Scheer Volker, Janssen Tanja I, Vieluf Solveig, Heitkamp Hans-Christian
Int J Sports Physiol Perform. 2019 Jan 1;14(1):130-133. doi: 10.1123/ijspp.2018-0390.
Trail running is a complex sport, and performance prediction is challenging. The aim was to evaluate 3 standard laboratory exercise tests in trail runners and correlate measurements to the race time of a trail competition evaluating its predictive power.
Nine competitive male trail runners (mean age: 31 [5.8] y) completed 3 different laboratory exercise tests (step, ramp, and trail tests) for determination of maximal oxygen uptake (VO2max), vVO2max, ventilatory (VT) and lactate thresholds (LT), mechanical power output, and running economy (RE), followed by a 31-km trail race. Runners had previously participated in the same race (previous year) and finished in the top 2%. Finishing times (dependent value) were tested in multiple-regression analysis with different independent value combinations.
Linear-regression analysis revealed that variables measured during step and ramp tests significantly predicted performance. Step-test variables (speed at individual anaerobic threshold 16.4 [1.7] km/h and RE 12 km/h in %VO2max 65.6% [5.4%]) showed the highest performance prediction (R2 = .651, F2,6 = 5.60, P = .043), followed by the ramp test (vVO2max 20.3 [1.3] km/h; R2 = .477, F1,7 = 6.39, P = .04) and trail test (maximal power 3.9 [0.5] W/kg, VO2max 63.0 [4.8] mL O2·kg-1·min-1, vVT1 11.9 [0.7] km/h; R2 = .68, F3,5 = 3.52, P = .11). Adding race time from the preceding year to the step test improved the predictive power of the model (R2 = .988, F3,5 = 66.51, P < .001).
The graded exercise test (VO2max, individual anaerobic threshold, and RE) most accurately predicted a 31.1-km trail-running performance. Combining submaximal intensities (individual anaerobic threshold and RE) with the previous year's race time of that specific event increased the predictive power of the model to 99%.
越野跑是一项复杂的运动，成绩预测具有挑战性。本研究旨在评估越野跑者的3项标准实验室运动测试，并将测量结果与一场越野比赛的完赛时间相关联，以评估其预测能力。
9名有竞争力的男性越野跑者（平均年龄：31 [5.8]岁）完成了3项不同的实验室运动测试（台阶测试、斜坡测试和越野测试），以测定最大摄氧量（VO2max）、通气无氧阈速度（vVO2max）、通气阈值（VT）和乳酸阈值（LT）、机械功率输出和跑步经济性（RE），随后参加了一场31公里的越野赛。这些跑者此前曾参加过同一场比赛（上一年），且成绩排名前2%。完赛时间（因变量）在多元回归分析中与不同的自变量组合进行测试。
线性回归分析显示，台阶测试和斜坡测试期间测量的变量能显著预测成绩。台阶测试变量（个体无氧阈速度16.4 [1.7]公里/小时和12公里/小时速度下的RE为65.6% [5.4%]的VO2max）显示出最高的成绩预测能力（R2 = .651，F2,6 = 5.60，P = .043），其次是斜坡测试（vVO2max 20.3 [1.3]公里/小时；R2 = .477，F1,7 = 6.39，P = .04）和越野测试（最大功率3.9 [0.5]瓦/千克，VO2max 63.0 [4.8]毫升氧气·千克-1·分钟-1，vVT1 11.9 [0.7]公里/小时；R2 = .68，F3,5 = 3.52，P = .11）。将上一年的比赛时间加入台阶测试可提高模型的预测能力（R2 = .988，F3,5 = 66.51，P < .001）。
分级运动测试（VO2max、个体无氧阈和RE）最准确地预测了31.1公里越野跑成绩。将次最大强度（个体无氧阈和RE）与该特定赛事上一年的比赛时间相结合，可将模型的预测能力提高到99%。
