Search Results (58)

In the present study, 96 teams’ performances across 48 matches in the group stage of the FIFA Club World Cup 2025 were analyzed. Teams scoring first won 62.5% of matches (p < 0.05), while goals were evenly distributed between halves (p > 0.05) and showed marginal variation across six 15 min intervals, peaking near the 30–45 and 75–90 min marks. Parametric analyses revealed a significant effect of match outcome on possession, with winning teams exhibiting higher average possession (53.3%) compared to losing and drawing teams. Non-parametric analyses identified significant differences between match outcomes for goals scored, attempts at goal, total and completed passes, pass completion rate, defensive line breaks, receptions in the final third, ball progressions, defensive pressures, and total distance covered. Winning teams scored more goals and registered more attempts on target than losing teams, although some metrics showed no significant difference between wins and draws. Logistic regression analysis identified attempts at goal on target, defensive pressures, total completed passes, total distance covered, and receptions in the final third as significant predictors of match success (AUC = 0.85), correctly classifying 80.2% of match outcomes. These results emphasized the crucial role of offensive accuracy and possession dominance in achieving success in elite football. Full article

The aim of this study was to analyze and compare the external load demands of players from the Spanish women’s national football teams across the U-17, U-20, and senior categories during their respective FIFA World Cup participations. Key kinematic variables were assessed via global positioning systems (GPS), including total distance (TD), high-speed running (HSR; ≥18 km·h⁻¹), sprint distance (≥21 km·h⁻¹), accelerations (>3 m·s⁻²), decelerations (<–3 m·s⁻²), and high metabolic load distance (HMLD) during 3 world cups (U17, U20 and senior). Significant differences were observed between the senior team and both U-20 and U-17 in nearly all variables, with greater magnitude as the intensity of the metrics increased, showing effect sizes ranging from moderate to very large (d = 0.95 to 4.76). Positional analysis by categories showed that senior full backs (FB) and central midfielders (CM) showed higher demands compared to U-20 and U-17. For TD, senior covered more than U-17 (FB: p = 0.001; d = 1.11 | CM: p = 0.023; d = 0.97), with small differences vs. U-20 (d ≤ 0.54). In HSR, both positions outperformed U-17 and U-20 (FB: p ≤ 0.007; d = 0.87–1.15 | CM: p ≤ 0.031; d = 0.71–1.11). In HMLD, both FB and CM displayed very large differences compared to U-17 and U-20 (all p < 0.001; d = 2.54–6.16). These findings underscore the need for progressive development of locomotor capacities from early stages, considering both age category and playing position, to facilitate a more seamless transition to elite-level football. Full article

Football performance results from the dynamic interaction between physical, tactical, technical, and psychological dimensions—each of which also influences player well-being, recovery, and readiness. However, integrated monitoring approaches remain scarce, particularly in youth and sub-elite contexts. This systematic review screened 341 records from PubMed, Scopus, and Web of Science, with 46 studies meeting the inclusion criteria (n = 1763 players; age range: 13.2–28.7 years). Physical external load was reported in 44 studies using GPS-derived metrics such as total distance and high-speed running, while internal load was examined in 36 studies through session-RPE (rate of perceived exertion × duration), heart rate zones, training impulse (TRIMP), and Player Load (PL). A total of 22 studies included well-being indicators capturing fatigue, sleep quality, stress levels, and muscle soreness, through tools such as the Hooper Index (HI), the Total Quality Recovery (TQR) scale, and various Likert-type or composite wellness scores. Tactical behaviours (n = 15) were derived from positional tracking systems, while technical performance (n = 7) was assessed using metrics like pass accuracy and expected goals, typically obtained from Wyscout^® or TRACAB^® (a multi-camera optical tracking system). Only five studies employed multivariate models to examine interactions between performance domains or to predict well-being outcomes. Most remained observational, relying on descriptive analyses and examining each domain in isolation. These findings reveal a fragmented approach to player monitoring and a lack of conceptual integration between physical, psychological, tactical, and technical indicators. Future research should prioritise multidimensional, standardised monitoring frameworks that combine contextual, psychophysiological, and performance data to improve applied decision-making and support player health, particularly in sub-elite and youth populations. Full article

