The Institute of Sport Science at the University of West-Hungary, and the FH-Joanneum -together with students majoring in sport science -started a collaborative international research aimed at assessing the sport-specific skills of football players. The study closely monitored football players -from leagues at different levels -in terms of choice reaction time, short and long pass skills and agility skills with and without a ball. The most modern device available, the SmartSpeed -a photoelectric stopwatch system -was used for the measurements. The data obtained by the applied internationally standardized tests can be compared in terms of players from leagues at different levels. The study occurred using correlation analysis (p<0.05), and we used linear regression to compare laterality. The hypothesis that teams playing in higher league are significantly more successful in terms of the evaluated technical parameters has not been verified in all cases. There are interesting results regarding the differences between moving to the opposite side with and without ball. The results of the Hungarian team (N=97 players) can be compared to those of the Austrian and international players.

The aim of this study is to determine body composition (BC) factors that influence agility among adolescent soccer players (N=66), in U14, U16, U18 soccer teams of the Topola Sport Club. Agility tests (Dribbling test, Illinois test), Inbody 720 instrument measuring the BC, and Oxa Starter infrared timing gate instrument measuring speed the agility were used. Data are processed by the IBM SPSS Statistics 25 software. In addition to descriptive statistics, a correlation matrix analysis, linear regression and one-way analysis of variance (ANOVA) were also applied (p<0.05). A moderate correlation between agility with a ball and without a ball (r=0.595) is determined as well as between agility and BC parameters: Skeletal Muscle Mass, Intracellular Water Mass, Protein Mass, Mineral Mass (r=-0.453, -0.454, -0.453, -0.417, respectively) while the correlation between agility and Height, Mass, Body Mass Index, Right Leg Lean Mass, Left Leg Lean Mass, Extracellular Water Mass is less than moderate (r=-0.318, -0.329, -0.276, -0.332, -0.330, -0.374, respectively). A slight correlation is determined between agility with a ball and BC variables. No correlation was determined between Agility and Body Fat Mass. The influence of BC on agility is lower than expected. Using the scientific based approach and measurements, a complex exercise plan can be made for players and in this way young soccer players can be trained by using tailor-made and post-specified coaching methods.

Data measured in the U15–U19 age groups at the football academy were analyzed during the research (N = 70). These data comprised Body Mass, Height, YYIR1, 30 m running, FMS, and SLJ, Locomotor parameters using the 6-week averages of Catapult OptimEye S5, mechanical performance parameters. The players did well in the motoric tests: YYIR1 (M = 2155, SD = 311), 30 m (M = 4.34, SD = 0.26), and SLJ (M = 2.28, SD = 0.18), and the different age groups underwent dynamic improvement. The young soccer players ran 19,552m players ran 568, 298, and 97 m in the moderate-, high-, and sprint-intensity zones. The athletes’ maximum speed was M = 26.72 km/h (SD = 1.74). The differences between the age groups were justified statistically in each case.

The monitoring of young soccer players’ training load using up-to-date devices is essential from the point of view of continuous improvement at high-quality soccer academies. In the present study, we used tests that are accepted and valid in soccer, which were performed frequently to find out more about improvement. Data measured in the U15–U19 age groups at the Illés Academy in Szombathely were analyzed during the research (N = 70). These data comprised (a) body parameters and performance trials: Body Mass, Height, Yo-Yo intermittent recovery test–level 1 (YYIR1), 30 m running, Functional Movement Screening (FMS), and Standing Long Jump (SLJ). (b) Locomotor parameters using the 6-week averages of Catapult OptimEye S5 standardized weekly reports of locomotor performance data (weeks 42–47, 2019): Total Time, Total Distance (m), Velocity Bands 4–6 Average Effort counts and distances, and Maximum Velocity. (c) Mechanical performance parameters: Total Player Load (TPL), high-intensity acceleration, high-intensity deceleration, Change of Direction (CoD) Left, High, CoD Right, High, and Explosive Effort (EE). The Illés Academy players did well in the motoric tests: YYIR1 (M = 2155, SD = 311), 30 m (M = 4.34, SD = 0.26), and SLJ (M = 2.28, SD = 0.18), and the different age groups underwent dynamic improvement. The young soccer players ran 19,552 m on average in their weekly training sessions (SD = 4562): players ran 568, 298, and 97 m in the moderate-, high-, and sprint-intensity zones (Velocity Band 4–5–6 Average Distance) (SD = 287, 148, and 67). The number of moderate-, high-, and sprint-intensity actions (Velocity Band 4–5–6 Average Effort Counts) was M = 58.32, 24.24, and 6.20 (SD = 24.41, 11.30, and 3.74). The athletes’ maximum speed was M = 26.72 km/h (SD = 1.74). The differences between the age groups were justified statistically in each case. Moderate or more intensive correlations were not found between the different intensity of running and the body parameters. High-intensity correlations were found between the completed total distance and the number of moderate-intensity actions (r = 0.806, p &lt; .001), and high correlations were found between the moderate-intensity and high-intensity running (r = 0.933, p &lt; .001).