J Sports Sci Med. 2010 Sep 1;9(3):439-44. eCollection 2010.
The purpose of the present study was to analyze longitudinal changes in 3,000 m running performance and the relationship with selected physiological parameters. Eighteen well-trained male middle-distance runners were measured six times (x3 per year) throughout two consecutive competitive seasons. The following parameters were measured on each occasion: maximal oxygen uptake (VO2max), running economy (RE), velocity at maximal oxygen uptake (vVO2max), velocity at 4mmol L(-1) blood lactate concentration (V4), and performance velocity (km·h(-1)) in 3,000 m time trials. Values ranged from 19.59 to 20.16 km·h(-1), running performance; 197 to 207 mL·kg(-1)·km(-1). RE; 17.2 to 17.7 km·h(-1), V4; 67.1 to 72.5 mL·kg(-1)·min(-1), VO2max; and 19.8 to 20.2 km·h(-1), vVO2max. A hierarchical linear model was used to quantify longitudinal relationships between running performance and selected physiological variables. Running performance decreased significantly over time, between each time point the decrease in running velocity was 0.06 km·h(-1). The variables that significantly explained performance changes were V4 and vVO2max. Also, vVO2max and V4 were the measures most strongly correlated with performance and can be used to predict 3,000 m race velocity. The best prediction formula for 3,000 m running performance was: y = 0.646 + 0.626x + 0.416z (R(2)=0.85); where y = V3,000 m velocity (km·h(-1)), x = V4 (km·h(-1)) and z = vVO2max (km·h(-1)). The high predictive power of vVO2max and V4 suggest that both coaches and athletes should give attention to improving these two physiological variables, in order to improve running performance. Key pointsV4 and vVO2max are the most important physiological variables to explain longitudinal changes in 3000 m running performance;3000 m running performance prediction is better if one uses both V4 and vVO2max in the same formula: y = 0.646 + 0.626x + 0.416z; R(2)=0.85, where y is the Vrace (km/h), x is V4 (km/h) and z is vVO2max (km/h).The V4 and vVO2max can be used for training control purposes.
本研究的目的是分析 3000 米跑成绩的纵向变化及其与选定生理参数的关系。18 名训练有素的男性中长跑运动员在两个连续的竞技赛季中每 3 次(每年 x3 次)进行了 6 次测量。每次都测量以下参数:最大摄氧量(VO2max)、运动经济性(RE)、最大摄氧量时的速度(vVO2max)、4mmol L(-1)血乳酸浓度时的速度(V4)和 3000 米计时赛的成绩速度(km·h(-1))。值范围为 19.59 至 20.16km·h(-1),跑步成绩;197 至 207mL·kg(-1)·km(-1),RE;17.2 至 17.7km·h(-1),V4;67.1 至 72.5mL·kg(-1)·min(-1),VO2max;和 19.8 至 20.2km·h(-1),vVO2max。使用层次线性模型来量化跑步成绩与选定生理变量之间的纵向关系。跑步成绩随着时间的推移显着下降,每个时间点的跑步速度下降 0.06km·h(-1)。显着解释成绩变化的变量是 V4 和 vVO2max。此外,vVO2max 和 V4 是与成绩最密切相关的指标,可用于预测 3000 米比赛速度。3000 米跑步成绩的最佳预测公式为:y = 0.646 + 0.626x + 0.416z(R(2)=0.85);其中 y = V3000 m 速度(km·h(-1)),x = V4(km·h(-1)),z = vVO2max(km·h(-1))。vVO2max 和 V4 的高预测能力表明,教练和运动员都应该注意提高这两个生理变量,以提高跑步成绩。关键点V4 和 vVO2max 是解释 3000 米跑成绩纵向变化的最重要生理变量;如果在同一公式中同时使用 V4 和 vVO2max,则可以更好地预测 3000 米跑步成绩:y = 0.646 + 0.626x + 0.416z;R(2)=0.85,其中 y 是 Vrace(km/h),x 是 V4(km/h),z 是 vVO2max(km/h)。V4 和 vVO2max 可用于训练控制目的。