This study aimed to examine whether managerial changes and their training methodology influence the physical attributes of soccer players and determine if these changes significantly impact the overall physical performance of the team. Twenty-seven male elite-level football players competing in the Eastern Mediterranean region (age: 28.12 ± 5.5 years, height: 179.3 ± 6.25 cm, body mass: 75.8 ± 6.6 kg) participated in this study. To analyze the impact of managerial changes on elite football players’ physical performance, this study evaluated and compared physical attributes during weekly microcycles and official games across three different coaching regimes over an entire season. Data were collected using a 10 Hz GPS tracking technology and included the following external load (EL) parameters: total distance, high metabolic load distance, high-speed running, sprint distance, accelerations, and decelerations. A one-way Analysis of Variance (ANOVA) was utilized to assess differences in physical performance across the three coaching methods. Significant differences were evident in high metabolic load distance during games [F(2,27) = 7.59, p < 0.05]. High-speed running distance also varied significantly across the three coaching regimes, both during training sessions [F(2,27) = 5.89, p < 0.05] and games [F(2,27) = 4.31, p < 0.05]. Furthermore, sprint distance showed significant differences during training [F(2,27) = 4.62, p < 0.05] and games [F(2,27) = 3.37, p < 0.05]. The findings of this study suggest that managerial changes can have a significant effect on the physical performance of soccer players. The results highlight the importance of aligning coaching strategies with physical conditioning techniques for optimizing performance. These findings provide a deeper understanding of the potential benefits and risks associated with managerial changes in professional soccer. Nevertheless, a limitation in this study is that all metrics of EL were interpreted as absolute values rather than relative-based threshold values, which may affect the interpretation of the players’ physical capacities. Full article

In this paper, multi-option probabilistic paired comparison models are presented and applied for prediction. As these models operate on the basis of probabilities, they can estimate the likelihood of future outcomes and thus predict future events. The aim of the paper is to demonstrate that these models have strong predictive capabilities when the information embedded into the data is properly utilized. To this end, we incorporate the degree (e.g., large or small) of the differences between the compared objects. By refining the usual three-option model, we define a five-option model capable of leveraging information derived from the goal differences. To incorporate additional information, the model is further extended to account for potential advantages in the comparisons. As a further refinement, temporal weighting is also introduced. These models are applied to forecasting football match outcomes in the top five European leagues (Premier League, La Liga, Serie A, Bundesliga, and Ligue 1), and their predictive performance is evaluated using various metrics. Based on the most recent football seasons, this model consistently delivers better predictive metrics, on average, than those of the already strong benchmark model. The effect of a home-field advantage is statistically supported across all five leagues. The model fits are illustrated using confidence intervals, and, as an interesting insight, we also present the evolution of the team strengths for the top four English clubs during the 2023/24 season. Full article

This study aimed to compare the external peak physical demands (PDs) of under-19-year-old (U19) and professional male football players according to playing position. Positional data derived from Global Positioning System (GPS) tracking during 15 matches in the 2023/24 season for both groups were analyzed. The following variables were measured: total distance, high-intensity running distance, sprint distance, acceleration count, and high-intensity actions. A linear mixed-effects model was employed, with category and playing position included as fixed effects to compare these metrics at the player level. The results revealed only a few significant differences in physical demands between the U19 and professional players. Notably, central defenders and central midfielders exhibited lower performance in HSR distance compared to other positions, with the professional players registering higher values than their U19 counterparts. However, no significant differences were observed for total and relative sprint distances, the number of accelerations, high intensity and relative sprint running efforts. These findings highlight the overall similarity in physical demands between U19 players and professional players, suggesting that elite youth athletes may be adequately prepared to meet the physical challenges of professional competition, with the exception of HSR distance. These conclusions have practical implications for coaches and performance staff, supporting the development of position-specific training programs, optimizing workload management through GPS monitoring, improving microcycle planning, and enhancing injury prevention strategies. Full article

