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Articles

Opportunistic shirking behaviour during unpaid overtime

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Pages 608-612 | Published online: 27 Jun 2018
 

ABSTRACT

We identify the presence of shirking by Major League Baseball umpires during indefinite unpaid overtime, as defined by extra innings. In the presence of new information about expected game length, umpires exert biases in ball and strike calls consistent with opportunistically reducing the likelihood of working additional time. General implications with respect to the effectiveness of salaried workers during unpaid overtime hours are discussed.

JEL CLASSIFICATION:

Acknowledgment

The authors thank Charlie Brown, Scott Tainsky, and Steve Salaga for their helpful comments on earlier versions of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Once the home team has secured a lead in extra innings, the game ends.

2 We use the ‘baseballr’ package in the R statistical software to scrape the data.

3 Relative to fully parametric approaches such as logistic regression, GAMs require fewer assumptions regarding the link between pitch location and strike likelihood. Specifically, GAMs do not require the true association between pitch location and strike likelihood to be known, instead considering various linear and nonlinear possibilities.

4 Our entire analysis plan, which includes R code for scraping and analysing the data, can be found at https://github.com/statsbylopez/mlb-shirking.

5 The base rate of strike calls in these regions is between approximately 40% and 60%. The effect magnitudes are substantially larger in scale than various biases found by Mills (Citation2014).

6 These comparisons are provided in the online repository at https://github.com/statsbylopez/mlb-shirking.

7 We note that, while not presented here, our full analysis included a comparison of pitcher quality across conditions, finding nearly identical results.

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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