Ahrend Marc-Daniel, Schneeweiss Patrick, Martus Peter, Niess Andreas M, Krauss Inga
Department of Sports Medicine, Medical Clinic, University of Tuebingen, Tuebingen, Germany.
Institute for Clinical Epidemiology and Applied Biometry, University Hospital Tuebingen, Tuebingen, Germany.
BMJ Open Sport Exerc Med. 2018 Jan 26;4(1):e000293. doi: 10.1136/bmjsem-2017-000293. eCollection 2018.
Traditional performance tests in mountain bike marathon (XCM) primarily quantify aerobic metabolism and may not describe the relevant capacities in XCM. We aimed to validate a comprehensive test protocol quantifying its intermittent demands.
Forty-nine athletes (38.8±9.1 years; 38 male; 11 female) performed a laboratory performance test, including an incremental test, to determine individual anaerobic threshold (IAT), peak power output (PPO) and three maximal efforts (10 s all-out sprint, 1 min maximal effort and 5 min maximal effort). Within 2 weeks, the athletes participated in one of three XCM races (n=15, n=9 and n=25). Correlations between test variables and race times were calculated separately. In addition, multiple regression models of the predictive value of laboratory outcomes were calculated for race 3 and across all races (z-transformed data).
All variables were correlated with race times 1, 2 and 3: 10 s all-out sprint (r=-0.72; r=-0.59; r=-0.61), 1 min maximal effort (r=-0.85; r=-0.84; r=-0.82), 5 min maximal effort (r=-0.57; r=-0.85; r=-0.76), PPO (r=-0.77; r=-0.73; r=-0.76) and IAT (r=-0.71; r=-0.67; r=-0.68). The best-fitting multiple regression models for race 3 (r=0.868) and across all races (r=0.757) comprised 1 min maximal effort, IAT and body weight.
Aerobic and intermittent variables correlated least strongly with race times. Their use in a multiple regression model confirmed additional explanatory power to predict XCM performance. These findings underline the usefulness of the comprehensive incremental test to predict performance in that sport more precisely.
山地自行车马拉松(XCM)传统的体能测试主要用于量化有氧代谢,可能无法描述XCM中的相关能力。我们旨在验证一种全面的测试方案,以量化其间歇性需求。
49名运动员(38.8±9.1岁;38名男性;11名女性)进行了一项实验室体能测试,包括递增测试,以确定个体无氧阈(IAT)、最大功率输出(PPO)和三次全力冲刺(10秒全力冲刺、1分钟全力冲刺和5分钟全力冲刺)。在两周内,运动员参加了三项XCM比赛中的一项(n = 15、n = 9和n = 25)。分别计算测试变量与比赛时间之间的相关性。此外,针对比赛3和所有比赛(z转换数据)计算了实验室结果预测价值的多元回归模型。
所有变量均与比赛1、2和3的时间相关:10秒全力冲刺(r = -0.72;r = -0.59;r = -0.61)、1分钟全力冲刺(r = -0.85;r = -0.84;r = -0.82)、5分钟全力冲刺(r = -0.57;r = -0.85;r = -0.76)、PPO(r = -0.77;r = -0.73;r = -0.76)和IAT(r = -0.71;r = -0.67;r = -0.68)。比赛3(r = 0.868)和所有比赛(r = 0.757)的最佳拟合多元回归模型包括1分钟全力冲刺、IAT和体重。
有氧和间歇性变量与比赛时间的相关性最弱。它们在多元回归模型中的应用证实了其对预测XCM表现的额外解释力。这些发现强调了全面递增测试对更准确预测该运动表现的有用性。