Over the past 20 years, the use of the global positioning system (GPS) in football has become widespread. This technology has facilitated the tracking of external load both during training sessions and matches. Creating an external load profile for each playing position within specific formations can assist the coaching staff in shaping the training load of the microcycle according to the demands of each position. The purpose of this study was to create the running performance profile for high-level young football players based on their playing position in the 1-4-2-3-1 formation and to investigate potential differences between positions. Additionally, the study aimed to compare the players’ running performance across the two halves of the match. The study involved 22 Under-19 players from the academy of a professional football team. Only matches where the team used the 1-4-2-3-1 formation were analyzed (10 matches). The playing positions were categorized as: Central Defensive Fielders (CDFs), Central Midfielders (CMFs), Forwards (FWDs), Wide Defensive Fielders (WDFs), and Wide Midfielders (WMFs). Player movement was tracked using GPS devices and categorized into four velocity zones: (Zone 1: 3.6–10.8 km/h, Zone 2: 10.9–18.0 km/h, Zone 3: 18.1–25.2 km/h, Zone 4: >25.2 km/h). Depending on whether normality was present in our data, either a one-way analysis of variance (ANOVA) or a Kruskal–Wallis test was conducted. A subsequent analysis was performed to compare the performance between the first and second halves of the match, using either the independent samples t-test or the Mann–Whitney U test. The results showed that CMF players covered the greatest total distance and had the highest movement velocity (distance/min) compared to all other positions (p = 0.001). In high-speed running (>18 km/h), CMF again covered the greatest distance, followed by WDF. In sprinting, CDF covered the shortest distance and reached the lowest maximum speed (p = 0.001). CMF performed the most accelerations and decelerations across all positions (p = 0.001). As for the entire team, total distance, movement rate, and the number of accelerations and decelerations decreased in the second half. All players except the WDF also showed a decrease in total distance, while midfielders experienced a notable drop in sprint distance. In conclusion, this study underscores the positional specificity of physical demands in elite football and the systematic decline in physical output as matches progress. While all positions demonstrated some level of second-half performance deterioration, midfielders experienced the most significant decreases in both volume and intensity-related metrics. These insights offer valuable implications for position-specific physical condition, recovery planning, and substitution strategies, helping to optimize performance and manage player load in elite football environments. It should be reiterated that the results of the present study apply exclusively to the 1-4-2-3-1 formation. Full article

This study investigated physiological differences in cardiorespiratory and metabolic performance parameters between professional football players from top- (TR) and mid-ranked teams (MR) in the Serbian Super League. A total of 55 male outfield players (TR: n = 29; MR: n = 26) were assessed in March 2022 using a maximal multistage treadmill protocol and lactate analysis. The key cardiorespiratory variables included maximum oxygen uptake (VO₂max), heart rate at the anaerobic threshold (HR AT), and recovery heart rate metrics, while the metabolic variables focused on lactate concentrations and efficiency indices. The results indicate that the TR players achieved significantly lower HR AT values (162 ± 10.26 vs. 168.77 ± 7.28 bpm; p = 0.017) and demonstrated superior second-minute recovery (%Re 2′: 66.62 ± 14.08% vs. 34.53 ± 9.13%, p < 0.001). In contrast, the MR players exhibited higher VO₂max (62.65 ± 4.48 vs. 60.06 ± 3.29 mL/kg/min; p = 0.017) and greater cardiorespiratory efficiency scores. The lactate parameters were comparable between the groups, except for the metabolic efficiency index (Index ME), which were favorable among the TR players (p = 0.011). These findings highlight that while MR players possess higher aerobic capacity, TR players demonstrate superior physiological recovery and metabolic control, reflecting adaptations to different tactical demands and match intensities. The results offer practical implications for individualized training design and performance monitoring in elite football settings. Full article

Objective: Understanding unique ways that strength and power contribute to on-field performance in collegiate-based American football might aid coaches in recruiting and determining starters. Using retrospective analysis of existing data, including starting status (STR) and number of defensive tackles or contributing plays (CP), we sought a viable strategy to observe on-field play. Our purpose was to determine what role baseline and in-season strength, and power metrics contributed to on-field football performance (e.g., using STR and CP) from one Football Championship Subdivision (FCS) university. We hypothesized greater pre-season (baseline) and in-season (repeated variables) strength and power outcomes would lead to an increased number of STR among players (n = 53) as well as CP among defensive players (n = 30). Method: Power, determined through countermovement jump (CMJ) was observed weekly using a VALD Performance force deck (i.e., jump height) over a 9-week, in-season period (excluding weeks 6 and 8, a bye week, and erroneous data, respectively). Baseline measures of strength and power were also collected at the beginning of the season for each player using four specific measurements, namely the following: (a) peak vertical jump; (b) pull-ups to failure; (c) a one rep max for bench press; (d) power clean. Pearson’s correlation was used to correlate baseline measures and weekly power, along with baseline measures and the total number of STR and CP each week. Additionally, linear regressions were used to examine the effects of baseline measures (vertical jump, bench press) on STR and CP. Results: Moderate correlations (r > 0.5) were observed between baseline variables and weekly CMJ measures. Baseline measures of power clean were correlated with CP only in week 4. All other analyses were not significant. Conclusions: Since our on-field performance variables were not significant, future research should focus on more potent variables, as reported in the literature, such as football IQ, initial recruiting status, and psychological resilience, in addition to accounting for strength and power metrics. Full article

