This study investigates the relationship between gender and self-concept among high school students enrolled in sports-oriented programs. In addition, it examines the interconnections among self-concept, motivation, and the satisfaction of basic psychological needs. The sample comprises 215 high school students aged 16 to 18 years. Three standardized instruments were employed: the brief version of the Five-Factor Self-Concept Questionnaire, the Basic Psychological Needs in Exercise Scale, and the Sport Motivation Scale (SMS-II). Statistical analyses were conducted using IBM SPSS (version 28.0) and AMOS (version 29). As anticipated, no significant differences emerged in overall self-concept between male and female students, a finding consistent with prior research. However, a significant positive association was observed between gender and emotional self-concept, with female students scoring higher than their male counterparts. Regarding the relationship between self-concept and motivation, academic self-concept demonstrated a significant positive association with intrinsic motivation and a negative correlation with amotivation. Furthermore, academic self-concept was positively related to the basic psychological needs of autonomy, competence, and relatedness, with autonomy showing the strongest link. The study highlights the complex interplay among gender, self-concept, motivational orientations, and psychological needs. Emotional self-concept was positively correlated with less autonomous forms of motivation—introjected regulation, external regulation, and amotivation—suggesting a potential connection between emotional sensitivity and motivational vulnerability. Family self-concept emerged as a strong predictor of autonomous motivation, while social self-concept was significantly associated with the need for relatedness. In summary, the findings underscore the complex and multidimensional nature of self-concept and its significant implications for motivational processes.
Sports are one of the most significant products of the entertainment industry, accounting for a large portion of all television (and even platform) viewing. Consequently, the sale of broadcasting and media rights is the most important source of revenue for professional sports clubs. We survey the economic literature dealing with this issue, with a special emphasis on the crucial problem that arises with the allocation of revenues when they are raised from the collective sale of broadcasting rights.
Large Language Models (LLMs) have been shown to be biased in prior work, as they generate text that is in line with stereotypical views of the world or that is not representative of the viewpoints and values of historically marginalized demographic groups. In this work, we propose using data from parallel men's and women's events at the Olympic Games to investigate different forms of gender bias in language models. We define three metrics to measure bias, and find that models are consistently biased against women when the gender is ambiguous in the prompt. In this case, the model frequently retrieves only the results of the men's event with or without acknowledging them as such, revealing pervasive gender bias in LLMs in the context of athletics.
In many real-world complex systems, the behavior can be observed as a collection of discrete events generated by multiple interacting agents. Analyzing the dynamics of these multi-agent systems, especially team sports, often relies on understanding the movement and interactions of individual agents. However, while providing valuable snapshots, event-based positional data typically lacks the continuous temporal information needed to directly calculate crucial properties such as velocity. This absence severely limits the depth of dynamic analysis, preventing a comprehensive understanding of individual agent behaviors and emergent team strategies. To address this challenge, we propose a new method to simultaneously complete the velocity of all agents using only the event-based positional data from team sports. Based on this completed velocity information, we investigate the applicability of existing team sports analysis and evaluation methods. Experiments using soccer event data demonstrate that neural network-based approaches outperformed rule-based methods regarding velocity completion error, considering the underlying temporal dependencies and graph structure of player-to-player or player-to-ball interaction. Moreover, the space evaluation results obtained using the completed velocity are closer to those derived from complete tracking data, highlighting our method's potential for enhanced team sports system analysis.
The impact evaluation of female sports events remains an important yet neglected area of research. To fill this gap, this working paper provides a timely assessment of the 2025 UEFA Women's European Championship (WEURO) in Switzerland-the largest women-specific sports event in Europe with more than 657,000 spectators. Using city-level data on hotel overnight stays, we apply the Synthetic Difference-in-Differences approach of Arkhangelsky et al. (2021) to compare WEURO host cities with non-host destinations. In summary, our results do not support strong claims of large tourism impacts but rather point to a small positive effect. Sensitivity analyses also suggest positive effects. However, confidence intervals permit firm conclusions only for the main venues, indicating an increase in overnight stays of 1.6% attributable to the WEURO. Overall, our findings indicate positive but modest tourism impacts of the WEURO and outline a framework for further policy evaluation of sports events.
