Correlating anthropometric parameters with lower limb muscle strength: on the example of female volleyball players

Purpose: This study aimed to investigate the relationship between anthropometric parameters, strength of the muscles of the lower limbs, and jump height among women volleyball players, with a focus on anthropometric parameters. Material and methods: Thirty-two university-level women volleyball players aged 18 to 25 years participated in the study. Height, weight, arm span, body mass index (BMI), and lower limb muscle strength were measured using standard anthropometric techniques and specialized equipment. Regression modeling and Pearson correlation analysis were employed to examine the associations between anthropometric parameters and lower limb muscle strength. Results: The regression analysis revealed significant associations between weight and BMI with lower limb muscle strength, indicating a positive relationship with weight and a negative relationship with BMI. However, height and arm span did not show significant correlations with lower limb muscle strength. Pearson correlation analysis confirmed strong positive correlations between height, weight, arm span, and lower limb muscle strength. Conclusions: This study challenges the conventional emphasis on height alone in assessing athletic performance in women's volleyball. It highlights the significant roles played by weight and BMI in predicting lower limb muscle strength and jump height, suggesting that players with greater body mass tend to achieve greater vertical displacement during jumps. These findings underscore the importance of considering a holistic array of anthropometric parameters, lower limb muscle strength, in talent identification and training program design in women's volleybal

Protein supplementation on muscle recovery and soreness after intense badminton training sessions

Purpose. This study aimed to investigate the impact of protein supplementation on muscle recovery and delayed-onset muscle soreness (DOMS) in male badminton players following intense training sessions. Materials and Methods. Thirty-six male badminton players, aged 18 to 25, were randomly divided into three groups: a high-protein group (1.6 g/kg body weight), a moderate-protein group (0.8 g/kg body weight), and a placebo group. Participants consumed their respective supplements within 30 minutes after each training session over a six-week period. Muscle soreness was assessed using the Visual Analog Scale (VAS) at 24, 48 and 72 hours post-exercise, and recovery was measured through the Perceived Recovery Status (PRS) scale. Statistical analyses, including two-way ANOVA, were performed to assess the effects of protein supplementation and the recovery time on muscle soreness and recovery. Results. The high-protein group showed significantly faster recovery and reduced muscle soreness than the moderate-protein and placebo groups (p < 0.001). Furthermore, regression analysis indicated a strong negative correlation between protein intake and muscle soreness, highlighting the benefit of higher protein levels in improving recovery. Conclusions. Protein supplementation, especially at a higher dose of 1.6 g/kg body weight, significantly aided in muscle recovery and reduced muscle soreness in male badminton players. This suggests that adequate protein intake is key to enhancing recovery and performance in sports that require quick bursts of intense activity

Efficacy of Resistance Band Training on Shoulder Muscle Strength and Injury Prevention in Volleyball Athletes

Purpose: Shoulder injuries are common in women volleyball players, often resulting from repetitive overhead movements. Effective strength training methods can help prevent these injuries. This study aimed to investigate the efficacy of an eight-week resistance band training program on shoulder muscle strength enhancement and injury prevention in women volleyball athletes. Material and Methods. Forty collegiate women volleyball players, aged 18-25, were randomly assigned to either an intervention group (n=20) or a control group (n=20). The intervention group underwent a structured resistance band training program targeting shoulder strength, which included exercises like shoulder presses, lateral raises, internal and external rotations, and scapular retractions. Isokinetic dynamometry was used to assess shoulder muscle strength before and after the intervention, measuring peak torque of the shoulder flexors, extensors, internal rotators, and external rotators. Injury rates were monitored throughout the volleyball season, documenting the number and severity of shoulder injuries. Results. Significant improvements in shoulder muscle strength were observed in the intervention group across all measured parameters (p 0.05). Moreover, the intervention group exhibited a significant reduction in shoulder injury rates post-intervention (p = 0.041), whereas the control group's injury rates remained stable (p = 0.768). Conclusions. The findings suggest that resistance band training effectively enhances shoulder muscle strength and reduces injury rates in women volleyball athletes. Integrating targeted strength training, such as resistance band exercises, into regular training routines may help enhance athlete performance and mitigate injury risk in sports characterized by repetitive overhead movements. Further research is needed to explore the long-term effects and optimal implementation strategies of resistance band training in athletic contexts

