棒球领域数据与分析研究的现状
Current State of Data and Analytics Research in Baseball.
作者信息
Mizels Joshua, Erickson Brandon, Chalmers Peter
机构信息
Department of Orthopaedic Surgery, University of Utah, 590 Wakara Way, Salt Lake City, UT, 84108, USA.
Rothman Orthopaedic Institute, New York, NY, USA.
出版信息
Curr Rev Musculoskelet Med. 2022 Aug;15(4):283-290. doi: 10.1007/s12178-022-09763-6. Epub 2022 Apr 29.
PURPOSE OF REVIEW
Baseball has become one of the largest data-driven sports. In this review, we highlight the historical context of how big data and sabermetrics began to transform baseball, the current methods for data collection and analysis in baseball, and a look to the future including emerging technologies.
RECENT FINDINGS
Machine learning (ML), artificial intelligence (AI), and modern motion-analysis techniques have shown promise in predicting player performance and preventing injury. With the advent of the Health Injury Tracking System (HITS), numerous studies have been published which highlight the epidemiology and performance implications for specific injuries. Wearable technologies allow for the prospective collection of kinematic data to improve pitching mechanics and prevent injury. Data and analytics research has transcended baseball over time, and the future of this field remains bright.
综述目的
棒球已成为数据驱动程度最高的运动项目之一。在本综述中，我们重点介绍大数据和赛伯计量学如何开始改变棒球的历史背景、当前棒球数据收集与分析的方法，以及对包括新兴技术在内的未来展望。
最新发现
机器学习（ML）、人工智能（AI）和现代运动分析技术在预测球员表现和预防伤病方面已展现出前景。随着健康伤病跟踪系统（HITS）的出现，已发表了大量研究，突出了特定伤病的流行病学及对表现的影响。可穿戴技术能够前瞻性地收集运动学数据，以改善投球技术并预防伤病。随着时间推移，数据与分析研究已超越棒球领域，该领域的未来依然光明。
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