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April 27, 2012 3:00 am
If you want to estimate run-scoring accurately, what are all the factors you need to take into account?
The forces that influence run-scoring
As a reader of this site, you would be suspicious of any article that compared a starter’s ERA and a reliever’s ERA without making any adjustment for role: it has been shown several times (including by yours truly) that the luxury of pitching in short bursts and not having to face the same batters multiple times in a single outing significantly deflates relievers’ ERAs.
Similarly, we can’t model run-scoring on a team level without accounting for all the factors at play at any particular time. Many elements combine to shape the distribution of runs scored. Some of them are quite obvious, while others remain hidden until they’re exposed by the most brilliant analysts. In the following paragraphs, I’ll try to evaluate as many of those components as possible in an attempt to isolate their individual effects on offensive outcomes.
Using a database of 30,000 starts from 1994 to 2000, BP corrspondent Ted Kury introduces a new model to estimate pitch counts per start from historical and minor league games.
Using data commonly available in newspaper box scores, e.g., innings pitched, hits, runs allowed, earned runs allowed, walks, and strikeouts, we can derive estimated pitch counts. In addition, we will look at how the designated hitter impacts pitch counts.
The Raw Data
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