Effect of cardiovascular fitness on performance metrics in Bangladeshi women cricket: a role-specific analysis employing the harvard step test

Background: Cardiovascular fitness is essential for sports performance, enabling players to endure intense training, delay fatigue, and reduce injury risk—all critical factors for achieving optimal results in competitive sports like cricket. Emphasizing inclusive health ensures that all athletes enhance their cardiovascular fitness and overall performance. Purpose: This study aimed to investigate the impact of cardiovascular fitness, assessed using the Harvard Step Test, on the performance indicators of Bangladeshi women cricketers across their respective playing roles. Method: 104 players, including 34 batters, 38 bowlers, and 32 all-rounders, were voluntarily selected from the “Bangladesh National Women’s Cricket League 2021-22”. Cardiovascular fitness was evaluated through the Harvard Step Test, and role-specific performance metrics such as strike rate, bowling economy, and dismissal rates were analyzed. Statistical analyses included descriptive statistics and one-way ANOVA to assess differences in aerobic fitness across player roles and correlation analyses to examine the relationships between performance metrics and Harvard Step Test scores. Results: The multi-group comparison did not reveal a statistically significant difference in aerobic fitness across the playing roles, F(2, 101) = 0.668, p = 0.515. Additionally, the Harvard Step Test scores showed a weak and statistically non-significant relationship with role-specific performance metrics: strike rate (r = 0.20, p = 0.06) for batters, bowling economy (r = -0.09, p = 0.51) for bowlers, and dismissals (r = 0.10, p = 0.38) for fielders. Conclusion: Cardiovascular efficiency is similar across batters, bowlers, and all-rounders among Bangladeshi women cricketers. The Harvard Step Test score is not directly associated with role-specific performance in women's cricket. These findings suggest that training programs should adopt a holistic physical fitness approach, incorporating role-specific training to enhance the overall abilities of female cricketers and contribute to the development of women's cricket in Bangladesh

The role of football video games in boosting cognitive abilities critical to football performance

Background and Aim: Football requires rapid decision-making and quick reaction times, crucial cognitive abilities that traditionally develop through physical training. This study explores whether football video games, which simulate real game scenarios, can enhance these cognitive abilities among college-level male football players. Materials and Methods: The study involved 51 football players from SRM Group of Institutions, divided into three groups: regular video game players (Group A), occasional players (Group B), and non-players (Group C). A mixed-methods approach was used, combining quantitative cognitive abilities tests (decision-making, reaction time, situational awareness). The video game used in the study was eFootball 2024 with participants engaging in gameplay over a period of 6 weeks. Tests were conducted before and after a set period of video game engagement. Data were analyzed using mixed-design ANOVA and Pearson’s correlation. Results: Significant improvements were observed in Group A across all cognitive abilities tested. Decision-making showed notable group and time effects (F (2, 48) = 5.76, p = 0.005, η² = 0.17; F (1, 48) = 12.54, p < 0.001, η² = 0.25), with interaction effects indicating substantial enhancements over time (F (2, 48) = 3.45, p = 0.035, η² = 0.08). Reaction time and situational awareness followed similar patterns, with significant group, time, and interaction effects. Correlation analysis revealed strong interrelations between the cognitive abilities, indicating that improvements in one area positively influenced others. Conclusion: Regular engagement with football video games significantly enhances cognitive abilities essential for football performance. These findings suggest that integrating video games into training programs could complement traditional methods, offering a valuable tool for cognitive development in sports

Assessing the effect of exercise timing on menstrual irregularity in women diagnosed with oligomenorrhea

