERA of 1.17.

Of course, the objective is to measure Abbott's production of wins. To do this we follow the following steps:

- For each pitcher we determine the number of earned runs the pitcher surrendered that can be attributed to each pitcher's FIP stats (i.e. strike outs, walks, hit-by-pitch, and home runs). For Abbott in 2017, her FIP stats for the season were worth -3.95 runs for the season.
- Abbott pitched 144 innings in 2017. The next step is to determine how many runs an average pitcher would have surrendered with her FIP stats in that many innings. From 2004 to 2018, NPF pitchers recorded 24,908.67 innings pitched and surrendered in these innings 3,998.4 FIP earned runs. This means that per inning, an average pitcher surrendered 0.16 runs. So, in 144 innings an average pitcher's FIP stats would have led to 23.1 earned runs. In other words, Abbott surrendered 27.1 fewer runs than an average NFP pitcher.
- A regression of team winning percentage on runs scored per game and runs surrendered per game indicates that each additional run scored is worth 0.085 additional wins in the NPF. This means that Abbott produced 2.30 wins more than an average NFP pitcher (i.e. 0.085*27.1).
- From 2004 to 2018, NPF teams won 1950 games. Let's assume hitters produce half a team's wins and pitching and defense produce the remaining half. So, pitchers and the defensive players are credited with 975 wins. To split the credit for pitchers and the defenders around the pitchers we will look at total runs surrendered and FIP earned runs. From 2004 to 2018, teams surrendered 12,038 total runs. But again, the FIP earned runs were only 3,998.41. Therefore, pitchers were only responsible for 33% of the runs allowed by NPF teams. And therefore, we can argue that pitchers are only responsible for 33% of the wins attributed to the pitchers and defense. That means, pitchers are credited with 323.8 wins. Given the number of innings pitched, this means an average pitcher produced 0.013 wins per inning.
- Again, Abbott pitched 144 innings. If she was average, she would have produced 1.87 wins. Given that she produced 2.30 wins above average, we can now see that all these calculations indicate Abbott was worth 4.17 wins in 2017.

Each of those steps were applied to all pitchers in the NPF from 2004 to 2018. What follows are the top 20 pitchers -- in Wins Produced -- from 2004 to 2018.

As one can see, Monica Abbott's 2017 performance ranks 3rd all-time in NPF history. She is also listed five more times in the list of top 20 pitchers. She never did quite as well as Christa Williams in 2005 and Amanda Scott in 2004. But Wins Produced suggests Abbott is likely the greatest pitcher in NPF history.

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About the Author

David Berri is the lead author of two books—The Wages of Wins (with Martin Schmidt and Stacy Brook; Stanford University Press) and Stumbling on Wins (with Martin Schmidt; Financial Times Press)—written for a general audience on the subject of sports and economics. In addition, he has had more than 40 papers accepted and/or published in refereed journals in the field and at least a dozen additional papers published in academic collections. Beyond this academic work, Berri has written more than 100 articles for the popular press, including The New York Times, Time.com, Atlantic.com, Vice Sports, and the Huffington Post. Berri has also served as president of the North American Association of Sports Economics (NAASE) and currently sits on the editorial board of the Journal of Sports Economics and International Journal of Sport Finance (the two journals in sports economics). Beginning in 2004, he has helped organize meetings of NAASE at the Western Economic Association, which is the world’s largest gathering of sports economists annually. Berri has taught sports economics since 1999, starting at Coe College and then moving on to California State University-Bakersfield. He has taught at Southern Utah University since 2008.

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