Int J Sports Physiol Perform. 2018 Nov 1;13(10):1273-1280. doi: 10.1123/ijspp.2018-0026. Epub 2018 Nov 20.
To examine the ability of multivariate models to predict the heart-rate (HR) responses to some specific training drills from various global positioning system (GPS) variables and to examine the usefulness of the difference in predicted vs actual HR responses as an index of fitness or readiness to perform.
All data were collected during 1 season (2016-17) with players' soccer activity recorded using 5-Hz GPS and internal load monitored using HR. GPS and HR data were analyzed during typical small-sided games and a 4-min standardized submaximal run (12 km·h). A multiple stepwise regression analysis was used to identify which combinations of GPS variables showed the largest correlations with HR responses at the individual level (HR, 149 [46] GPS/HR pairs per player) and was further used to predict HR during individual drills (HR). Then, HR predicted was compared with actual HR to compute an index of fitness or readiness to perform (HR, %). The validity of HR was examined while comparing changes in HR with the changes in HR responses to a submaximal run (HR, fitness criterion) and as a function of the different phases of the season (with fitness being expected to increase after the preseason).
HR was very largely correlated with HR (r = .78 [.04]). Within-player changes in HR were largely correlated with within-player changes in HR (r = .66, .50-.82). HR very likely decreased from July (3.1% [2.0%]) to August (0.8% [2.2%]) and most likely decreased further in September (-1.5% [2.1%]).
HR is a valid variable to monitor elite soccer players' fitness and allows fitness monitoring on a daily basis during normal practice, decreasing the need for formal testing.
研究多元模型预测特定训练项目的心率(HR)反应的能力,以及预测与实际 HR 反应之间的差异作为体能或准备状态的指标的有用性。
所有数据均在一个赛季(2016-17 年)中收集,使用 5Hz GPS 记录球员的足球活动,使用 HR 监测内部负荷。对典型的小场比赛和 4 分钟标准亚最大强度跑(12km·h)进行 GPS 和 HR 数据分析。使用多元逐步回归分析来确定 GPS 变量的哪些组合与个体水平的 HR 反应相关性最大(HR,每个球员 149[46]GPS/HR 对),并进一步用于预测个体训练时的 HR(HR)。然后,将预测的 HR 与实际 HR 进行比较,以计算体能或准备状态的指标(HR,%)。通过比较亚最大强度跑时 HR 变化和 HR 反应变化(HR,体能标准)以及与赛季不同阶段的关系(预计体能在季前赛后会提高),来检验 HR 的有效性。
HR 与 HR 非常相关(r=.78[.04])。个体内 HR 变化与个体内 HR 变化高度相关(r=.66,.50-82)。HR 很可能从 7 月(3.1%[2.0%])降至 8 月(0.8%[2.2%]),并且很可能在 9 月进一步下降(-1.5%[2.1%])。
HR 是监测精英足球运动员体能的有效变量,可以在正常训练期间每天进行体能监测,减少对正式测试的需求。