Background and purpose Oligomenorrhea (infrequent menstrual periods), can significantly impact women's reproductive health and quality of life. This study explores the potential connection between exercise timing and menstrual regularity, aiming to provide insights for tailored exercise interventions in women with such irregularity.  Material and methods A 12-week pretest-posttest design with multiple experimental groups was conducted with fifteen participants aged 18-23, each with a history of consistent menstruation for at least six months and without hormonal contraceptive usage. Participants were allocated to morning, afternoon, and evening exercise sessions, engaging in a personalized exercise regimen that combined cardiovascular and strength training activities thrice weekly. Pre- and post-intervention assessments were employed to comprehensively assess menstrual regularity, focusing on cycle length and characteristics. Analysis of Covariance (ANOVA) tests were utilized to scrutinize the potential impacts of exercise timing on menstrual regularity.  Results The results showed noteworthy changes in cycle lengths after the training sessions, indicating the potential effectiveness of such interventions for individuals experiencing menstrual irregularity. Regarding Oligomenorrhea, morning sessions demonstrated the most considerable reduction in cycle length, while afternoon and evening sessions had less pronounced effects.  Conclusion This study confirms the significant impact of exercise timing on menstrual cycle length and characteristics for women with Oligomenorrhea. Varied responses emphasize the importance of tailored interventions considering distinct times of the day

Застосування ядрових моделей опорно-векторної регресії для прогнозування результатів гри в крикет у Жіночій прем'єр-лізі 2024 року

Background. The interest in women’s premier league cricket has caused the need for advanced analytics to understand the multifaceted dynamics of the sport. Study Purpose. This study aimed to contribute to sports analytics by assessing the efficacy of Support Vector Regression (SVR) kernel models in predicting the most valuable player. Such research methods as ANOVA, Bessel function, and Inverse MultiQuadratic kernel application have been deliberately chosen for their diverse mathematical approaches, aligning with the nuanced intricacies of women’s premier league cricket. Materials and methods. Player performance was analyzed by using the following study methods: ANOVA, Bessel function and Inverse MultiQuadratic kernel application. The data, sourced from espncricinfo.com and the International Cricket Council, includes essential metrics for five teams. Rigorous preprocessing techniques, such as imputation and outlier removal, enhance data reliability, ensuring robust predictive models. Results. The application of the Inverse MultiQuadratic kernel exhibits exceptional predictive performance, surpassing ANOVA and Bessel function models. The kernels radial basis function proves effective in capturing the intricate dynamics of women’s premier league cricket. The findings underscore the suitability of kernel method for predicting standout performers in the Womenʼs Premier League 2024 season. Conclusions. The study revealed the dynamic interplay between sports analytics and machine learning in women’s premier league cricket. The application of the Inverse MultiQuadratic kernel stands out as the most effective model, providing key insights into player predictions. This emphasizes the continual integration of advanced analytical techniques to enhance our understanding of the evolving landscape of women’s premier league cricket. As the sport gains prominence on the global stage, such analytical endeavors become imperative for strategic decision-making and sustained growth.Історія питання. Інтерес до жіночої прем’єр-ліги з крикету викликав потребу в застосуванні розширеної аналітики для розуміння багатогранної динаміки даного виду спорту. Мета дослідження. Метою дослідження є внесок у спортивну аналітику шляхом оцінки ефективності застосування ядрових моделей опорно-векторної регресії (ОВР) у прогнозуванні визначення найбільш результативного гравця. Такі методи дослідження, як дисперсійний аналіз (ANOVA), функція Бесселя та застосування зворотніх мультиквадратичних ядер, були свідомо обрані через їхні різноманітні математичні підходи, що відповідають тонкощам гри в крикет у жіночій прем’єр-лізі. Матеріали та методи. Результативність гравців було проаналізовано за допомогою наступних методів дослідження: дисперсійний аналіз (ANOVA), функції Бесселя та застосування зворотніх мультиквадратичних ядер. Дані, отримані з сайту espncricinfo.com та Міжнародної ради крикету, включають основні показники для п’яти команд. Ретельні методи попереднього опрацювання, такі як імпутація та виключення відхилень, підвищують достовірність даних, забезпечуючи отримання надійних прогнозних моделей. Результати. Застосування зворотного мультиквадратичного ядра демонструє виняткову прогностичну ефективність, перевершуючи моделі дисперсійного аналізу (ANOVA) та функції Бесселя. Радіально-базисна функція ядра ефективно відображає складну динаміку жіночої прем’єр-ліги з крикету. Отримані результати підкреслюють доцільність застосування ядрового методу з метою прогнозування найбільш результативних гравців у сезоні Жіночої прем’єр-ліги 2024 року. Висновки. В результаті дослідження було встановлено динамічну взаємодію між спортивною аналітикою та машин-ним навчанням у жіночій прем’єр-лізі з крикету. Застосування зворотного мультиквадратичного ядра показало найбільшу ефективність, надаючи ключову інформацію щодо прогнозування результатів гравців. Це підкреслює постійну інтеграцію сучасних аналітичних методів для покращення нашого розуміння динаміки розвитку жіночої прем’єр-ліги з крикету. Оскільки цей вид спорту набуває все більшої популярності на світовій арені, такі аналітичні дослідження стають необхідними для прийняття стратегічних рішень та сталого розвитку

