Haney Thomas A, Mercer John A
Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, NV, USA.
Int J Exerc Sci. 2011 Apr 15;4(2):133-140. doi: 10.70252/RHGB2099. eCollection 2011.
The purpose of this study was twofold: 1) to describe variability of pacing during a marathon and 2) to determine if there is a relationship between variability of pacing and marathon performance. Publically available personal global positioning system profiles from two marathons (Race 1 n = 116, Race 2 n = 169) were downloaded (http://connect.garmin.com) for analysis. The coefficient of variation of velocity (Velcov) was calculated for each profile. Each profile was categorized as finishing in under 3.9 hours, between 3.9 and 4.6 hours, or longer than 4.6 hours. Linear and quadratic lines of best fit were computed to describe the relationship between marathon finish time and Velcov. A 2 (Race) × 3 (bin) analysis of variance (ANOVA) was used to compare the dependent variable (Velcov) between races and the marathon bin finish times. Velcov was not influenced by the interaction of finish time bin and Race (p>0.05) and was not different between races (Race 1: 16.6 ± 6.4%, Race 2: 16.8 ± 6.6%, p>0.05). Velcov was different between finish time categories (p<0.05) for each race such that Velcov was lower for faster finish times. Using combined data from both races, linear (marathon finish time = marathon finish time = 0.09Velcov + 2.9, R^2 = 0.46) and quadratic (marathon finish time = -0.0006 Velcov 2 + 0.11 Velcov + 2.7, R^2 = 0.46) lines of best fit were significant (p<0.05). Slower marathon finishers had greater variability of pace compared to faster marathoner finishers.
1)描述马拉松比赛中的配速变化;2)确定配速变化与马拉松成绩之间是否存在关联。从两场马拉松比赛(比赛1,n = 116;比赛2,n = 169)公开的个人全球定位系统数据中下载(http://connect.garmin.com)进行分析。计算每个数据的速度变异系数(Velcov)。每个数据被分类为在3.9小时以内、3.9至4.6小时之间或超过4.6小时完赛。计算最佳拟合线性和二次曲线以描述马拉松完赛时间与Velcov之间的关系。采用2(比赛)×3(分组)方差分析(ANOVA)来比较不同比赛和马拉松分组完赛时间之间的因变量(Velcov)。Velcov不受完赛时间分组与比赛的交互作用影响(p>0.05),且不同比赛之间无差异(比赛一:16.6±6.4%,比赛二:16.8±6.6%,p>0.05)。每场比赛的完赛时间类别之间Velcov存在差异(p<0.05),即完赛时间越快,Velcov越低。使用两场比赛的合并数据,最佳拟合线性(马拉松完赛时间=0.09Velcov + 2.9,R^2 = 0.46)和二次曲线(马拉松完赛时间=-0.0006Velcov² + 0.11Velcov + 2.7,R^2 = 0.46)均具有显著性(p<0.05)。与完赛较快的马拉松选手相比,完赛较慢的马拉松选手配速变化更大。