Tracking Pitcher Performance with Instantaneous Component ERA and Moving Averages

John Salmon, Assistant Professor, Brigham Young University

Willie Harrison, Assistant Professor, University of Colorado, Colorado Springs

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Abstract: The earned-run average (ERA) is a common statistic used to evaluate performance on the mound. However, ERA can be decomposed further and is often not presented nor calculated dynamically over time. The Component ERA statistic, or CERA, enhances the traditional ERA by providing a more detailed metric to analyze pitching performance. By appropriately aggregating the results of each individual batter a pitcher faces throughout the season, an “Instantaneous” CERA value can also be calculated. When these values are plotted over time into a profile, the performance trends on an individual pitcher, and the comparison between pitchers, is readily available through various data visualizations. When moving averages (MA) are applied to the CERA profile, crossovers between MA’s over different “time frames” (i.e. numbers of batters faced) can be used as trigger points for the identification of potential trends, suggesting issues such as pitcher fatigue or discomfort. In general, these crossover points from a MA approach, similar to some investing strategies, can suggest when a pitcher is trending up or down providing additional evidence for making more informed pitching decisions. Furthermore, since pitchers have different characteristic CERA profiles and crossover points, the additional data could suggest different ways to properly manage pitchers. CERA statistic profiles could be added to the arsenal of tools available to a manager making decisions about pulling pitchers from a game or the overall team’s pitching rotation and schedule.​

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