首页> 外文期刊>Orthopaedic Journal of Sports Medicine >Are Baseball Statistics an Appropriate Tool for Assessing Return to Play in Injured Players: An Analysis of Statistically Variability in Healthy Players Using a Machine Learning Approach
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Are Baseball Statistics an Appropriate Tool for Assessing Return to Play in Injured Players: An Analysis of Statistically Variability in Healthy Players Using a Machine Learning Approach

机译:棒球统计数据是评估受伤球员重返比赛的合适工具吗:使用机器学习方法对健康球员的统计变异性进行分析

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Objectives: Traditional pitching statistics (ERA, WHIP, etc) have been used as surrogates for pitcher performance without being validated. Even amongst healthy pitchers, the normal variability of these parameters has not yet been established. The purpose of this study was to determine the normal variability of basic and advanced pitching statistics in non-injured Major League Baseball (MLB) pitchers. It is our hope that this work will serve as the foundation for the identification and implementation of validated, pitcher dependent statistical measures that can be used to assess return to play performance following injury. Methods: Publicly available data from MLB Statcast and Pitch/Fx databases was used to analyze all non-injured MLB pitchers during 2015 and 2016 seasons who pitcher greater than 100 innings each season without injury. Traditional and advanced baseball pitching statistics were analyzed. The variability of each parameter was assessed by computing coefficient of variation (CV) between individual pitchers and across all pitchers. A CV below 10 is typically indicative of a relatively constant parameter, and parameters with a CV & 10 are generally considered inconsistent and unreliable. Results: A total of 118 pitchers met all inclusion criteria. For each of these healthy pitchers, 38 basic/traditional parameters and 17 advanced parameters were analyzed. Of the traditional pitcher statistics, only 1 (3%) demonstrated a CV value & 10 (average fastball velocity [FBv]; CV 1.5) (Figure 1). In advanced statistics, 9 of 17 (53%) variables demonstrated acceptable consistency as evidenced by a CV value & 10 (Figure 2). Release position from plate (release_pos_y) along with velocity from the plate (vy0) where the two most constant advanced parameters. When separated by pitch type, these two parameters were the most constant (lowest CV) in every pitch type. Conclusion: The validity and variability of baseball statistics as surrogate markers for performance after injury/surgery have not yet been evaluated. It is critical that baseball statistics undergo proper vetting prior to being used to assess recovery. This study reveals average fastball velocity and release position from the plate to be the least variable basic and advanced baseball statistics in MLB pitchers. In total, only 10 of the 55 statistics analyzed demonstrated acceptable consistency and reliability. This study can be further used to determine the minimum time that each of these variables needs to be followed to ensure an appropriate sample size is obtained to detect significant differences in pre- and post- injury performance. Figure 1. Variability for each traditional MLB pitcher statistic sorted in ascending order. Lower values indicate less variation. Figure 2. Variability for each advanced MLB pitcher statistic. Lower values indicate less variation.
机译:目标:传统的投球统计数据(ERA,WHIP等)已被用作未经证实的投手表现的替代物。即使在健康的投手中,这些参数的正常变异性尚未确定。这项研究的目的是确定未受伤的美国职棒大联盟(MLB)投手的基本和高级投球统计数据的正常变异性。我们希望这项工作将为识别和实施经过验证的,依赖投手的统计方法奠定基础,这些统计方法可用于评估受伤后的比赛表现。方法:使用来自MLB Statcast和Pitch / Fx数据库的公开数据分析2015年和2016赛季所有未受伤的MLB投手,每个赛季投手超过100局而没有受伤。分析了传统和高级棒球投球统计数据。通过计算各个投手之间以及所有投手之间的变异系数(CV)来评估每个参数的变异性。低于10的CV通常表示相对恒定的参数,并且CV>通常认为10个不一致且不可靠。结果:总共118个投手符合所有纳入标准。对于这些健康投手中的每一个,分析了38个基本/传统参数和17个高级参数。在传统的投手统计数据中,只有1(3%)的CV值<0。 10(快球平均速度[FBv]; CV 1.5)(图1)。在高级统计数据中,17个变量中的9个(53%)表现出可接受的一致性,如CV值<1所证明。 10(图2)。从板(release_pos_y)释放的位置以及从板(vy0)的速度,这是两个最恒定的高级参数。当按音高类型分开时,这两个参数是每种音高类型中最恒定的(最低CV)。结论:棒球统计数据作为损伤/手术后表现的替代指标的有效性和变异性尚未得到评估。棒球统计数据在用于评估恢复之前必须经过适当的审查,这一点至关重要。这项研究表明,MLB投手的平均快球速度和从板中释放的位置是基础和进阶棒球统计数据中变化最小的。总共分析的55个统计数据中,只有10个显示出可接受的一致性和可靠性。该研究可进一步用于确定需要遵循这些变量中的每一个的最短时间,以确保获得适当的样本量,以检测损伤前后表现的显着差异。图1.按升序排序的每个传统MLB投手统计数据的可变性。较低的值表示变化较小。图2.每个高级MLB投手统计的可变性。较低的值表示较少的变化。

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