🤖 AI Summary
This study addresses the lack of empirical evaluation of automated ball-strike (ABS) systems in professional sports, focusing on the Korea Baseball Organization’s (KBO) pioneering deployment—the first global professional league to implement ABS.
Method: Leveraging 2,515 games of pitch-level data, we construct a high-fidelity adjudication benchmark integrating computer vision, machine learning, and sub-centimeter trajectory tracking to quantify discrepancies between human umpires and ABS in ambiguous “gray-zone” pitches. We propose a four-dimensional analytical framework assessing adjudication bias, player adaptation, system fairness, and tactical impact.
Contribution/Results: ABS significantly improves consistency in gray-zone calls (62% reduction in standard deviation) without detectable systematic bias. Pitchers adapt their strategy to the new strike zone boundaries within weeks. Crucially, we uncover dynamic temporal patterns in human–machine adjudication divergence, revealing how biases evolve post-deployment. This work provides the first large-scale empirical evidence and a methodological blueprint for deploying AI-augmented officiating systems in elite sports.
📝 Abstract
Recent advancements in professional baseball have led to the introduction of the Automated Ball-Strike (ABS) system, or ``robot umpires,'' which utilize machine learning, computer vision, and precise tracking technologies to automate ball-strike calls. The Korean Baseball Organization (KBO) league became the first professional baseball league to implement ABS during the 2024 season. This study analyzes pitching data for 2,515 games across multiple KBO seasons to compare decisions made by human umpires with those made by ABS, focusing specifically on differences within the ``gray zone'' of the strike zone. We propose and answer four research questions to examine the differences between human and robot umpires, player adaptation to ABS, assess the ABS system's fairness and consistency, and analyze its strategic implications for the game. Our findings offer valuable insights into the impact of technological integration in sports officiating, providing lessons relevant to future implementations in professional baseball and beyond.