Running performance (RP) and game performance indicators (GPI) are important determinants of success in soccer (football), but there is an evident lack of knowledge about the possible associations between RP and GPI. This study aimed to identify associations between RP and GPI in professional soccer players and to compare RP and GPI among soccer playing positions. One hundred one match performances were observed over the course of half of a season at the highest level of national competition in Croatia. Players (mean ± SD, age: 23.85 ± 2.88 years; body height: 183.05 ± 8.88 cm; body mass: 78.69 ± 7.17 kg) were classified into five playing positions (central defenders (n = 26), full-backs (n = 24), central midfielders (n = 33), wide midfielders (n = 10), and forwards (n = 8). RP, as measured by global positioning system, included the total distance covered, distance covered in five speed categories (walking, jogging, running, high-speed running, and maximal sprinting), total number of accelerations, number of high-intensity accelerations, total number of decelerations, and number of high-intensity decelerations. The GPI were collected by the position-specific performance statistics index (InStat index). The average total distance was 10,298.4 ± 928.7 m, with central defenders having the shortest and central midfielders having the greatest covered distances. The running (r = 0.419, p = 0.03) and high-intensity accelerations (r = 0.493, p = 0.01) were correlated with the InStat index for central defenders. The number of decelerations of full-backs (r = −0.43, p = 0.04) and the distance covered during sprinting of forwards (r = 0.80, p = 0.02) were associated with their GPI obtained by InStat index. The specific correlations between RP and GPI should be considered during the conditioning process in soccer. The soccer training should follow the specific requirements of the playing positions established herein, which will allow players to meet the game demands and to perform successfully.

Reactive agility (RAG) and change of direction speed (CODS) are important determinants of success in football (soccer), but there is an evident lack of information on reliable and valid football-specific testing procedures which will be applicable in defining sport-specific RAG and CODS in youth players. This study evaluated reliability and construct validity of newly developed tests of football-specific RAG (FS_RAG) and CODS (FS_CODS), which involved the ball kicking football technique. Additionally, factors associated with FS_RAG and FS_CODS were evaluated. The participants were youth football players (n = 59; age: 13.40 ± 1.25 years) divided according to their age into U13 (11–12 years of age; n = 29), and U15 (13–14 years of age; n = 30) categories. Additionally, performance levels (starters [first-team] vs. non-starters [substitutes]) were observed in each age category. The dependent variables were newly developed FS_RAG and FS_CODS tests. The independent variables were sprinting capacities over 10 and 20 meters (S10M, S20M), countermovement jump (CMJ), the reactive strength index (RSI), and a generic CODS test of 20 yards (20Y). The newly developed FS_CODS and FS_RAG were observed as dependent variables. Results showed appropriate intra-testing and inter-testing reliability of the FS_RAG and FS_CODS, with somewhat better reliability of the FS_CODS (ICC=0.82 and 0.79, respectively). Additionally, better reliability was evidenced in U15 than in U13 (ICC: 0.82–0.85, and 0.78-0.80 for U15 and U13, respectively). Independent samples t-test indicated significant differences between U13 and U15 in S10 (t-test: 3.57, p < 0.001), S20M (t-test: 3.13, p < 0.001), 20Y (t-test: 4.89, p < 0.001), FS_RAG (t-test: 3.96, p < 0.001), and FS_CODS (t-test: 6.42, p < 0.001), with better performance in U15. Starters outperformed non-starters in most capacities among U13, but only in FS_RAG among U15 (t-test: 1.56, p < 0.05). Multiple regression calculations indicated nonsignificant association between independent and dependent variables in U13 (FS_CODS: 19%, FS_RAG: 21% of the explained variance, both p > 0.05), but independent variables explained significant proportion of both dependent variables in U15 (FS_CODS: 35%, FS_RAG: 33% explained variance, both p < 0.05). The study confirmed the applicability of newly developed tests in distinguishing studied age categories of players. Results indicate that superiority in all studied fitness capacities is translated into performance level in U13. Meanwhile, FS_RAG seems to be important determinant of quality in U15.

