Out of gas: quantifying fatigue in MLB relievers
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Kyle Burris
and
Jacob Coleman
Abstract
As relief pitcher usage in Major League Baseball has spiked in recent years, optimal bullpen decision-making has become increasingly vital for team managers. Throughout the season, managers must be mindful to avoid overusing their most talented relievers, due to the risks of injury and ineffectiveness. Despite the substantial amount of attention given to pitcher arm health and injury prevention, the effect of workload on pitcher fatigue is poorly understood. As a result, many of these overuse decisions are driven by feel and intuition. In this paper, we borrow ideas from toxicology to provide a framework for estimating the effect of recent workload on short-term reliever effectiveness, as measured by fastball velocity. Treating a thrown pitch as a fatigue-inducing “toxin” administered to a player’s arm, we develop a Bayesian hierarchical model to estimate the pitcher-level dose-response relationship, the rate of recovery, and the relationship between pitch count and fatigue. Based on the model, we find that the rate of reliever fatigue rises with increasing pitch count. When relief pitchers throw more than 15 pitches in an appearance, they are expected to suffer small, short-term velocity decreases in future games; upon crossing the 20 pitch threshold, this dip is further amplified. For each day that passes after the appearance, we estimate that the effect on a player’s velocity is cut roughly in half. Finally, we identify the relievers most affected by fatigue, along with those most resilient to its effects.
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©2018 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Estimating the effect of plate discipline using a causal inference framework: an application of the G-computation algorithm
- Out of gas: quantifying fatigue in MLB relievers
- On the dependency of soccer scores – a sparse bivariate Poisson model for the UEFA European football championship 2016
- Modeling between-subject differences and within-subject changes for long distance runners by age
Articles in the same Issue
- Frontmatter
- Estimating the effect of plate discipline using a causal inference framework: an application of the G-computation algorithm
- Out of gas: quantifying fatigue in MLB relievers
- On the dependency of soccer scores – a sparse bivariate Poisson model for the UEFA European football championship 2016
- Modeling between-subject differences and within-subject changes for long distance runners by age