Field detection in team sports is an essential task in sports video analysis. However, collecting large-scale and diverse real-world datasets for training detection models is often cost and time-consuming. Synthetic datasets, which allow controlled variability in lighting, textures, and camera angles, will be a promising alternative for addressing these problems. This study addresses the challenges of high costs and difficulties in collecting real-world datasets by investigating the effectiveness of pretraining models using synthetic datasets. In this paper, we propose the effectiveness of using a synthetic dataset (SoccerSynth-Field) for soccer field detection. A synthetic soccer field dataset was created to pretrain models, and the performance of these models was compared with models trained on real-world datasets. The results demonstrate that models pretrained on the synthetic dataset exhibit superior performance in detecting soccer fields. This highlights the effectiveness of synthetic data in enhancing model robustness and accuracy, offering a cost-effective and scalable solution for advancing detection tasks in sports field detection.
Behdad Sadeghi, Rahmatollah Gholipour, Mojtaba Amiri
et al.
Objective
This study was conducted with the goal of designing a policy-making model for sports in Iran, with a focus on the development of 'sport for all'. In terms of purpose, this study is classified as applied research, as it encompasses practical aspects for various organizations related to sports and health, in addition to providing awareness and scientific insights. Furthermore, this research is exploratory in nature, as it aims to design a model on a novel and innovative topic.
Methods
A mixed qualitative-quantitative method was employed in this study. The qualitative component was conducted using a situation analysis approach, which is one of the methods of grounded theory. The qualitative research involved interviewing experts; thus, 12 experts in the fields of policy making and sport management were interviewed. These experts were either professors or managers of organizations related to sports, possessing over a decade of executive and decision-making experience. Sampling was carried out using targeted and snowball methods. The quantitative section utilized interpretative structural modeling, an approach based on expert opinions, effective for exploring qualitative variables with mutual effects at various levels of importance.
Results
After an in-depth examination of the interviews and the data obtained, each interview was analyzed individually to extract initial codes. Subsequently, concepts and categories were developed. Messy situational maps, ordered situational maps, and social worlds/arenas maps were identified. The primary categories of the sport policy-making model in Iran for the development of 'sport for all' include contextual factors, mediating factors, role players and influential institutions, executive requirements, environmental complexities, risks, legal problems, external organizational factors, costs and expenses, and interorganizational challenges. With the aid of interpretive structural modeling, conceptual modeling was conducted. Role players and influential institutions emerged as the most significant factors in Iran's sport policy-making process, possessing the highest influence and the least dependence compared to other factors.
Conclusion
Given that 'sport for all' should be elevated to the level of the country's macro policies, and its development and progress should be approached as a complex issue, the policy for the development of 'sport for all' becomes especially important. Policymakers should give it significant attention. Role players and influential institutions in Iran's sports policy-making process require substantial coordination due to their numerous connections and conflicts. In Iran, 'sport for all' and organized recreation have received limited attention, and currently, there is no mechanism for monitoring sports policies and their continuous implementation. Therefore, it is recommended to implement a national physical activity monitoring plan based on a comprehensive and electronic system. Since the involvement of managers and executives, as well as their cooperation with policymakers in the policy formation process, is crucial, policymakers should be as involved as possible in the implementation process. Additionally, conditions should be facilitated to enable the private sector to effectively engage in this field.
Political institutions and public administration (General)
It has long been stated that children have the rights to protection from, e.g., abuse and to the provision of age-appropriate leisure, play, and recreational activities along with participation in all matters that concerns them. Yet, the full range of children’s rights to and in sport has not yet been explored in detail. To do so, it is relevant to turn to the Scandinavian countries, which are praised for promoting children’s rights and well-being, with organized sport forming part of the daily lives of many children and youths. In this paper, we examine the organizational policies in Scandinavian sport in order to develop foundational knowledge about how the range of children’s rights to and in sport may be supported. Comparing key policy documents of the major sports confederations in Denmark, Norway, and Sweden, these analyses identify great variety in the following: 1. when and how children’s rights to and in sport have been made explicit in the three countries; 2. whether the emphasis is on protection and/or provision of sport to children and youths or their participation in shaping sporting activities; 3. the degree to and ways in which such rights are regulated. In sum, our findings reflect a disparity between organizational policies in the three countries, with a more liberal and individualistic approach to public policy in the Danish context, providing some explanation of the only recent development in and scattered enaction of regulations to support children’s rights to and in sports. Furthermore, we identify that political attention has mainly been drawn to the protection and provision of sports to children and youths, while their participation in shaping sport is a shared challenge for sport confederations in the Scandinavian countries and beyond.
Yahya Süleyman Mollaibrahimoğlu, Nurefşan Kaygas, Özlem Feyzioğlu
et al.
