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Inside Baseball: The Automated Ball-Strike System as an O...
[Submitted on 15 May 2026 (v1), last revised 23 Jun 2026 (this v · 2026-06-25 · via cs.HC updates on arXiv.org

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Abstract:Clearly-defined rules are often assumed to be straightforward to automate and evaluate. We challenge this assumption through an in-depth study of Major League Baseball's (MLB) seven-year experimentation with the Automated Ball-Strike System (ABS). ABS is envisioned to call balls and strikes accurately: a seemingly straightforward use of technology to objectively determine the distance between a pitch and the strike zone. Although the strike zone is an area clearly defined in the rulebook, it took MLB seven years to figure out how to automate calling balls and strikes with ABS, showing how even seemingly straightforward rules require a complex translation process to operationalize via technological systems. In this paper, we trace the design decisions that led to the current implementation of ABS. Our case study reveals that "distance" exists even between a clear rule and its technological implementation. Using analytic frameworks from Science and Technology Studies (STS), we show that such distance exists because (1) historically, the "ground truth" of the strike zone is contested: the rule in practice has always reflected a hybrid between the rulebook definition and umpires' enforcement decisions; and (2) the use of ABS is embedded in an existing eco-system, where the implementation of a technological enforcement system needs to balance multiple stakeholder values. This perspective challenges conventional evaluation paradigms that center on the distance between a formalized rule and its technological implementation, and instead calls for evaluating how such systems are experienced in practice. Addressing this question requires in-depth social science approaches, contributing to ongoing conversations in FAccT about the implementation and evaluation of sociotechnical systems.

Submission history

From: Andrea Wen-Yi Wang [view email]
[v1] Fri, 15 May 2026 17:45:04 UTC (2,069 KB)
[v2] Wed, 27 May 2026 04:47:58 UTC (2,069 KB)
[v3] Tue, 23 Jun 2026 21:26:43 UTC (2,069 KB)