The aims of the current study were to analyze the evolution of players’ age in the UEFA Champions League since the start of its modern-day format in 1992–1993 up until 2017–2018 and to determine how the players’ age relates to their market value. The sample consisted of all players participating in the UEFA Champions League from the 1992–1993 to 2017–2018 seasons (n = 16062). The following variables were used in this study: players’ age, number of seasons in the club, number of Champions Leagues won, team performance, and market value of the player in the season. Data were examined using a one-way ANOVA and a linear regression. The main finding of the current study is that an aging trend has occurred in the last three decades in the Champions League. A significant increase in average players’ age (>1.6 years) was observed, rising from an age of 24.9 to 26.5 years. Goalkeepers and Center Backs tend to peak later than attackers, and their peak performance can last until an age of about 31 years. Finally, an inverted-U curve defines the association between market value and age, with peak value appearing in the 26–30 age range. These results provide useful information regarding at which age soccer players are likely to perform at the highest level, as well as the age they are likely to have the highest market value.

The aim of this study was to assess the effect of core strength training performed on a stable surface (CTS) compared with core strength training performed on an unstable surface (CTU) on physical fitness (jump performance, sprint, and repeated sprint ability (RSA)) and quality of movement (Fundamental Movement Screen) in professional female futsal players. Fourteen professional female futsal players (mean age: 23.7 ± 5.1 years, age range: 18-28 years) were randomly assigned to a CTS (n = 7) or a CTU (n = 7) group. The intervention program was carried out 3 times a week over 6 weeks. Players of both groups performed the same four core-strengthening exercises. The only difference between the two interventions was that the CTU group performed all exercises (i.e., shoulder bridge, side bridge, prone plank, and crunch) on an unstable surface (Togu® Dyn-Air). Within-group analysis showed significant improvements (p < 0.001) in 10 m sprint performance from the pre- to post-test in the CTS (+4.37%) and CTU (+5.00%) groups. Players in both the CTS (+10.39%) and CTU (+11.10%) group also showed significant enhancement in the Functional Movement Screen total score, from the pre-test to post-test. In addition, a significant time effect was also observed for the CTU group in the relative score of the RSA test decreasing from the pre- to post-test (-30.85%). In the between-groups analysis, there were no significant differences between the core strength training groups (CTS vs CTU) in any variable. To conclude, sprint and Functional Movement Screen performance improved following CTS and CTU when conducted in combination with regular futsal training. In addition, CTU had limited benefit in RSA compared to CTS.

Rey, E, Costa, PB, Corredoira, FJ, and Sal de Rellán Guerra, A. Effects of age on physical match performance in professional soccer players. J Strength Cond Res 37(6): 1244–1249, 2023—This study aimed to evaluate the effects of age using a large-scale analysis of match physical performance in professional soccer players. A total of 10,739 individual match observations were undertaken on outfield players competing in the first and second divisions of the Spanish soccer professional leagues during the 2017–2018 season, using a computerized tracking system (TRACAB, Chyronhego, New York, NY). The players were classified into five positions and into 5 age groups (<20 years, 20–24.9 years, 25–29.9 years, 30–34.9 years, and ≥35 years). The results showed that (a) professional soccer players aged ≥30 years exhibit a significant decrease (p < 0.01) in the total distance covered, medium-speed running distance, high-speed running (HSR) distance, very HSR (VHSR) distance, sprint distance, and maximum running speed compared with younger players (<30 years); (b) professional soccer players aged ≥35 years exhibit a significant decrease (p < 0.01) in the number of HSR, number of VHSR, and number of sprints compared with younger players (<35 years); and (c) all playing positions reduced their physical performance; however, external midfielders were less affected by age effects. In conclusion, this study demonstrates players' physical match performance reduces with increasing age. Such findings may help coaches and managers to better understand the effects of age on match-related physical performance and may have the potential to assist in decisions regarding recruitment and player list management within professional soccer clubs.

Introduction: Physical Education plays a crucial role in adolescent health, but motivation remains a challenge as participation declines during this stage. Gamification, which integrates game elements into learning, has gained attention as a methodology to enhance it. However, its effectiveness in Physical Education requires further exploration.Methods: This systematic review followed PRISMA guidelines. A search was conducted in Dialnet, PubMed, ERIC, Scopus, and Web of Science for studies published between 2015 and January 2025. Research focusing on gamification and motivation in secondary and high school Physical Education was selected based on predefined criteria. The methodological quality was assessed using the PEDro scale.Results: A total of 19 studies met the inclusion criteria. The findings indicate that gamification enhances motivation in Physical Education, whether applied independently or combined with other methodologies. Additional benefits include improved autonomy, social skills, and classroom atmosphere. However, its impact on academic performance and motor skill development remains inconclusive. One study reported potential drawbacks when gamification neglects affective-motivational skills.Discussion: Gamification appears to be an effective tool for increasing motivation in Physical Education. However, methodological inconsistencies limit the generalizability of results. Future research should include control groups, clearer methodologies, and long-term evaluations to assess its sustained impact.

Background: Anthropometric measures such as the body mass index (BMI), reciprocal ponderal index (RPI), and waist-to-height ratio (WHR) have been proposed as predictors of physical fitness. This study aimed to identify the differences in explanatory capacity and fit of BMI, RPI, and WHR on physical fitness, which involves jumping, sprinting, change of direction, and aerobic capacity, by adjusting the polynomial regression.Methods: A sample of 297 healthy, recreationally active male university students between 18 and 20 years old was recruited for this study. Anthropometric measurements (height: 174.09 ± 6.27 cm, weight: 78.98 ± 20.27 kg, waist circumference: 93.74 ± 14.56 cm) were taken for each participant. Jumping tests (squat jump, countermovement jump), sprinting tests (20 m sprint), agility tests (agility T-test), and aerobic/endurance tests (6 min walk test, VAM-EVAL test) were performed. Nonlinear quadratic regression models were used to assess the relationship between the jump, sprint, and fitness test scores and the anthropometric indices. The models were compared based on R-squares and Bayesian Information Criterion (BIC). The significance level was set at p < 0.05.Results: The results showed that all the indices predicted a portion of the variance because all variables and index relationships were significant. Regarding the fitted models, the Bayesian Information Criterion showed that BMI was the best indicator of performance, although the RPI was better for VO_2max.Conclusion: These findings may be of great interest to practitioners because it appears that anthropometric measures can be used to predict physical fitness in certain tests although the accuracy raises any concerns.