The study aims to compare static and dynamic postural stability, navicular drop, dorsiflexion range of motion, and jumping performance of individuals with neutral, prone, and hyperprone foot postures. Forty-eight participants between the ages of 18 and 40, were categorized into neutral (n=16), prone (n=16), and hyperprone (n=16) according to foot posture index (FPI). Static and dynamic postural control evaluations (with the Biodex Balance System SD), navicular drop test (NDT) weight-bearing lunge test, countermovement jump test without arm swing, and drop vertical jump tests have been completed. In the results, the average age of participants in the NG, PG, and HPG are 22.31 ± 2.75, 23.87± 3.72, and 22.37 ± 1.28 years and BMI are 22.6 ± 3, 23.4 ± 3.8, and 21.4 ± 2.24 (kg/m²), respectively. The demographic data of the participants showed a homogeneous distribution. There were no significant differences in none of the outcomes except the NDT. Navicular drop amount is positively correlated by the subtalar joint pronation. An increase in subtalar joint pronation does not have a significant effect on static and dynamic stability, jump performance, or dorsiflexion range of motion in healthy individuals.
Blinov V. Dmitry, Antonina G. Solopova, Elena V. Gameeva
et al.
Introduction. Surgical treatment of vulvar cancer (VC) entails mental and somatic disturbances due to pain, body image changes, and sexual dysfunction, which are closely associated with impaired social functioning and reduced overall quality of life. However, the results evaluating the impact of rehabilitation programmes on various components of quality of life in these patients remain limited.
Aim. to evaluate the effectiveness of rehabilitation programs in relation to the psycho-emotional sphere during 36 months following surgical treatment of early-stage VC.
Materials and methods. The randomized controlled study included female patients with VC, divided into two parallel groups of those who received a personalized program of comprehensive rehabilitation (VC-1) and rehabilitation according to the general principles regulated in the national clinical guidelines (VC-2). 36 patients each were randomly assigned to VC-1 and VC-2 groups. The control group included 80 women without female cancer. The VC-2 group was recommended physical activity, psychological support, and anti-edema therapy for lymphostasis. The personalized rehabilitation program in the VC-1 group additionally included lifestyle modification, cognitive-behavioral therapy, intimate hygiene training, magnesium, vitamin B6 and folic acid supplementation, correction of sexual disorders, phytotherapy and physiotherapy from the 3rd month, and climatotherapy and landscape therapy from the 6th month. The “Well-being, Activity, Mood” (WAM) questionnaire was administered at the preoperative visit, 1 week, 1, 3, 6, 12, 24 and 36 months after surgery. Scores were presented as Me [Q25; Q75], differences were considered significant at p 0.05.
Results. In the control group, scores on all WAM domains were within normal values throughout the study. In the 1st week after the surgery, well-being and activity decreased to unfavorable values in both VC-1 and VC-2 groups. Mood, however, showed significant positive dynamics compared to baseline. Subsequently, the improvement in the WAM domains was significantly faster and more pronounced in the VC-1 group than in the VC-2 group, reaching the range of favorable values by the 12th month, but not reaching the control group.
Conclusion. The personalized comprehensive rehabilitation program showed efficacy on well-being, activity and mood on the WAM questionnaire compared to basic rehabilitation. However, rehabilitation measures should be continued one year after surgery.
Combining sports and machine learning involves leveraging ML algorithms and techniques to extract insight from sports-related data such as player statistics, game footage, and other relevant information. However, datasets related to figure skating in the literature focus primarily on element classification and are currently unavailable or exhibit only limited access, which greatly raise the entry barrier to developing visual sports technology for it. Moreover, when using such data to help athletes improve their skills, we find they are very coarse-grained: they work for learning what an element is, but they are poorly suited to learning whether the element is good or bad. Here we propose air time detection, a novel motion analysis task, the goal of which is to accurately detect the duration of the air time of a jump. We present YourSkatingCoach, a large, novel figure skating dataset which contains 454 videos of jump elements, the detected skater skeletons in each video, along with the gold labels of the start and ending frames of each jump, together as a video benchmark for figure skating. In addition, although this type of task is often viewed as classification, we cast it as a sequential labeling problem and propose a Transformer-based model to calculate the duration. Experimental results show that the proposed model yields a favorable results for a strong baseline. To further verify the generalizability of the fine-grained labels, we apply the same process to other sports as cross-sports tasks but for coarse-grained task action classification. Here we fine-tune the classification to demonstrate that figure skating, as it contains the essential body movements, constitutes a strong foundation for adaptation to other sports.
