Journal Description
Sports
Sports
is an international, peer-reviewed, open access journal published monthly online by MDPI. The Strength and Conditioning Society (SCS), The European Sport Nutrition Society (ESNS) and The European Network of Sport Education (ENSE) are affiliated with Sports and their members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), PubMed, PMC, and other databases.
- Journal Rank: JCR - Q2 (Sport Sciences ) / CiteScore - Q2 (Physical Therapy, Sports Therapy and Rehabilitation)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.4 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the first half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
2.2 (2023);
5-Year Impact Factor:
2.8 (2023)
Latest Articles
A Comparison of Physical Activity and Exercise Recommendations for Public Health: Inconsistent Activity Messages Are Being Conveyed to the General Public
Sports 2024, 12(12), 335; https://doi.org/10.3390/sports12120335 - 4 Dec 2024
Abstract
We examined the similarities and differences between government-supported public health activity recommendations from the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), the National Health Service (NHS), the Department of Health and Aged Care (DHAC), and one of the
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We examined the similarities and differences between government-supported public health activity recommendations from the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), the National Health Service (NHS), the Department of Health and Aged Care (DHAC), and one of the most renowned public health activity recommendations, the 10,000 Steps Program. The findings derived from our evaluation suggest a lack of consistency in public health activity recommendations, including the nomenclature used to describe aerobic activity, the amount of time required per week to meet the minimum recommendation for moderate and vigorous activity, and variations in the intensities required to meet aerobic activity recommendations. We also found that moderate-intensity activity (3.0 to less than 6.0 METS) is achieved across the lifespan with normal (i.e., mean), rather than vigorous, walking speeds; this suggests the MET level for moderate-intensity activity may need to be re-examined. The suggested strength activities must also be considered to ensure that the activities maintain or improve strength in the general public. Among the reviewed recommendations, none distinguished between physical activity and exercise, which may contribute to the low levels of exercise participation among the general public. Since exercise is medicine, the most recognized government-supported public health activity recommendations should place a greater emphasis on exercise over physical activity. Moreover, given the low levels of activity in the general public, more care should be given to provide a consistent, clear, and direct message regarding activity recommendations.
Full article
Open AccessArticle
A Comparison of Three Protocols for Determining Barbell Bench Press Single Repetition Maximum, Barbell Kinetics, and Subsequent Measures of Muscular Performance in Resistance-Trained Adults
by
Matthew T. Stratton, Austin T. Massengale, Riley A. Clark, Kaitlyn Evenson-McMurtry and Morgan Wormely
Sports 2024, 12(12), 334; https://doi.org/10.3390/sports12120334 - 3 Dec 2024
Abstract
Background: One repetition maximum (1RM) is a vital metric for exercise professionals, but various testing protocols exist, and their impacts on the resulting 1RM, barbell kinetics, and subsequent muscular performance testing are not well understood. This study aimed to compare two previously established
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Background: One repetition maximum (1RM) is a vital metric for exercise professionals, but various testing protocols exist, and their impacts on the resulting 1RM, barbell kinetics, and subsequent muscular performance testing are not well understood. This study aimed to compare two previously established protocols and a novel self-led method for determining bench press 1RM, 1RM barbell kinetics, and subsequent muscular performance measures. Methods: Twenty-four resistance-trained males (n = 12, 24 ± 6.1 years) and females (n = 12, 22.5 ± 5.5 years) completed three laboratory visits in a randomized crossover fashion. During each visit, a 1RM was established using one of the three protocols followed by a single set to volitional fatigue using 80% of their 1RM. A Sex:Protocol repeated measures ANOVA was used to determine the effects of sex and differences between protocols. Results: No significant differences were observed between the protocols for any measure, except for 1RM peak power (p = 0.036). Post hoc pairwise comparisons failed to identify any differences. Males showed significantly higher 1RM, average, and peak power (ps < 0.001), while females demonstrated a greater average concentric velocity (p = 0.031) at 1RM. Conclusions: These data suggest the protocol used to establish 1RM may have minimal impact on the final 1RM, 1RM barbell kinetics, and subsequent muscular endurance in a laboratory setting.