The purpose of this study was to determine the inter- and intra-testing reliability of newly developed tests of the change of direction speed (CODS) and reactive agility (RAG) in competitive futsal players. Additionally, the developed tests were evaluated for their validity with regard to the differentiation of two performance-levels. Thirty-two professional male futsal players (age = 26.22 ± 5.22 years; body height = 182.13 ± 5.99 cm, body mass = 77.43 ± 8.00 kg) participated in the study. The sample was divided into two groups based on their level of futsal performance: A top-level-group (n = 12) and a team-level-group (n = 20). The variables included body height, mass, body mass index, a sprint over a 10-m distance (S10M), and eight newly developed futsal specific CODS and RAG tests. The CODS and RAG tests were performed by dribbling the balls (CODS_D and RAG_D) and without dribbling (CODS_T and RAG_T), and the performances on the dominant and non-dominant sides were observed separately. All CODS, and RAG tests performed on dominant side and RAG_T tests performed on the non-dominant side had good inter-testing (CV = 5–8%; ICC = 0.76–0.89) and intra-testing (CV = 4–9%; ICC = 0.77–0.91) reliability. However, RAG_D performed on the non-dominant side was not reliable (ICC = 0.60, CV = 10%). The top-level-players outperformed the team-level-players in the CODS and RAG tests that involved dribbling (t-test: 4.28 and 2.40, p < 0.05; effect sizes (ES): 0.81 and 1.5, respectively), while the team-level players achieved better results in the CODS_T (t-test: 2.08, p < 0.05; ES: 0.60). The proposed CODS and RAG tests that involved dribbling over a 3.2-m distance, especially on the dominant side, appeared to be reliable, as well as valid for distinguishing the performance level in futsal players.

Running performances (RPs) are known to be important parameters of success in football (soccer), but there is a lack of studies where RPs are contextualized regarding applied tactical solutions. This study aims to quantify and analyze the differences in position-specific RPs in professional football, when games are played with three defensive players (3DP) and four defensive players (4DP). The participants here include professional football players (M ± SD, age 23.57 ± 2.84 years, body height 181.9 ± 5.17 cm, body mass 78.36 ± 4.18 kg) playing at the highest competitive level in Croatia. RPs were measured by global positioning system and classified into four groups based on playing positions: central defenders (CD; n = 47), wide defenders (WD; n = 24), midfielders (MF; n = 48), or forwards (FW; n = 19). Analysis of variance and discriminant canonical analysis are used to identify differences between 3DP and 4DP tactical solutions in terms of the RPs for each playing position. The number of accelerations and decelerations most significantly contributed to the differentiation of 3DP and 4DP among MFs (Wilks λ = 0.31, p < 0.001), with higher occurrences with 3DP. For CDs, total distance, and high-intensity running were higher in 3DP (Wilks λ = 0.66, p < 0.001). No multivariate differences were found for FW and WD players in terms of the RPs between 3DP and 4DP tactical formations. The characteristics and differences shown in this study may provide useful information for coaching staff regarding changing in-season tactical formations. Additionally, the results are useful for optimizing training programs for football players with different playing positions. When changing from 4DP to 3DP tactical formations, WDs training programs should include more of high-intensity running, while MFs training programs should be more based on short intensity activities (accelerations and decelerations).

Summary Study aim: The aim of this study was to determine the fitness profiles of senior and junior futsal players and to identify potential differences between the studied age groups. Materials and methods: 44 male futsal players from 5 professional futsal teams participated in this study. Subjects were divided into two age groups (seniors [>18 years; n = 26] vs juniors [<18 years of age; n = 18]). Players were tested for anthropometrics (body mass, body height and body fat percentage), jumping capacity (countermovement jump and standing broad jump), kicking speed (for dominant and non-dominant leg), sprinting capacity (5- and 10-meter sprints), 20-yard test, futsal-specific reactive agility, and futsal-specific change-of-direction speed tests. Results: No significant differences between age groups were apparent for anthropometrics. Seniors achieved better results than juniors in tests of kicking speed, for both the dominant (106.81 ± 6.94 km/h and 100.94 ± 5.33 km/h, respectively, t-test: 3.02 [p < 0.001], Cohen’s d: 1.02) and nondominant leg (95.54 ± 8.57 km/h and 85.28 ± 8.71 km/h, respectively, t-test: 3.88 [p < 0.001], Cohen’s d: 1.25). Conclusions: Seniors did not achieve significantly better results than juniors in most of the observed variables. Since the maximum biological maturity occurs up to 18 years, and studied juniors were in their late adolescence, we can assume that differences between groups are related to other indices (i.e. technical skills, tactical knowledge).

