Sprinting is a decisive action in soccer that is considerably taxing from a neuromuscular and energetic perspective. This study compared different calculation methods for the metabolic power (MP) and energy cost (EC) of sprinting using global positioning system (GPS) metrics and electromyography (EMG), with the aim of identifying potential differences in performance markers. Sixteen elite U17 male soccer players (age: 16.4 ± 0.5 years; body mass: 64.6 ± 4.4 kg; and height: 177.4 ± 4.3 cm) participated in the study and completed four different submaximal constant running efforts followed by sprinting actions while using portable GPS-IMU units and surface EMG. GPS-derived MP was determined based on GPS velocity, and the EMG-MP and EC were calculated based on individual profiles plotting the MP of the GPS and all EMG signals acquired. The goodness of fit of the linear regressions was assessed by the coefficient of determination (R2), and a repeated measures ANOVA was used to detect changes. A linear trend was found in EMG activity during submaximal speed runs (R2 = 1), but when the sprint effort was considered, the trend became exponential (R2 = 0.89). The EMG/force ratio displayed two different trends: linear up to a 30 m sprint (R2 = 0.99) and polynomial up to a 50 m sprint (R2 = 0.96). Statistically significant differences between the GPS and EMG were observed for MP splits at 0–5 m, 5–10 m, 25–30 m, 30–35 m, and 35–40 m and for EC splits at 5–10 m, 25–30 m, 30–35 m, and 35–40 m (p ≤ 0.05). Therefore, the determination of the MP and EC based on GPS technology underestimated the neuromuscular and metabolic engagement during the sprinting efforts. Thus, the EMG-derived method seems to be more accurate for calculating the MP and EC in this type of action.

中文翻译：

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精英青少年足球运动员使用不同方法进行次最大跑步和冲刺跑的代谢功率和能量消耗的比较：一种新颖的能量方法

冲刺是足球运动中的决定性动作，从神经肌肉和能量的角度来看，它对神经肌肉和能量的消耗相当大。本研究使用全球定位系统（GPS）指标和肌电图（EMG）比较了短跑代谢功率（MP）和能量成本（EC）的不同计算方法，旨在识别表现标记的潜在差异。 16名U17精英男子足球运动员（年龄：16.4±0.5岁；体重：64.6±4.4公斤；身高：177.4±4.3厘米）参与了这项研究，并在使用便携式GPS的情况下完成了四种不同的次最大持续跑步努力，然后是冲刺动作-IMU 单元和表面肌电图。 GPS 衍生的 MP 是根据 GPS 速度确定的，并且 EMG-MP 和 EC 是根据绘制 GPS 的 MP 和采集的所有 EMG 信号的个人轮廓来计算的。线性回归的拟合优度通过确定系数 (R2) 进行评估，并使用重复测量方差分析来检测变化。在次最大速度跑步期间，肌电图活动呈线性趋势（R2 = 1），但当考虑冲刺努力时，趋势变为指数趋势（R2 = 0.89）。 EMG/力比显示出两种不同的趋势：30 m 冲刺 (R2 = 0.99) 呈线性趋势，50 m 冲刺 (R2 = 0.96) 呈多项式趋势。对于 0-5 m、5-10 m、25-30 m、30-35 m 和 35-40 m 的 MP 分割以及 5-10 m、25 EC 分割，观察到 GPS 和 EMG 之间存在统计显着差异。 –30 m、30–35 m 和 35–40 m (p ≤ 0.05)。因此，基于 GPS 技术确定的 MP 和 EC 低估了短跑期间的神经肌肉和代谢参与。因此，EMG 衍生方法对于计算此类动作中的 MP 和 EC 似乎更准确。