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Park Factors and ERA Estimators: Part II

In my series’ first part, I looked at the effect that Park Factors have on various ERA estimators. The original question I attempted to answer was whether certain estimators were better suited for predicting performance, depending on whether a park is hitter-friendly or pitcher-friendly. The short answer was that ERA estimators did a much better job in hitter-friendly parks than pitcher-friendly parks, relative to YR1_ERA.

One question I didn’t answer was whether the effectiveness of estimators in various types of parks also varied by pitcher role (i.e. starters versus relievers). Generally speaking, ERA estimators perform better when you restrict the analysis to starters only — since relievers tend to be more volatile year-over-year. The question is whether this same pattern will hold given park factors’ impact. And as predicted, ERA estimators do a better job predicting performance for starters versus relievers.

The current data set includes 533 pairs of starter seasons and reliever seasons where the pitchers threw in the same parks in the first and second years, and did so as starters or relievers both years. Before segmenting by park type, we see results that are consistent with previous analysis regarding ERA estimators and their predictive powers for starters and relievers:

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Park Factors and ERA Estimators: Part I

(Note: I noticed a coding issue in the data, which resulted in three parks having a different classification. The data has been re-run to reflect the new results and the article updated to reflect the findings.)

Researchers have gone to great pains to highlight and account for factors outside of an individual player’s control when evaluating their performance and value. The standard for this is of course Voros McCracken’s seminal research into defense independent pitching and Tom Tango’s fielding independent pitching (FIP). While baseball is arguably the most “individualistic” of the major team sports, players do not perform in isolation from each other or from their environment.

Lately I’ve become more interested in how the physical environment of a team and its players affects their outcomes on the field. My initial research led me to look at whether a team’s home park and the degree to which it inflated or suppressed run scoring put the team at a fundamental advantage or disadvantage in terms of winning. The results suggested that hitter-friendly parks do, in fact, put a team at a fundamental disadvantage, likely due to the stress that playing 81 games a year in that environment places on the pitching staff.

In this article, I am concerned with how park factors may affect the various constructs we’ve developed to help us better evaluate a player’s talent and likely performance in the future. Specifically, to what extent to do park factors affect the usefulness of various ERA estimators? It seems reasonable to assume that while much of what happens when a ball is put in play is not controlled by a pitcher. However, given that some extreme parks are likely to exercise their own environmental force over the outcome of batted balls it stands to reason that ERA estimators that factor in a pitcher’s batted ball profile may do a better job in certain types of parks than others.

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