The aim of this study was to identify associations between aerobic fitness (AF) and game performance indicator (GPI) in elite football. Participants were professional football players (males, n ¼ 16; age: 23.76 AE 2.64; body height: 181.62 AE 7.09 cm; body mass: 77.01 AE 6.34 kg). AF testing was conducted by direct measurement and included VO2max, running speed at aerobic threshold (AeT), and running speed at anaerobic threshold (AT). The GPI were collected by the position-specific performance statistics index (InStat index). The players were observed over one competitive half-season, resulting in 82 game performances, grouped according to the positions in game: defenders (n ¼ 39), midfielders (n ¼ 32) and forwards (n ¼ 11). VO2max was not found to be a good discriminator of AF among different playing positions. AeT (F-test ¼ 26.36. p ¼ 0.01) and AT (F-test ¼ 7.25, p ¼ 0.01) were highest among midfielders, and lowest among forwards. No correlations were found between AF and GPI. This study confirmed that AeT and AT are better indicators of AF than VO2max in football players at different playing positions. The lack of associations between AF and GPI was discussed with regard to calculation of InStat as a GPI.

There is an evident lack of studies examining the pursuit of excellence in futsal. The aims of this study were to evaluate anthropometric and physiological variables that may contribute to distinguishing among performance levels in professional futsal players and to evaluate correlates of those variables. The participants were 75 male professionals (age = 25.1 ± 5.1 years, body height = 182.3 ± 6.2 cm, body mass = 80.8 ± 10.4 kg), who were divided into performance levels using two criteria: (i) starters (first teams) vs. non-starters (substitutes) and (ii) top-level players (members of the national team and players who participated in top-level team competition in Europe) vs. high-level players (team players competing at the highest national competitive rank). Variables included anthropometrics (body height and mass, BMI, body fat percentage), generic tests of physiological capacities [5- and 10-m sprints, countermovement jump, broad jump, 20-yard test, reactive strength index (RSI)], and futsal-specific fitness tests [kicking speed by dominant and non-dominant leg, futsal-specific tests of change of direction speed, and reactive agility (FSRAG) involving/not involving dribbling the ball]. Top-level players outperformed high-level players in RSI, broad jump, kicking speed, and FSRAG involving dribbling. Starters achieved better results than non-starters in fewer variables, including kicking speed and RSI. Body fat percentage negatively influenced FSRAG involving dribbling, and RSI. FSRAG, RSI, and kicking speed were significantly correlated, indicating the similar physiological background of these capacities. The findings suggest that enhanced reactive strength and the ability to rapidly change direction speed in response to external stimulus while executing futsal-specific motor tasks (e.g., dribbling), along with players’ ability to kick the ball speedily, can be considered essential qualities required for advanced performance in futsal. Consequently, futsal strength and conditioning training should be targeted toward lowering relative body fat, maximizing lower-body reactive strength and including futsal-specific skills (e.g., dribbling, shooting) in reactive agility drills.

Parental/familial factors are important determinants of the physical activity level (PAL) in children and adolescents, but studies rarely prospectively evaluate their relationships. This study aimed to evaluate the changes in physical activity levels among adolescents from Bosnia and Herzegovina over a two-year period and to determine parental/familial predictors of PAL in early adolescence. A total of 651 participants (50.3% females) were tested at baseline (beginning of high school education; 14 years old on average) and at follow-up (approximately 20 months later). The predictors included sociodemographic characteristics (age, gender) and parental/familial factors (socioeconomic status of the family, maternal and paternal education, conflict with parents, parental absence from home, parental questioning, and parental monitoring). Physical activity levels were evidenced by the Physical Activity Questionnaire for Adolescents (PAQ-A; criterion). Boys were more active than girls, both at baseline (t-test = 3.09, p < 0.001) and at follow-up (t-test = 3.4, p < 0.001). Physical activity level decreased over the observed two-year period (t-test = 16.89, p < 0.001), especially in boys, which is probably a consequence of drop-out from the sport in this period. Logistic regression evidenced parental education as a positive predictor of physical activity level at baseline (OR [95% CI]; 1.38 [1.15–170], 1.35 [1.10–1.65]), and at follow-up (1.35 [1.11–1.69], 1.29 [1.09–1.59], for maternal and paternal education, respectively). Parents with a higher level of education are probably more informed about the importance of physical activity on health status, and thus transfer this information to their children as well. The age from 14 to 16 years is likely a critical period for maintaining physical activity levels in boys, while further studies of a younger age are necessary to evaluate the dynamics of changes in physical activity levels for girls. For maintaining physical activity levels in adolescence, special attention should be paid to children whose parents are less educated, and to inform them of the benefits of an appropriate physical activity level and its necessity for maintaining proper health and growth.