Full article
(This article belongs to the Special Issue Cutting-Edge Strategies in Resistance Training: Exploring Innovative Approaches)
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<p>Timeline and overview of procedures.</p> Full article ">Figure 2
<p>Description of the three methods utilized to determine barbell bench press 1RM. Protocol #1 (P1) was the guidelines set forth by the National Strength and Conditioning Association (NSCA) [<a href="#B39-sports-12-00334" class="html-bibr">39</a>] while Protocol #2 (P2) was developed by Klemp and colleagues [<a href="#B11-sports-12-00334" class="html-bibr">11</a>].</p> Full article ">
<p>Timeline and overview of procedures.</p> Full article ">Figure 2
<p>Description of the three methods utilized to determine barbell bench press 1RM. Protocol #1 (P1) was the guidelines set forth by the National Strength and Conditioning Association (NSCA) [<a href="#B39-sports-12-00334" class="html-bibr">39</a>] while Protocol #2 (P2) was developed by Klemp and colleagues [<a href="#B11-sports-12-00334" class="html-bibr">11</a>].</p> Full article ">
Open AccessReview
A Bibliometric Study on the Evolution of Women’s Football and Determinants Behind Its Growth over the Last 30 Years
by
Javier Ventaja-Cruz, Jesús M. Cuevas Rincón, Virginia Tejada-Medina and Ricardo Martín-Moya
Sports 2024, 12(12), 333; https://doi.org/10.3390/sports12120333 - 3 Dec 2024
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Background: The evolution of women’s football over the past three decades has been remarkable in terms of development, visibility, and acceptance, transforming into a discipline with growing popularity and professionalization. Significant advancements in gender equality and global visibility have occurred, and the combination
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Background: The evolution of women’s football over the past three decades has been remarkable in terms of development, visibility, and acceptance, transforming into a discipline with growing popularity and professionalization. Significant advancements in gender equality and global visibility have occurred, and the combination of emerging talent, increasing commercial interest, and institutional support will continue to drive the growth and consolidation of women’s football worldwide. Methods: The purpose of this study was to present a bibliometric analysis of articles on the evolution of women’s football in terms of scientific production as well as its causes and motivations over the past 30 years (1992–2024). A total of 128 documents indexed in the Web of Science database were reviewed. Outcome measures were analyzed using RStudio version 4.3.1 (Viena, Austria) software and the Bibliometrix data package to evaluate productivity indicators including the number of articles published per year, most productive authors, institutions, countries, and journals as well as identify the most cited articles and common topics. Results: Scientific production on women’s football has shown sustained growth, particularly since 2010. Key research areas have focused on injury prevention, physical performance, psychosocial factors, motivation, and leadership. The United States, the United Kingdom, and Spain have emerged as the most productive countries in this field, with strong international collaboration reflected in co-authorship networks. Conclusions: The study revealed a clear correlation between the evolution of women’s football and the increase in scientific production, providing a strong foundation for future research on emerging topics such as the importance of psychological factors, sport motivation and emotional well-being on performance, gender differences at the physiological and biomechanical levels, or misogyny in social networks, thus promoting comprehensive development in this sport modality.
Full article
Figure 1
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<p>Annual scientific production (1992–2024).</p> Full article ">Figure 2
<p>Top ten most relevant journals.</p> Full article ">Figure 3
<p>Relevant journals according to Bradford’s law.</p> Full article ">Figure 4
<p>Distribution of scientific production according to Bradford’s law.</p> Full article ">Figure 5
<p>Author productivity according to Lotka’s law.</p> Full article ">Figure 6
<p>Top ten authors with the highest scientific production.</p> Full article ">Figure 7
<p>Collaboration map between countries.</p> Full article ">Figure 8
<p>Country of the corresponding author. SCP: single-country publication; MCP: multiple-country publication.</p> Full article ">Figure 9
<p>Most relevant affiliations.</p> Full article ">Figure 10
<p>Collaboration visualization network among authors (co-authorships).</p> Full article ">Figure 11