Biathlon is a unique winter sport that combines precision rifle marksmanship with the endurance demands of cross-country skiing. We develop a Bayesian hierarchical model to predict and understand shooting performance using data from the 2021/22 Women's World Cup season. The model captures athlete-specific, position-specific, race-type, and stage-dependent effects, providing a comprehensive view of shooting accuracy variability. By incorporating dynamic components, we reveal how performance evolves over the season, with model validation showing strong predictive ability at both overall and individual levels. Our findings highlight substantial athlete-specific differences and underscore the value of personalized performance analysis for optimizing coaching strategies. This work demonstrates the potential of advanced Bayesian modeling in sports analytics, paving the way for future research in biathlon and similar sports requiring the integration of technical and endurance skills.
Yung-Hui Lin, Yu-Wen Chang, Huang-Chia Shih
et al.
Jersey number recognition (JNR) has always been an important task in sports analytics. Improving recognition accuracy remains an ongoing challenge because images are subject to blurring, occlusion, deformity, and low resolution. Recent research has addressed these problems using number localization and optical character recognition. Some approaches apply player identification schemes to image sequences, ignoring the impact of human body rotation angles on jersey digit identification. Accurately predicting the number of jersey digits by using a multi-task scheme to recognize each individual digit enables more robust results. Based on the above considerations, this paper proposes a multi-task learning method called the angle-digit refine scheme (ADRS), which combines human body orientation angles and digit number clues to recognize athletic jersey numbers. Based on our experimental results, our approach increases inference information, significantly improving prediction accuracy. Compared to state-of-the-art methods, which can only handle a single type of sport, the proposed method produces a more diverse and practical JNR application. The incorporation of diverse types of team sports such as soccer, football, basketball, volleyball, and baseball into our dataset contributes greatly to generalized JNR in sports analytics. Our accuracy achieves 64.07% on Top-1 and 89.97% on Top-2, with corresponding F1 scores of 67.46% and 90.64%, respectively.
Robert C Manske, Michael Voight, Chris Wolfe
et al.
Quadriceps muscle injury is a common occurrence, especially among athletes. While a careful history and a thorough physical examination are important steps in the assessment of quadriceps muscle pathology, it is still difficult to differentiate the type and severity of the pathology. Because of this difficulty, musculoskeletal ultrasound (MSK-US) is an invaluable tool in the diagnosis of quadriceps muscle or tendon injury. Utilizing this noninvasive imaging technique, medical professionals can easily diagnose and monitor muscle and tendon disorders to quickly determine the correct treatment plan for each individual case. The ability to view these structures in real-time allows identification of any present pathologies. MSK-US has become a useful component in diagnosing quadriceps muscle and tendon injuries due to its ability to clearly display the affected structures without exposing the patient to radiation or utilizing ionized contrast media. MSK-US provides valuable insight into fluid dynamics around joints and can even detect myotendinous tears that might otherwise be overlooked with the clinical examination or symptoms usually reported by patients. MSK-US can provide precise visualization of edema and can easily distinguish between benign and potentially pathological findings which make it an integral part of any holistic evaluation of quadriceps muscle and tendon injury. Additionally, it can be used to track the progress of physical therapy treatments and monitor tissue healing. This information is invaluable in ensuring an optimal outcome for any quadriceps muscle and tendon injury. Therefore, when used in combination with clinical tests, MSK-US can drastically increase the accuracy of the clinical examination. By utilizing this technology, healthcare practitioners have reliable access to more comprehensive diagnostics for musculoskeletal injuries and diseases than ever before. Clinicians are then able to tailor rehabilitation plans more effectively and ensure their patients receive proper treatment. As a result, recovery times may be shortened, and patients are able to return to their normal activities more quickly.
Sports professionals constantly under pressure to perform at the highest level can benefit from sports analysis, which allows coaches and players to reduce manual efforts and systematically evaluate their performance using automated tools. This research aims to advance sports analysis in badminton, systematically detecting hit-frames automatically from match videos using modern deep learning techniques. The data included in hit-frames can subsequently be utilized to synthesize players' strokes and on-court movement, as well as for other downstream applications such as analyzing training tasks and competition strategy. The proposed approach in this study comprises several automated procedures like rally-wise video trimming, player and court keypoints detection, shuttlecock flying direction prediction, and hit-frame detection. In the study, we achieved 99% accuracy on shot angle recognition for video trimming, over 92% accuracy for applying player keypoints sequences on shuttlecock flying direction prediction, and reported the evaluation results of rally-wise video trimming and hit-frame detection.
