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.

Substance use and misuse (SUM) and the relation to physical activity/exercise/athletic participation (sport factors) and scholastic achievement are rarely studied in Croatia. The aim of this study was: (1) to investigate the SUM habits in Croatian adolescents (17-18 years of age, 254 males, and 218 females), and (2) to study potential gender-specific interrelationships between scholastic and sport factors in relation to SUM. The testing was done using an extensive, anonymous, self-administered questionnaire that consisted of scholastic variables, sport factors, and SUM data. Descriptive statistics, counts, and proportions were calculated. Gender differences were established using the Kruskal-Wallis test. Gender-specific correlations within and between studied variables were established using the Spearman's correlation. The incidence of smoking habits and alcohol consumption among Croatian adolescents was alarming, and a serious intervention program should be developed to address this issue. Educational achievement was negatively related to SUM, with no gender-specific relationships. The data indicated some "protective" effects of the sport factors against SUM in boys, but a significant positive correlation between alcohol drinking and sport participation in girls was also noted.

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).

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.

Aerobic performance is considered an important determinant of match running performance in soccer, but studies have rarely investigated this issue in top-level players. This study examined the possible associations between direct measures of aerobic performance and match running performance in elite soccer players. Aerobic performance was tested at the beginning of the season in laboratory settings. The match-running performance was measured by a global positioning system over a competitive half-season for a total of 82 match performances in professional players from Croatia (age: 23.76 ± 2.64; body height: 181.62 ± 7.09 cm; body mass: 77.01 ± 6.34 kg) and clustered as central player (n = 57) and side player (n = 25) performance. No significant differences in aerobic performance were noted between central and side players. The anaerobic threshold was correlated with high-speed running (19.8-25.1 km/h), sprint running (>25.1 km/h), and high-intensity running (>19.8 km/h) among side players (r = 0.52, 0.53, and 0.59, respectively; p < 0.01). For central players, the aerobic threshold was correlated with the total distance covered, low-intensity running (<14.3 km/h), and distance covered in the zone of running (14.4-19.7 km/h) (r = 0.47, 0.49, and 0.39; p < 0.01, 0.01, and 0.03, respectively). Conditioning for central players should include activities with intensities corresponding to aerobic thresholds, while conditioning of side players should be focused on the development of anaerobic thresholds.

Thus, proper and continuous monitoring of the training load is important to determine the applied training load and implement interventions in subsequent sessions (i.e., increases or decreases in the training load; Jaspers et al., 2017; Rebelo et al., 2012). Training loads can comprise external and internal loads (Impellizzeri, Rampinini, Coutts, Sassi, & Marcora, 2004). External training loads are measured by the work done by players and are currently commonly monitored by Global Positioning System (GPS) technology (Buchheit et al., 2013). Internal training loads are measured by the metabolic demands required to complete the external work (Bingham, 2015) and are commonly monitored using physiological and/or perceptual measures such as the player's heart rate and rating of perceived exertion (Coutts & Cormack, 2014). However, the external load (i.e., total distance covered, distances covered in different speed zones, number of accelerations and decelerations) is most

Although associations between running performance (RP) with ball possession and team achievement in soccer are often hypothesized, actual knowledge of this association in elite soccer remains limited. Therefore, this study aimed to evaluate players’ RPs according to ball possession to determine its possible influence on team achievement in the UEFA Champions League (UCL). The players’ RPs (n = 244) were collected during UCL group stage matches (n = 20) in the 2020/21 season using the semiautomatic video system InStat Fitness. Then, players’ RPs were classified according to the specific playing position: central defenders (CD; n = 79), fullbacks (FB; n = 65), central midfielders (CM; n = 55), wide midfielders (WM; n = 28) and forwards (FW; n = 17). RPs were observed in the attacking phase (AP, i.e., when the team was in possession of the ball) and defensive phase (DP, i.e., when the team did not have possession of the ball) of the game, and included the total distance covered (m) and distance covered in different categories: walking (<7.1 km/h), jogging (7.1–14.3 km/h), running (14.4–19.7 km/h), high-intensity running (>19.8 km/h), high-speed running (19.8–25.1 km/h) and sprinting (>25.2 km/h). Team achievement was defined by the total group points earned (TGP) at the end of the group phase of the UCL and by match outcome (win, draw, loss) of single matches. The results indicated that the total, walking and jogging distances covered were negatively and positively associated with TGP (Pearson’s correlations from 0.30 to 0.73; all p < 0.05) in the AP and DP of the game, respectively. Won matches were characterized by significantly lower and higher values of total, walking and jogging distances covered in AP and DP of the game, respectively (F tests: from 7.15 to 22.5, all p < 0.01; all small to medium effect sizes). In addition, RPs in the AP and DP of the game explained only 37.2% of the variance in the TGP. These findings demonstrate that the influence of RP on team achievement in UCL is limited in both the AP and DP of the game.