Прогнозування успішності команд в Індійській прем’єр-лізі з крикету сезону 2024 року через аналіз застосування методу випадкового лісу

Background. Random Forest is a popular machine learning algorithm used for classification and regression tasks. The study purpose is to investigate the use of Random Forest machine learning to predict the winning chances of teams in the 2024 Indian Premier League (IPL) season. Objectives. By analyzing comprehensive player statistics, including matches played, batting and bowling averages, as well as fielding contributions, the study aims to understand the factors that influence team success in T20 cricket and provide actionable insights for team management, betting markets, and cricket enthusiasts. Material and methods. The study involved 10 cricket teams competing in the IPL 2024 season. Player statistics and match outcomes data from previous IPL seasons were collected and cleaned, with missing values addressed through imputation. The features were based on player statistics, including both aggregate measures and calculated metrics. A Random Forest is chosen as the machine learning model, trained using preprocessed data, with features derived from player statistics as input and match outcomes as the target variable. The dataset was split into training and validation sets, using methodologies such as cross-validation to ensure a robust model performance. Results. The Random Forest model demonstrates strong predictive performance, with a low Mean Squared Error (MSE) of 8.2174, Root Mean Squared Error (RMSE) of 2.8666, and a high R-Squared value of 0.9173, indicating approximately 91.73% variance explained in the data. Chennai Super Kings emerge as frontrunners with a predicted performance percentage of 83.4%, while teams like Punjab Kings and Lucknow Super Giants show lower predicted performance percentages, suggesting potential areas for its improvement. Conclusions. This study reveals the effectiveness of Random Forest machine learning in forecasting IPL match outcomes based on player statistics. It provides valuable insights into team dynamics and offers actionable recommendations for team management and cricket enthusiasts. The findings enrich our understanding of IPL match dynamics, contribute to the evolution of cricket analytics, and promote greater engagement with sport, ultimately enhancing the fan experience in the IPL.Історія питання. Випадковий ліс (англ. “Random Forest”) — популярний алгоритм машинного навчання, який використовується для задач класифікації та регресії. Метою роботи є дослідити застосування методу машинного навчання випадкового лісу для прогнозування шансів команд на перемогу в сезоні 2024 року Індійської прем’єр-ліги (ІПЛ). Мета дослідження. Шляхом аналізу всебічної статистики гравців, включаючи зіграні матчі, середні показники відбивання та боулінгу, а також активність філдингу, дослідження має на меті з’ясувати фактори, що впливають на успіх команди в крикеті серії T20 (“Twenty20”), і надати практичну інформацію для менеджменту команд, ринків прогнозів та поціновувачів крикету. Матеріал та методи. У дослідженні взяли участь 10 команд з крикету, які змагалися в сезоні ІПЛ 2024 року. Статистичні дані про гравців та результати матчів за попередні сезони ІПЛ було зібрано та опрацьовано, а відсутні значення отримано за допомогою методу імпутації. Характеристики базувалися на статистиці гравців, включаючи як агреговані показники, так і обчислювані метрики. В якості моделі машинного навчання обрано метод випадкового лісу, який використовується для навчання на основі попередньо оброблених даних, з характеристиками, отриманими на основі статистики гравців —  в якості вхідних даних та результатами матчів в якості цільової змінної. Для забезпечення надійного функціонування моделі набір даних було розділено на тренувальний та затверджувальний набори з використанням таких методик, як перехресне затверджування. Результати. Модель випадкового лісу демонструє суттєву прогностичну ефективність з низькою середньоквадратичною похибкою (СКП) 8,2174, коренем із середньоквадратичної похибки (КСКП) 2,8666 і високим значенням R-квадрату 0,9173, вказуючи на пояснення приблизно 91,73% дисперсії в даних. Команда “Chennai Super Kings” лідирує з прогнозованим відсотком результативності 83,4%, в той час як команди “Punjab Kings” та “Lucknow Super Giants” показують нижчий прогнозований відсоток результативності, що свідчить про наявність потенційних можливостей для її покращення. Висновки. Це дослідження демонструє ефективність застосування методу машинного навчання випадкового лісу для прогнозування результатів матчів ІПЛ на основі статистики гравців. Дослідження містить цінну інформацію щодо командної динаміки та практичні рекомендації для менеджменту команд і шанувальників крикету. Отримані результати збагачують наше розуміння щодо динаміки матчів ІПЛ, сприяють розвитку аналітики крикету та більшому залученню до спорту, що в кінцевому підсумку підвищує рівень досвіду вболівальників в ІПЛ

