Comparison of Sprint and Run Times with Performance on the Wingate Anaerobic Test

Tharp, G. D., Newhouse, R. K., Uffelman, L., Thorland, W. G., & Johnson, G. O. (1985). Comparison of Sprint and Run Times with Performance on the Wingate Anaerobic Test. Research Quarterly for Exercise and Sport, 56(1), 73–76. https://doi.org/10.1080/02701367.1985.10608434In recent years the classic Margaria step-test for anaerobic power has been largely replaced by bicycle ergometer tests, the most popular of these being the Wingate Anaerobic Test (WAnT). The purpose of this study was to examine the relationship between the WAnT and sprint-run times and to determine the influence of age and weight on the WAnT scores. The 56 male volunteers (age 10–15 years) recruited from a track club and junior high school represented a wide range of athletic abilities. Subjects were tested for anaerobic power (5 sec output) and capacity (30 sec output) using the Wingate test procedures. Wingate scores for anaerobic power and capacity were only moderately correlated with 50 yd dash times (r = −.53 and −.53) and with the 600 yd run (r = −.26 and −.29). Partial correlations between these variables were lower when age adjusted and higher when adjusted for body weight. Results of this study indicate that the Wingate anaerobic test is only a moderate predictor of dash or run times, but becomes a stronger predictor when WAnT scores are adjusted for body weight.Tharp, G. D.、Newhouse, R. K.、Uffelman, L.、Thorland, W. G. 与 Johnson, G. O.（1985）。《短跑与长跑时长与温盖特无氧测试（Wingate Anaerobic Test, WAnT）表现的比较》。《运动与锻炼研究季刊》，56(1)，73–76页。https://doi.org/10.1080/02701367.1985.10608434 近年来，用于评估无氧功率的经典Margaria台阶测试，已被自行车功率计测试广泛替代，其中最广为应用的便是温盖特无氧测试。本研究旨在探讨温盖特无氧测试与短跑、长跑时长之间的关联，并明确年龄与体重对温盖特无氧测试得分的影响。 研究从田径俱乐部与初中招募了56名男性志愿者，年龄介于10至15岁之间，其运动能力分布范围较广。受试者采用温盖特测试流程，分别测定其无氧功率（5秒输出功率）与无氧能力（30秒输出功率）。 温盖特测试所得的无氧功率与能力得分，与50码冲刺时长仅呈中等程度相关（相关系数r分别为-0.53与-0.53），与600码长跑时长的相关系数则为-0.26与-0.29。当控制年龄变量进行偏相关分析时，上述变量间的偏相关系数有所降低；而当控制体重变量进行偏相关分析时，偏相关系数则有所升高。 本研究结果表明，温盖特无氧测试仅能中等程度预测冲刺或长跑时长，但在对测试得分进行体重校正后，其预测效能会得到显著提升。