This study aimed to analyze the in-match physical requirements of cerebral palsy football (CP football) players over an entire national league season (56 matches) and their relationship with team performance-related metrics. Key variables examined included total distance, distance at different intensities, acceleration/deceleration patterns, and ball contacts at various intensities. Statistical analyses (one-way ANOVA, t-tests, Pearson’s correlations, and multiple linear regressions) were conducted to identify differences and predictive relationships between these physical requirements and team success indicators (ranking position, points, and goal-related outcomes). Higher-ranked teams covered significantly greater total and walking distances (t = 2.73 and 3.09, p < 0.01). Total distance had the strongest relationship with team performance (r = 0.91–0.99, R² = 0.82–0.99), followed by walking and low-intensity distances (r = 0.71–0.92, R² = 0.66–0.88) and certain acceleration/deceleration actions. In contrast, no significant differences were found in high-intensity actions or ball contact patterns between teams with different performance-related outcomes. These findings suggest that success in CP football is closely related to total distance, particularly at low intensities, indicating a strong connection between physical requirements and tactical strategies. These insights are valuable for coaches and sports professionals, helping to optimize match strategies and training approaches to enhance team performance. Full article

This study aimed to investigate the relationship between visual system parameters (visual acuity and refractive error) and postural balance under controlled conditions in elite football players. Visual acuity (monocular and binocular) and refractive errors were assessed in 34 male athletes using retinoscopy and subjective refraction. Postural stability was assessed with the Cyber-Sabots™ platform, recording the center of pressure (CoP) metrics, including sway amplitude, velocity, and distribution area. Visual and postural parameter correlations were assessed using Pearson’s test (p < 0.05). Athletes demonstrated good binocular visual acuity (−0.03 ± 0.09 logMAR) and were predominantly emmetropic. Visual acuity and postural parameters showed significant negative correlations, whereby visual acuity was associated with reduced CoP displacement (r = −0.352) and sway area (r = −0.367), indicating enhanced stability. Hyperopia and oblique astigmatism were moderately correlated with increased sway (r = 0.343) and antero-posterior sway amplitude in the sagittal plane (r = 0.324). Anisometropia showed moderately negative correlations with antero-posterior control (r = −0.421), suggesting a disruptive effect on postural stability. The postural analysis showed adaptations characteristic of football players, including anterior body inclination, increased forefoot loading, and medio-lateral sway. Romberg’s quotients highlighted significant visual input reliance for maintaining postural balance. Visual acuity, refractive errors, and interocular refractive asymmetries significantly influence postural stability in elite football players. These results support incorporating visual function assessment into training and injury prevention in elite sports. Full article

Background: Proper nutrition is crucial for optimizing performance and recovery in elite young football players. This study aimed to assess sports nutrition knowledge, adherence to the Mediterranean diet (MD), and carbohydrate intake across different training phases, evaluating their relations with match performance. Methods: Thirty-three male HNK Hajduk academy players (15–19 years) completed a nutrition questionnaire and a seven-day food diary, while performance metrics were analyzed using GPS tracking. Results: The results showed that sports nutrition knowledge was generally low (43.0 ± 17.0%), with significant misconceptions about carbohydrate fueling strategies. Players significantly overestimated their MD adherence, with a self-reported KIDMED index (6.06 ± 2.41) notably higher than the corrected score derived from food diaries (4.21 ± 2.53, p < 0.001). Carbohydrate intake was suboptimal on match-related days (3.64 g/kg on match day, 4.45 g/kg on the day before), failing to meet the recommended minimum of 6 g/kg per day. Regression analysis predicted that energy (β = 0.83; p = 0.02) and carbohydrate intake (β = 0.69; p = 0.03) on match day significantly predicted distance covered per minute, with a positive relationship observed for both outcomes, highlighting its impact on endurance. However, no significant relationship was found between carbohydrate intake and maximum sprint speed. Conclusions: These findings underscore the need for structured nutrition education within football academies to enhance players’ dietary habits and performance outcomes. Future research should focus on longitudinal interventions to assess how improved nutrition knowledge influences dietary adherence and athletic performance over time. Although knowledge of sports nutrition is fundamental, practical training and education to improve dietary competencies are crucial for athletes to effectively apply this knowledge in daily training and match preparations. Full article