The effectiveness of a 12-week sport nutrition education intervention on female volleyball players performance

Purpose: This study aimed to evaluate the effectiveness of a 12-week sport nutrition education intervention (SNEI) on female volleyball players aged 18 to 25 in Tamil Nadu, India, with a focus on improving nutritional knowledge, dietary habits, body composition, and athletic performance. Material and Methods: Employing a single-group pre- and post-test design, 30 participants underwent the SNEI, consisting of structured educational sessions covering topics such as energy intake, macronutrients, and hydration. Performance evaluations included agility, vertical jump, broad jump, and strength tests using standardized protocols. Results: Post-intervention, participants demonstrated significant improvements in multiple domains. Sport nutrition knowledge increased significantly, with mean scores rising from 65.4 ± 7.2 to 82.7 ± 6.5. Dietary intake saw notable enhancements, particularly in protein and fat consumption, reflecting adherence to dietary guidelines. Body composition assessments revealed reduced fat mass, indicating improvements in body composition. Performance metrics exhibited significant enhancements, including agility, vertical jump height, broad jump distance, and strength, highlighting improved athletic performance. Conclusions: The findings indicate that the 12-week SNEI effectively enhanced sport nutrition knowledge, dietary habits, body composition, and athletic performance among female volleyball players aged 18 to 25 in Tamil Nadu, India. Integrating nutrition education into athlete development programs is crucial for optimizing performance and fostering informed nutrition practices. The study underscores the importance of targeted interventions tailored to the unique needs of athletes, particularly in regions where resources for nutritional education may be limited

Effect of cardiovascular fitness on performance metrics in Bangladeshi women cricket: a role-specific analysis employing the Harvard step test

