King Benjamin W, Snow Teresa K, Millard-Stafford Mindy
Exercise Physiology Laboratory, School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia; and.
Emory University School of Medicine, Atlanta, Georgia.
J Strength Cond Res. 2025 Feb 1;39(2):217-226. doi: 10.1519/JSC.0000000000004966. Epub 2024 Oct 24.
King, BW, Snow, TK, and Millard-Stafford, M. Peak lower-extremity power unadjusted for body mass predicts fastball velocity in collegiate baseball pitchers. J Strength Cond Res 39(2): 217-226, 2025-The relationship between lower-extremity power production and fastball velocity in collegiate pitchers remains unclear. This study aimed to evaluate the relationship between lower-extremity power and throwing velocity in 33 National Collegiate Athletic Association Division I baseball pitchers. Lower-extremity power was quantified using countermovement jump (CMJ) testing on force plates and the Wingate anaerobic cycling test. In-game fastball velocities were collected using TrackMan technology. Pearson correlations and linear regressions were used to evaluate the association between lower-body power and fastball velocity. The strongest predictor of peak fastball velocity was body mass ( r = 0.58, p = 0.0004), followed by lean mass ( r = 0.52, p = 0.002). Peak power (W) produced on the Wingate and CMJ tests were each statistically significant predictors of peak velocity ( r = 0.44, p = 0.011; r = 0.43, p = 0.014, respectively), but CMJ power relative to body mass ( r = 0.19), jump height ( r = 0.07), and Sparta Scores ( r = -0.06) were not ( p > 0.05). Linear regression indicated Wingate and CMJ absolute peak power tests each independently explained 19% of the variance in fastball velocity but added little to the model when combined with body mass (∼34 vs. 32% of total variance). Because total body mass and lower-body power are important predictors of pitching velocity, absolute power output is a more relevant predictor of baseball pitching velocity than lower-body power variables influenced by body mass (e.g., jump height and Sparta Score).
金,BW,斯诺,TK,以及米勒德 - 斯塔福德,M。未经体重调整的下肢峰值功率可预测大学棒球投手的快球速度。《力量与体能研究杂志》39(2): 217 - 226,2025年 - 大学投手中下肢功率产生与快球速度之间的关系仍不明确。本研究旨在评估33名美国大学体育协会第一分区棒球投手中下肢功率与投球速度之间的关系。使用测力板上的反向移动跳跃(CMJ)测试和温盖特无氧自行车测试对下肢功率进行量化。使用TrackMan技术收集比赛中的快球速度。采用皮尔逊相关性和线性回归来评估下半身功率与快球速度之间的关联。快球峰值速度的最强预测因素是体重(r = 0.58,p = 0.0004),其次是瘦体重(r = 0.52,p = 0.002)。温盖特测试和CMJ测试产生的峰值功率(瓦特)均为峰值速度的统计学显著预测因素(分别为r = 0.44,p = 0.011;r = 0.43,p = 0.014),但相对于体重的CMJ功率(r = 0.19)、跳跃高度(r = 0.07)和斯巴达得分(r = -0.06)则不是(p > 0.05)。线性回归表明,温盖特测试和CMJ绝对峰值功率测试各自独立解释了快球速度方差的19%,但与体重结合时对模型的贡献不大(总方差的约34%对32%)。由于总体重和下半身功率是投球速度的重要预测因素,绝对功率输出比受体重影响的下半身功率变量(如跳跃高度和斯巴达得分)更能预测棒球投球速度。