For almost 25 years, the goal of the RoboCup has been to build soccer robots capable of winning against the FIFA World Champion of 2050. To foster the participation of the next generation of roboticists, the RoboCupJunior competition takes place in parallel and provides a similar challenge of appropriate difficulty for high school students. RoboCupJunior has three main categories: Soccer, Rescue and OnStage. For the Soccer category, participants need to design, build and program a team of autonomous robots to play soccer against an opponent team of robots. The competition is physical in nature, since it assumes physical robots playing against one another. In 2020 and 2021, the COVID-19 pandemic has made it difficult for a competition of this type to take place, due to obvious restrictions on physical gatherings. To allow for some sort of participation, and inspired by positive experience of the larger RoboCup community, the Organizing Committee of RoboCupJunior Soccer has explored porting a portion of the challenge to a simulated environment. Many of the existing environments, however, are built for higher education/research teams competitions or research, making them complex to deploy and generally unsuitable for high school students. In this paper we present the development of SoccerSim, a simulated environment for RoboCupJunior Soccer, based on the Webots open-source robotics simulator. We also discuss how the participation of students was key for its development and present a summary of the competition rules. We further describe the case study of utilizing SoccerSim first as a testbed for a Demo competition, and later as part of RoboCup Worldwide 2021. The participation of more than 60 teams from over 20 countries suggests that SoccerSim provides an affordable alternative to physical robotics platforms, while being stable enough to support a diverse userbase. The experience of using SoccerSim at RoboCupJunior Worldwide 2021 suggests that a simulated environment significantly lowers the barrier to entry, as evidenced by the participation of many teams that have not participated before. To make it easy for similar competitions to take place in the future, we made the code of SoccerSim available as open-source, as well as the associated tooling required for using it in a tournament.
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Abstract: OBJECTIVE: To describe characteristics of outdoor soccer injury and recovery among Dutch soccer players.
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The use of robots as educational tools provides a stimulating environment for students. Some robotics competitions focus on primary and secondary school aged children, and serve as motivation for students to get involved in educational robotics activities. Although very appealing, many students cannot participate on robotics competitions because they cannot afford robotics kits. Hence, several students have no access to educational robotics, especially on developing countries. To minimize this problem and contribute to education equality, we have created RoSoS Robot Soccer Simulator, in which students program virtual robots in a similar way that they would program their real ones. In this chapter we explain some technical details of RoSoS and discuss the implementation of a new league for the robotics competitions: Junior Soccer Simulation league (JSS). Because soccer is the most popular sport in the world, we believe JSS will be a strong motivator for students to get involved with robotics.
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Talent development programmes for professional soccer clubs aim to guide players towards professional level performance. We identify whether the intermittent endurance capacity of these players may have changed over time. Since the 2000/2001 competition season, the intermittent endurance capacity of players in the talent development programmes of two professional soccer clubs was measured annually. A total of 492 players participated, divided across seven age categories (under 13 (U13), U14, U15, U16, U17, U18, U19) and resulting in 953 measurements. Analyses of variance showed an improvement in intermittent endurance capacity from the 2000/2001 season to 2009/2010 of around 50% in all age groups (P < 0.05). A possible explanation is the increased quantity and quality of training over the years. When identifying, developing and selecting young players, scouts, trainers and coaches have to be aware that the current level of soccer and its underlying performance characteristics--such as intermittent endurance capacity--are improving over time. This factor may have consequences for current young players aiming to make it to the top 10 years from now.
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The aim of the study was to investigate whether an increased risk of injury occurrence can be determined through frequent anthropometric measurements in elite-standard youth soccer players. Over the course of one season, we followed 101 male elite-standard youth soccer players between 11 and 19 years of age. Height and body mass were monitored at monthly measurement intervals and fat percentage was assessed every 3 months by use of the sum of skinfold method. Growth in height (cm), alternations in body mass index (kg/m(2)), fat percentage and fat-free mass index (kg/m(2)) were calculated. Injuries were recorded in accordance with the recommendations of the FIFA Consensus Model for Injury Registration. Odds ratio scores and 95% confidence intervals were calculated using binary logistic regression analyses. The following anthropometric injury risk factors were identified: ≥ 0.6 centimeter growth per month (p=0.03; OR=1.63; 95% CI: 1.06-2.52), ≥ 0.3 kg/m(2) increase of body mass index value per month (p=0.03; OR=1.61; 95% CI: 1.04-2.49) and low fat percentage; i. e., < 7% for players aged 11-16 and < 5% for players over 16 years (p=0.01; OR=1.81; 95% CI: 1.18-2.76). Individual monitoring of anthropometrics provides useful information to determine increased risk of injury occurrence in elite-standard youth soccer.
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PurposeYoung soccer players need excellent tactical skills to reach the top. Tactical behavior emerges through interactions between opposing teams. However, few studies have focused on on-field tactical behavior of teams with talented soccer players. Therefore, this study aimed to determine teams’ tactical behavior during small-sided games in two age categories, Under-17 and Under-19.MethodsPositional data of thirty-nine elite-standard soccer players were collected during twenty-four small-sided games to calculate longitudinal and lateral inter-team distances, stretch indices and length per width ratios. Corresponding interaction patterns and game-to-game variability were also determined.ResultsUnder-19 showed a significantly larger lateral stretch index and a significantly lower length per width ratio compared with Under-17. Furthermore, teams of both age groups showed similar large proportions of in-phase behavior. Variability of tactical performance measures within and between games was similar for Under-17 and Under-19.ConclusionsVariability within games seems to be functional for attacking teams for creating goal-scoring opportunities. In conclusion, the main difference was that Under-19 adopted a wider pitch dispersion than Under-17, represented by a larger lateral stretch index and smaller length per width ratio. Coach instructions and training exercises should be directed at exploiting pitch width to increase the pursuit of goal-scoring.