Background: Cardiovascular fitness is essential for sports performance, enabling players to endure intense training, delay fatigue, and reduce injury risk—all critical factors for achieving optimal results in competitive sports like cricket. Emphasizing inclusive health ensures that all athletes enhance their cardiovascular fitness and overall performance. Purpose: This study aimed to investigate the impact of cardiovascular fitness, assessed using the Harvard Step Test, on the performance indicators of Bangladeshi women cricketers across their respective playing roles. Method: 104 players, including 34 batters, 38 bowlers, and 32 all-rounders, were voluntarily selected from the “Bangladesh National Women’s Cricket League 2021-22”. Cardiovascular fitness was evaluated through the Harvard Step Test, and role-specific performance metrics such as strike rate, bowling economy, and dismissal rates were analyzed. Statistical analyses included descrip-tive statistics and one-way ANOVA to assess differences in aerobic fitness across player roles and correlation analyses to examine the rela-tionships between performance metrics and Harvard Step Test scores. Results: The multi-group comparison did not reveal a statistically significant difference in aerobic fitness across the playing roles, F(2, 101) = 0.668, p = 0.515. Additionally, the Harvard Step Test scores showed a weak and statistically non-significant relationship with role-specific performance metrics: strike rate (r = 0.20, p = 0.06) for batters, bowling economy (r = -0.09, p = 0.51) for bowlers, and dismissals (r = 0.10, p = 0.38) for fielders. Conclusion: Cardiovascular efficiency is similar across batters, bowlers, and all-rounders among Bangladeshi women cricketers. The Harvard Step Test score is notdirectly associated with role-specific performance in women's cricket. These findings suggest that training programs should adopt a holistic physical fitness approach, incorporating role-specific training to enhance the overall abilities of female cricketers and contribute to the development of women's cricket in Bangladesh.Antecedentes: La aptitud cardiovascular es esencial para el rendimiento deportivo, ya que permite a los jugadores soportar un entrenamiento intenso, retrasar la fatiga y reducir el riesgo de lesiones, todos factores críticos para lograr resultados óptimos en deportes competitivos como el cricket. Hacer hincapié en la salud inclusiva garantiza que todos los atletas mejoren su aptitud cardiovascular y su rendimiento general. Propósito: Este estudio tuvo como objetivo investigar el impacto de la aptitud cardiovascular, evaluada mediante el Test de Pasos de Harvard, en los indicadores de rendimiento de las jugadoras de críquet de Bangladesh en sus respectivos roles de juego. Método: Un total de 104 jugadoras, incluidas 34 bateadoras, 38 lanzadoras y 32 polivalentes, fueron seleccionadas voluntariamente de la "Liga Nacional de Cricket Femenino de Bangladesh 2021-22". La aptitud cardiovascular se evaluó a través de la prueba de pasos de Harvard, y se analizaron las métricas de rendimiento específicas del rol, como la tasa de golpes, la economía de los bolos y las tasas de expulsión. Los análisis estadísticos incluyeron estadísticas descriptivas y ANOVA de un factor para evaluar las diferencias en la aptitud aeróbica entre los roles de los jugadores y análisis de correlación para examinar las relaciones entre las métricas de rendimiento y las puntuaciones de la prueba de pasos de Harvard. Resultados: La comparación multigrupo no reveló una diferencia estadísticamente significativa en la aptitud aeróbica entre los roles de juego, F(2, 101) = 0,668, p = 0,515. Además, los puntajes de la prueba de pasos de Harvard mostraron una relación débil y estadísticamente no significativa con las métricas de rendimiento específicas del rol: tasa de strikes (r = 0.20, p = 0.06) para los bateadores, economía de bolos (r = -0.09, p = 0.51) para los lanzadores y despidos (r = 0.10, p = 0.38) para los fildeadores. Conclusión: La eficiencia cardiovascular es similar entre las bateadoras, las lanzadoras y las jugadoras de críquet de Bangladesh. La puntuación de la Harvard Step Test no está directamente asociada con el rendimiento específico del rol en el críquet femenino. Estos hallazgos sugieren que los programas de entrenamiento deben adoptar un enfoque holístico de aptitud física, incorporando un entrenamiento específico para mejorar las habilidades generales de las jugadoras de críquet y contribuir al desarrollo del críquet femenino en Banglades