Zlojutro Nemanja, Eler Serdar, Joksimovic Marko, Eler Nebahat, Marković Saša, Kukrić Aleksandar, Goranovic Kosta
Faculty of Physical Education and Sport, University of Banja Luka, Banja Luka, Bosnia and Herzegovina.
Faculty of Sport Science, Gazi University, Ankara, Ankara, Türkiye.
Front Physiol. 2023 Apr 7;14:1150713. doi: 10.3389/fphys.2023.1150713. eCollection 2023.
The goal of this paper is to determine what happens in one minute (on average) in kinematic parameters and metabolic power in small sided games (SSG) (3v3; 5v5) and large sided games (LSG) (10v10) and in which games kinematic parameters and metabolic power are best developed. The participants of this study were 22 professional football players, height 182.95±6.52 cm, mass 77.17±8.21 kg, body mass index (BMI) 22.97±1.47 kg/m2, body fat 9.85±2.55 %, aged 27.1±5.4 yrs, who played in the Premier League of Bosnia and Herzegovina. Data total distance (TD), maximum speed (MS), number of accelerations (nAcc), number of decelerations (nDec), number of sprints (nS), high intensity distance (Z4≥19.8 km/h), sprint distance (Z5≥25.2 km/h) and movements requiring a certain metabolic power (Pmet), were collected using a 20 Hz Global positioning system (GPS) system Pro2 (GPEXE, Exelio srl, Udine, Italy), on a total of 307 individual observations. The results showed that the average total distance was significantly higher in the 5v5 (135.16±18.78 m) and 10v10 (133.43±20.06 m) games (F=64.26, p<0.001) compared to the 3v3 (108.24±11.26 m). Furthermore, the values of the variables Z4 (8.32±3.38 m, F=97.59), Z5 (1.84±1.53 m, F=123.64), nS (0.13±0.10 n, F=96.14) as well as Maxspeed (27.06±1.90 km/h, F=139.33), are statistically significantly higher (p<0.001) in the 10v10 game compared to the other two game formats. The average number of nAcc (0.40±0.32 n, F=9.86, p<0.001) and nDec (0.62±0.36 n, F=6.42, p<0.001) is statistically significantly higher in the 5v5 game. The results showed that the 5v5 game is significantly more metabolically demanding Pmet (2.76±0.67 W•kg, F=66.08, p<0.001) compared to the other two game formats. The data presented in this paper can be used as a basis for the construction of specific exercises based on kinematic and physiological requirements, and for planning and programming microcycles in football.
本文的目的是确定在小场地比赛（SSG）（3对3；5对5）和大场地比赛（LSG）（10对10）中，平均每分钟的运动学参数和代谢功率会发生什么变化，以及在哪种比赛中运动学参数和代谢功率能得到最佳发展。本研究的参与者是22名职业足球运动员，身高182.95±6.52厘米，体重77.17±8.21千克，身体质量指数（BMI）22.97±1.47千克/平方米，体脂9.85±2.55%，年龄27.1±5.4岁，他们都在波斯尼亚和黑塞哥维那超级联赛踢球。使用20赫兹的全球定位系统（GPS）Pro2系统（GPEXE，Exelio srl，乌迪内，意大利）收集了总共307次个体观察的数据，包括总距离（TD）、最大速度（MS）、加速次数（nAcc）、减速次数（nDec）、冲刺次数（nS）、高强度距离（Z4≥19.8千米/小时）、冲刺距离（Z5≥25.2千米/小时）以及需要一定代谢功率（Pmet）的运动。结果表明，与3对3比赛（108.24±11.26米）相比，5对5比赛（135.16±18.78米）和10对10比赛（133.43±20.06米）的平均总距离显著更高（F = 64.26，p < 0.001）。此外，与其他两种比赛形式相比，10对10比赛中变量Z4（8.32±3.38米，F = 97.59）、Z5（1.84±1.53米，F = 123.64）、nS（0.13±0.10次，F = 96.14）以及最大速度（27.06±1.90千米/小时，F = 139.33）的值在统计学上显著更高（p < 0.001）。5对5比赛中加速次数（0.40±0.32次，F = 9.86，p < 0.001）和减速次数（0.62±0.36次，F = 6.42，p < 0.001）的平均值在统计学上显著更高。结果表明，与其他两种比赛形式相比，5对5比赛的代谢需求Pmet显著更高（2.76±0.67瓦·千克，F = 66.08，p < 0.001）。本文所呈现的数据可作为根据运动学和生理学要求构建特定训练的基础，以及用于足球比赛中微周期的规划和编排。