Patterns of wins and losses in pairwise contests, such as occur in sports and games, consumer research and paired comparison studies, and human and animal social hierarchies, are commonly analyzed using probabilistic models that allow one to quantify the strength of competitors or predict the outcome of future contests. Here we generalize this approach to incorporate two additional features: an element of randomness or luck that leads to upset wins, and a "depth of competition" variable that measures the complexity of a game or hierarchy. Fitting the resulting model to a large collection of data sets we estimate depth and luck in a range of games, sports, and social situations. In general, we find that social competition tends to be "deep," meaning it has a pronounced hierarchy with many distinct levels, but also that there is often a nonzero chance of an upset victory, meaning that dominance challenges can be won even by significant underdogs. Competition in sports and games, by contrast, tends to be shallow and in most cases there is little evidence of upset wins, beyond those already implied by the shallowness of the hierarchy.
Melese Yeshambaw Teferi, Ziad El-Khatib, Endawoke Amsalu Alemayehu
et al.
Typhoid fever continues to be a health challenge in low-and middle-income countries where access to clean water and sanitation infrastructure is scarce. The non-confirmatory diagnostic method continues to hinder effective diagnosis and treatment, ensuring in a high antimicrobial resistance. This systematic review and meta-analysis aimed to estimate the pooled prevalence and antimicrobial susceptibility level of typhoid fever in Ethiopia.The review was designed based on the condition-context-population review approach. Fifteen eligible articles were identified from PubMed, Google Scholar, and Science Direct databases. Risk of bias and quality of studies were assessed using the Joanna Briggs Institute’s appraisal criteria. Heterogeneity was assessed using Cochran’s Q test and I2 statistics. The review protocol was registered in PROSPERO (registration number CRD42021224478).The estimated pooled prevalence of typhoid fever from blood and stool culture diagnosis was 3% (95% CI: 2%–4%, p < 0.01) (I2 = 82.25) and Widal test examination 33% (95% CI: 22%–44%) (I2 = 99.14). The sub-group analyses identified a lower detection of typhoid fever of 2% (95% CI: 1%–3%) among febrile patients compared to typhoid suspected cases of 6% (95% CI: 2%–9%). The stool culture test identified was twofold higher, value of 4% (95% CI: 2%-7%) salmonella S. Typhi infection than blood culture test of 2% (95% CI: 1%–4%). The antimicrobial susceptibility of salmonella S. Typhi for antibiotics was 94%, 80% and 65% for ceftriaxone, ciprofloxacin, and gentamycin respectively. Low susceptibility of salmonella S. Typhi isolates against nalidixic acid 22% (95% CI: 2%–46%) and chloramphenicol 11% (95% CI: 2%–20%) were observed. The diagnosis of typhoid fever was under or overestimated depending on the diagnostic modality. The Widal test which identified as nonreliable has long been used in Ethiopia for the diagnosis of salmonella S. Typhi causing high diagnosis uncertainties. Antimicrobial susceptibility of salmonella S. Typhi was low for most nationally recommended antibiotics. Ethiopian Food and Drug Authority must strengthen its continued monitoring and enhanced national antimicrobial surveillance system using the best available state-of-the-art technology and or tools to inform the rising resistance of salmonella S. Typhi towards the prescription of standard antibiotics. Finally, it is crucial to develop an evidence-based clinical decision-making support system for the diagnosis, empiric treatment and prevention of antimicrobial resistance.
Purpose: One of the changes that occurs in the vascular structure of skeletal muscle during exercise to resolving stress is the process of angiogenesis that has been considered by researchers. Thus, the aim of this study was to investigate the effect of 6-week resistance training with different Time under Tension (TUT) on some serum vascular growth factors in inactive girls.Methods: 20 female volunteer students (mean age 22.3 yrs) were randomly and equally divided into two groups with different TUT of (1s – 1s) and (2s – 4s). Resistance training was performed for 6-week, three times per week, in eight stations,three sets, the intensity of 75% 1RM (10 repetitions) and 50% 1RM (5 repetitions) to equalize the training load in two groups. Blood samples were taken from the subjects before the training period and 48 hours after the last training session to evaluate the variables of VEGF, GH and endostatin. Data were analyzed by analysis of covariance.Results: There were no significant differences in serum levels of VEGF (P = 0.59) and GH (P = 0.89) between groups following six weeks of resistance training. But there were significant differences in serum endostatin level (P = 0.04) and leg strength (P = 0.01) between the two groups. Conclusion: Although there was no significant difference in angiogenesis related-factors between the two groups during six weeks and it is likely to need more time, but in the case of angiogenesis inhibitor, this difference was significant. Also, the more eccentric component was more associated with more strength in the 2s – 4s training.