Murray Nick B, Black Georgia M, Whiteley Rod J, Gahan Peter, Cole Michael H, Utting Andy, Gabbett Tim J
Int J Sports Physiol Perform. 2017 Apr;12(4):533-537. doi: 10.1123/ijspp.2016-0212. Epub 2016 Sep 6.
Throwing loads are known to be closely related to injury risk. However, for logistic reasons, typically only pitchers have their throws counted, and then only during innings. Accordingly, all other throws made are not counted, so estimates of throws made by players may be inaccurately recorded and underreported. A potential solution to this is the use of wearable microtechnology to automatically detect, quantify, and report pitch counts in baseball. This study investigated the accuracy of detection of baseball pitching and throwing in both practice and competition using a commercially available wearable microtechnology unit.
Seventeen elite youth baseball players (mean ± SD age 16.5 ± 0.8 y, height 184.1 ± 5.5 cm, mass 78.3 ± 7.7 kg) participated in this study. Participants performed pitching, fielding, and throwing during practice and competition while wearing a microtechnology unit. Sensitivity and specificity of a pitching and throwing algorithm were determined by comparing automatic measures (ie, microtechnology unit) with direct measures (ie, manually recorded pitching counts).
The pitching and throwing algorithm was sensitive during both practice (100%) and competition (100%). Specificity was poorer during both practice (79.8%) and competition (74.4%).
These findings demonstrate that the microtechnology unit is sensitive to detect pitching and throwing events, but further development of the pitching algorithm is required to accurately and consistently quantify throwing loads using microtechnology.
已知投掷负荷与受伤风险密切相关。然而,出于后勤方面的原因,通常只有投手的投球会被计数,而且只在局数中计数。因此,其他所有的投掷都不被计数,所以球员投掷次数的估计可能记录不准确且报告不足。对此的一个潜在解决方案是使用可穿戴微技术来自动检测、量化和报告棒球比赛中的投球次数。本研究使用市售的可穿戴微技术设备,调查了在练习和比赛中检测棒球投球和投掷的准确性。
17名精英青少年棒球运动员(平均年龄±标准差16.5±0.8岁,身高184.1±5.5厘米,体重78.3±7.7千克)参与了本研究。参与者在练习和比赛中佩戴微技术设备进行投球、防守和投掷。通过将自动测量值(即微技术设备)与直接测量值(即人工记录的投球次数)进行比较,确定投球和投掷算法的敏感性和特异性。
投球和投掷算法在练习(100%)和比赛(100%)中均具有敏感性。特异性在练习(79.8%)和比赛(74.4%)中均较差。
这些发现表明,微技术设备对检测投球和投掷事件很敏感,但需要进一步开发投球算法,以便使用微技术准确且一致地量化投掷负荷。