<p>Author co-citation network in publications [<a href="#B22-sports-12-00333" class="html-bibr">22</a>,<a href="#B44-sports-12-00333" class="html-bibr">44</a>,<a href="#B45-sports-12-00333" class="html-bibr">45</a>,<a href="#B46-sports-12-00333" class="html-bibr">46</a>,<a href="#B47-sports-12-00333" class="html-bibr">47</a>,<a href="#B48-sports-12-00333" class="html-bibr">48</a>,<a href="#B49-sports-12-00333" class="html-bibr">49</a>,<a href="#B50-sports-12-00333" class="html-bibr">50</a>,<a href="#B51-sports-12-00333" class="html-bibr">51</a>,<a href="#B52-sports-12-00333" class="html-bibr">52</a>,<a href="#B53-sports-12-00333" class="html-bibr">53</a>,<a href="#B54-sports-12-00333" class="html-bibr">54</a>,<a href="#B55-sports-12-00333" class="html-bibr">55</a>,<a href="#B56-sports-12-00333" class="html-bibr">56</a>,<a href="#B57-sports-12-00333" class="html-bibr">57</a>,<a href="#B58-sports-12-00333" class="html-bibr">58</a>,<a href="#B59-sports-12-00333" class="html-bibr">59</a>].</p> Full article ">Figure 12
<p>Co-occurrence network map of KeyWords Plus.</p> Full article ">Figure 13
<p>Co-occurrence network map of author’s keywords.</p> Full article ">Figure 14
<p>Three-fields plot: authors (AU), journals (SO), and author’s keywords (DE).</p> Full article ">
<p>Annual scientific production (1992–2024).</p> Full article ">Figure 2
<p>Top ten most relevant journals.</p> Full article ">Figure 3
<p>Relevant journals according to Bradford’s law.</p> Full article ">Figure 4
<p>Distribution of scientific production according to Bradford’s law.</p> Full article ">Figure 5
<p>Author productivity according to Lotka’s law.</p> Full article ">Figure 6
<p>Top ten authors with the highest scientific production.</p> Full article ">Figure 7
<p>Collaboration map between countries.</p> Full article ">Figure 8
<p>Country of the corresponding author. SCP: single-country publication; MCP: multiple-country publication.</p> Full article ">Figure 9
<p>Most relevant affiliations.</p> Full article ">Figure 10
<p>Collaboration visualization network among authors (co-authorships).</p> Full article ">Figure 11
<p>Author co-citation network in publications [<a href="#B22-sports-12-00333" class="html-bibr">22</a>,<a href="#B44-sports-12-00333" class="html-bibr">44</a>,<a href="#B45-sports-12-00333" class="html-bibr">45</a>,<a href="#B46-sports-12-00333" class="html-bibr">46</a>,<a href="#B47-sports-12-00333" class="html-bibr">47</a>,<a href="#B48-sports-12-00333" class="html-bibr">48</a>,<a href="#B49-sports-12-00333" class="html-bibr">49</a>,<a href="#B50-sports-12-00333" class="html-bibr">50</a>,<a href="#B51-sports-12-00333" class="html-bibr">51</a>,<a href="#B52-sports-12-00333" class="html-bibr">52</a>,<a href="#B53-sports-12-00333" class="html-bibr">53</a>,<a href="#B54-sports-12-00333" class="html-bibr">54</a>,<a href="#B55-sports-12-00333" class="html-bibr">55</a>,<a href="#B56-sports-12-00333" class="html-bibr">56</a>,<a href="#B57-sports-12-00333" class="html-bibr">57</a>,<a href="#B58-sports-12-00333" class="html-bibr">58</a>,<a href="#B59-sports-12-00333" class="html-bibr">59</a>].</p> Full article ">Figure 12
<p>Co-occurrence network map of KeyWords Plus.</p> Full article ">Figure 13
<p>Co-occurrence network map of author’s keywords.</p> Full article ">Figure 14
<p>Three-fields plot: authors (AU), journals (SO), and author’s keywords (DE).</p> Full article ">
Open AccessArticle
Physical Activity and Sedentary Behavior on Well-Being and Self-Rated Health of Italian Public Health Medical Residents During the COVID-19 Pandemic: The PHRASI Study
by
Alessandro Catalini, Giuseppa Minutolo, Marta Caminiti, Angela Ancona, Claudia Cosma, Veronica Gallinoro and Vincenza Gianfredi
Sports 2024, 12(12), 332; https://doi.org/10.3390/sports12120332 - 2 Dec 2024
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High workloads and extended work shift greatly limit the opportunities for medical residents to adopt a healthy lifestyle by practicing regular physical exercise. Using data from the Public Health Residents’ Anonymous Survey in Italy (PHRASI), this research assessed the associations between physical activity
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High workloads and extended work shift greatly limit the opportunities for medical residents to adopt a healthy lifestyle by practicing regular physical exercise. Using data from the Public Health Residents’ Anonymous Survey in Italy (PHRASI), this research assessed the associations between physical activity levels and sedentary behavior, well-being, and self-rated health among Italian public health residents (PHRs) during the COVID-19 pandemic. Employing a cross-sectional design, this study utilized the International Physical Activity Questionnaire, the WHO-5 Well-being Index, and the single-item self-rated health to measure physical activity, sedentary behavior, self-rated health, and well-being among PHRs. The study included 379 PHRs. Multiple logistic regressions adjusted for age and sex were applied to explore the associations among the variables of interest. While 74% of PHRs were sufficiently active, 50% reported good well-being. We found a positive association between physical activity (specifically walking and intense activities) and well-being (aOR 1.292, p = 0.032). At the same time, sedentary behavior was negatively associated with self-rated health (aOR 0.948, p = 0.022) and well-being (aOR 0.945, p = 0.005). This study contributes valuable insights into the role of physical activity and sedentary behavior in PHRs’ mental health, calling for targeted public health strategies to support their well-being.