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This scoping review aimed to systematically explore the breadth and extent of the literature regarding the relationship between contextual factors (CFs) and training load (TL) in adolescent soccer players. Further aims included comprehending potential underlying mechanisms and identifying knowledge gaps. CFs were defined as factors not part of the main training process, such as the coach–athlete relationship and educational responsibilities. PubMed, EBSCO APA PsycINFO, Web of Science, ProQuest Dissertations & Theses A&I, and SportRxiv were searched. Studies involving adolescent soccer players that investigated the CF–TL relationship and measured TL indicators were deemed eligible. Seventeen studies were included, reflecting the limited number of articles published regarding the CF–TL relationship. CFs were mostly related to match-play (N = 13) and phase of the season (N = 7). Moreover, these factors appeared to affect TL. CF related to players’ personal environment (N = 3) were underrepresented in the reviewed studies. Overall, the CF–TL relationship appears to be rarely scrutinized. A likely cause for this lack of research is the segregation of the physiological and psychological research domains, where the CF–TL relationship is often speculated upon but not measured. Therefore, a holistic approach is warranted which also investigates the effect of personal environment, such as stressful life stress events, on TL.
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The purpose of this study was to identify differences in traumatic and overuse injury incidence between talented soccer players who differ in the timing of their adolescent growth spurt. 26 soccer players (mean age 11.9 ± 0.84 years) were followed longitudinally for 3 years around Peak Height Velocity, calculated according to the Maturity Offset Protocol. The group was divided into an earlier and later maturing group by median split. Injuries were registered following the FIFA consensus statement. Mann-Whitney tests showed that later maturing players had a significantly higher overuse injury incidence than their earlier maturing counterparts both in the year before Peak Height Velocity (3.53 vs.0.49 overuse injuries/1 000 h of exposure,U = 49.50, z = − 2.049, p < 0.05) and the year of Peak Height Velocity (3.97 vs. 1.56 overuse injuries/1 000 h of exposure, U = 50.5, z = − 1.796,p < 0.05). Trainers and coaches should be careful with the training and match load they put on talented soccer players, especially those physically not (yet) able to handle that load. Players appear to be especially susceptible to injury between 13.5 and 14.5 years of age. Training and match load should be structured relative to maturity such that athletic development is maximized and the risk of injury is minimized.
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Substitution is an essential tool for a coach to influence the match. Factors like the injury of a player, required tactical changes, or underperformance of a player initiates substitutions. This study aims to predict the physical performance of individual players in an early phase of the match to provide additional information to the coach for his decision on substitutions. Tracking data of individual players, except for goalkeepers, from 302 elite soccer matches of the Dutch ‘Eredivisie’ 2018–2019 season were used to enable the prediction of the individual physical performance. The players’ physical performance is expressed in the variables distance covered, distance in speed category, and energy expenditure in power category. The individualized normalized variables were used to build machine learning models that predict whether players will achieve 100%, 95%, or 90% of their average physical performance in a match. The tree-based algorithms Random Forest and Decision Tree were applied to build the models. A simple Naïve Bayes algorithm was used as the baseline model to support the superiority of the tree-based algorithms. The machine learning technique Random Forest combined with the variable energy expenditure in the power category was the most precise. The combination of Random Forest and energy expenditure in the power category resulted in precision in predicting performance and underperformance after 15 min in a match, and the values were 0.91, 0.88, and 0.92 for the thresholds 100%, 95%, and 90%, respectively. To conclude, it is possible to predict the physical performance of individual players in an early phase of the match. These findings offer opportunities to support coaches in making more informed decisions on player substitutions in elite soccer.
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The aim of this study was to prospectively monitor sport-specific performance and assess the stress-recovery balance in overreached (OR) soccer players and controls. During two competitive seasons, 94 players participated in the study. The stress-recovery balance (RESTQ-Sport) and sport-specific performance (Interval Shuttle Run Test) were assessed monthly. Seven players with performance decrement of at least a month were classified as OR. Stress and recovery measures were assessed between groups (OR vs healthy players) and at different times within the OR group. An unfavorable total recovery score appeared 2 months before diagnosis when compared with the reference values of the healthy group established at the start of the season (P=0.009) and also over the two seasons (P=0.028). The scales Emotional Stress (P=0.044), Physical Recovery (P=0.009), General Well-being (P=0.001) and Sleep Quality (P=0.045) were sensitive to OR compared with the average of the healthy group over the two seasons. Finally, Fatigue and Being in Shape demonstrated the largest changes in stress and recovery within the OR players (effect size=1.14 and 1.50). The longitudinal monitoring of performance and changes in stress and recovery may be useful for the detection of OR in its earliest stage. The information obtained from these tests can be used to optimize individual training and recovery programs.
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