Match running speed demands vary across competitive levels of football, influenced by player position, tactical considerations, and Head Coach changes. In England, the level directly below professional football, Non-League Football (NLF), comprises full-time and part-time clubs. However, the running speed demands of professional teams at this level remain unknown. Therefore, this study aimed to investigate (1) the match running speed demands in a professional NLF team, and (2) the impact of changing the Head Coach on these physical demands. Match running speed data were collected via Polar Team Pro global positioning system (GPS) devices during 41 matches of a tier 6 NLF team, comprising 311 observations of 22 full-time outfield players. Linear mixed-effect models examined the relationship between running speed metrics and fixed effects of a Head Coach change (n = 3), player position, and match outcome, with match number as a random effect. The team average total distance (TD) was 10,479 ± 42 m, and high-speed running and sprinting were 431 ± 62 m and 99 ± 26 m, respectively. The results showed significant positional differences, with wide defenders and midfielders associated with a greater TD than central defenders and strikers. Moreover, a change in Head Coach was significantly associated with a reduced TD, and a similar downward trend was observed across other running speed metrics. The TD and positional differences observed are comparable with other football cohorts, yet HSR and sprinting distances were notably lower in professional NLF. The findings highlight NLF clubs’ challenges in transitioning to higher competitive levels and provide insights for performance and training. Further research is warranted to explore the influence of running speed demands, technical and tactical factors, and other determinants on success in NLF. Full article

Background: Iron deficiency is a prevalent issue among elite athletes, particularly in endurance-based sports like football, where optimal iron status is crucial for aerobic capacity and performance. Despite the well-documented role of iron in oxygen transport and energy metabolism, the interplay between genetic polymorphisms, biochemical markers, and iron supplementation remains poorly understood. This study aimed to investigate the relationship between genetic polymorphisms and iron status in professional football players, assess the impact of iron supplementation on athletic performance, and develop a predictive model for iron supplementation based on genetic and biochemical profiles. Methods: A longitudinal study was conducted over three seasons (2021–2024) with 48 male professional football players. Participants underwent genotyping for polymorphisms in ACE (rs4646994), ACTN3 (rs1815739), AMPD1 (rs17602729), CKM (rs8111989), HFE (rs1799945), and MLCK (rs2700352, rs28497577). Biochemical markers (ferritin, haemoglobin, haematocrit, serum iron) and performance metrics (GPS-derived data) were monitored. Iron supplementation (105 mg/day ferrous sulphate) was administered to players with ferritin <30 ng/mL. A Total Genotype Score (TGS) was calculated to evaluate genetic predisposition. Results: Players with “optimal” genotypes (ACE DD, ACTN3 CC, AMPD1 CC, HFE GC) required less iron supplementation (TGS = 51.25 vs. 41.32 a.u.; p = 0.013) and exhibited better performance metrics. Iron supplementation significantly improved haemoglobin and haematocrit in deficient players (p < 0.05). The TGS predicted supplementation need (AUC = 0.711; p = 0.023), with a threshold of 46.42 a.u. (OR = 5.23, 95% CI: 1.336–14.362; p = 0.017 for non-supplemented players). Furthermore, performance data revealed that iron-supplemented players had significantly lower competition time (1128.40 vs. 1972.84 min; p = 0.003), total distance covered (128,129.42 vs. 218,556.64 m; p = 0.005), and high-speed running in the 18–21 km/h (7.58 vs. 10.36 m/min; p = 0.007) and 21–24 km/h (4.43 vs. 6.13 m/min; p = 0.010) speed zones. They also started fewer matches (11.50 vs. 21.59; p < 0.001). Conclusions: Genetic profile combined with biochemical monitoring effectively predicts iron supplementation needs in athletes. Personalized nutrition strategies, guided by TGS, can optimize iron status and enhance performance in elite football players. This approach bridges a critical gap in sports science, offering a framework for precision nutrition in athletics. Full article

Elite football players face increasing physical and tactical demands due to rising match schedules emphasizing the need for effective load monitoring strategies to optimize performance and reduce injury risk. This study integrates fitness and fatigue indices derived from a machine learning approach to develop a performance score based on Banister’s fitness–fatigue model. Data were collected over two seasons (2022/23 and 2023/24) from 23 elite players of an Italian professional team. Fitness was assessed via heart rate collected during small-sided games, while fatigue was evaluated through PlayerLoad recorded during training sessions; both were normalized using z-scores. Match outcomes, including physical (e.g., total distance, high-sprint distance) and tactical metrics (e.g., field tilt, territorial domination), were analyzed in relation to performance conditions (optimal, intermediate, poor). Results revealed that players in the optimal performance condition exhibited significantly higher second-half physical outputs, including total distance (z-TD_2ndHalf: p < 0.05, ES = 0.29) and distance covered at >14.4 km/h (z-D14.4_2ndHalf: p < 0.01, ES = 0.52), alongside improved match tactical parameters as territorial domination (%TDO_2ndHalf: p < 0.01, r = 0.431). This study underscores the utility of invisible monitoring in football, providing actionable insights for weekly training periodization. This research establishes a foundation for integrating data-driven strategies to enhance physical and tactical performance in professional football. Full article