Full article
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<p>Socio-demographic characteristics and physical activity levels of PHRs. Icons on moderate and vigorous physical activity were chosen according to Compendium of Physical Activities (<a href="https://pacompendium.com/sports/" target="_blank">https://pacompendium.com/sports/</a> (accessed on 22 November 2024)), considering the metabolic equivalent of task (MET) thresholds of physical activity levels reported by Haskell et al. (<a href="https://journals.lww.com/acsm-msse/fulltext/2007/08000/physical_activity_and_public_health__updated.27.aspx" target="_blank">https://journals.lww.com/acsm-msse/fulltext/2007/08000/physical_activity_and_public_health__updated.27.aspx</a> (22 November 2024)). Some of the graphical elements are 100% free images by pch.vector on Freepick.</p> Full article ">Figure 2
<p>Boxplots showing the mean (gray dot) and SD (gray line) of minutes per day spent on different levels of physical activity, grouped by well-being and self-rated health.</p> Full article ">Figure 3
<p>Boxplots showing the mean (gray dot) and SD (gray line) of minutes spent in sedentary behavior (weekly, on weekdays, and at the weekend), grouped by well-being and self-rated health.</p> Full article ">Figure 4
<p>Bar charts with the number of public health residents who participated in this study and the related percentages, grouped by well-being and SRH.</p> Full article ">
<p>Socio-demographic characteristics and physical activity levels of PHRs. Icons on moderate and vigorous physical activity were chosen according to Compendium of Physical Activities (<a href="https://pacompendium.com/sports/" target="_blank">https://pacompendium.com/sports/</a> (accessed on 22 November 2024)), considering the metabolic equivalent of task (MET) thresholds of physical activity levels reported by Haskell et al. (<a href="https://journals.lww.com/acsm-msse/fulltext/2007/08000/physical_activity_and_public_health__updated.27.aspx" target="_blank">https://journals.lww.com/acsm-msse/fulltext/2007/08000/physical_activity_and_public_health__updated.27.aspx</a> (22 November 2024)). Some of the graphical elements are 100% free images by pch.vector on Freepick.</p> Full article ">Figure 2
<p>Boxplots showing the mean (gray dot) and SD (gray line) of minutes per day spent on different levels of physical activity, grouped by well-being and self-rated health.</p> Full article ">Figure 3
<p>Boxplots showing the mean (gray dot) and SD (gray line) of minutes spent in sedentary behavior (weekly, on weekdays, and at the weekend), grouped by well-being and self-rated health.</p> Full article ">Figure 4
<p>Bar charts with the number of public health residents who participated in this study and the related percentages, grouped by well-being and SRH.</p> Full article ">
Open AccessArticle
The Effect of Intraset Rest Periods on External and Internal Load During Small-Sided Games in Soccer
by
Ioannis Ispirlidis, Dimitrios Pantazis, Athanasios Poulios, Alexandra Avloniti, Theodoros Stampoulis, Yiannis Michailidis, Konstantinos Troupkos, Evangelos Evangelou, Dimitrios Draganidis, Dimitrios Balampanos, Nikolaos-Orestis Retzepis, Maria Protopapa, Nikolaos Mantzouranis, Nikolaos Zaras, Maria Michalopoulou, Ioannis G. Fatouros and Athanasios Chatzinikolaou
Sports 2024, 12(12), 331; https://doi.org/10.3390/sports12120331 - 2 Dec 2024
Abstract
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The purpose of this study was to compare the internal and external load in continuous and intermittent small-sided games (SSG) formats. Eight semi-professional soccer players participated in the study, and they completed three protocols: (a) I-intermittent SSG protocol (Int-I, 4 sets of 4
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The purpose of this study was to compare the internal and external load in continuous and intermittent small-sided games (SSG) formats. Eight semi-professional soccer players participated in the study, and they completed three protocols: (a) I-intermittent SSG protocol (Int-I, 4 sets of 4 min with a 3 min recovery); (b) Continuous SSG protocol (Con, 2 sets of 8 min with a 3 min recovery); (c) II-SSG protocol (Int-II, 4 sets of 4 min, where each set includes 1 min of exercise with varying recovery periods (10, 20, 30 s), with a 3 min recovery period between sets). A one-way analysis of variance (ANOVA) was used to analyze the dependent variables, with significance determined at p < 0.05. The three protocols differed in total distance covered and in distance covered at speeds >19 km/h, with the Int-II protocol resulting in the greatest distance covered (p < 0.05). Additionally, players in the Con protocol exercised at a higher percentage of their maximum heart rate (%HRmax) (p < 0.05), while the highest RPE value was observed in the Int-I interval protocol (p < 0.05). The external load experienced by players in intermittent SSG protocols is higher, while internal load (%HRmax) remains relatively low. This effect is especially notable in the new intermittent exercise model proposed in this study, which incorporates progressively increasing recovery times within each exercise set. Coaches can use this model to increase players’ external load without causing a heightened perception of fatigue.
Full article
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<p>Experimental Design. RMR, resting metabolic rate; RSA, repeated sprint ability; Yo-Yo IR1, Yo-Yo intermittent recovery test level 1; CMJ, counter movement jump; R, right; L, left; m, meter; SSG, small-sided games; Int-I, intermittent-I protocol; Con, continuous protocol; Int-II, intermittent-II protocol; GPS, global positioning system; HR, heart rate.</p> Full article ">
<p>Experimental Design. RMR, resting metabolic rate; RSA, repeated sprint ability; Yo-Yo IR1, Yo-Yo intermittent recovery test level 1; CMJ, counter movement jump; R, right; L, left; m, meter; SSG, small-sided games; Int-I, intermittent-I protocol; Con, continuous protocol; Int-II, intermittent-II protocol; GPS, global positioning system; HR, heart rate.</p> Full article ">
Open AccessArticle
Impact of a Three-Month Training Break on Swimming Performance in Athletes with Intellectual Disability
by
Glykeria Kyriakidou, George Tsalis and Christina Evaggelinou
Sports 2024, 12(12), 330; https://doi.org/10.3390/sports12120330 - 2 Dec 2024
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This study aimed to ascertain whether there were any differences in anthropometrics, heart rate, and swimming performance parameters in athletes with intellectual disabilities (ID) before and after a three-month training break. A total of 21 athletes participated in the study, comprising 16 males
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This study aimed to ascertain whether there were any differences in anthropometrics, heart rate, and swimming performance parameters in athletes with intellectual disabilities (ID) before and after a three-month training break. A total of 21 athletes participated in the study, comprising 16 males and 5 females, with a mean age of 28.3 ± 8.7 years. All participants had ID, and six of them had Down syndrome. The study participants were classified as S14 athletes from a local swimming club. All participants had a minimum of four years of swimming experience and attended two to three one-hour sessions per week for eight consecutive months. All athletes completed two trials of 25 m freestyle swimming, one at the end of a training session and the other at the beginning of a new session. The measurements included weight, body mass index (BMI), handgrip strength (HGS), heart rate (pre- and post-trial), performance (T25), stroke count (SC), stroke length (SL), stroke rate, and the SWOLF efficiency index. The results demonstrated statistically significant elevations in weight (80.2 ± 16.1 to 81.7 ± 15.9), BMI (26.8 ± 5.5 to 27.2 ± 5.5), T25 (33.1 ± 17.1 to 35.6 ± 18), SC (19.3 ± 6.1 to 20.7 ± 7.2), and SWOLF (52.4 ± 22.0 to 56.3 ± 25.2) and a reduction in SL (1.39 ± 0.48 to 1.27 ± 0.42). However, no significant differences were observed in the remaining parameters. Significant correlations were found for body weight, BMI, HGS, and SWOLF with T25 throughout the study. It was concluded that individuals with ID experienced a decline in 25 m swimming performance due to technical rather than physiological factors after three months of detraining.
Full article
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<p>A schematic diagram of the experimental protocol.</p> Full article ">Figure 2
<p>The heart rate measurements taken prior to (Pre), immediately following (Post), one minute after (Post1min), and two minutes after (Post2min) the 25 m freestyle trials are represented in the graph. Heart rate data from the June trials are represented by a blue line, while data from the September trials are indicated by a red line. bpm = beats per minute.</p> Full article ">
<p>A schematic diagram of the experimental protocol.</p> Full article ">Figure 2
<p>The heart rate measurements taken prior to (Pre), immediately following (Post), one minute after (Post1min), and two minutes after (Post2min) the 25 m freestyle trials are represented in the graph. Heart rate data from the June trials are represented by a blue line, while data from the September trials are indicated by a red line. bpm = beats per minute.</p> Full article ">
Open AccessArticle
Influence of Running Surface Using Advanced Footwear Technology Spikes on Middle- and Long-Distance Running Performance Measures
by
Alejandro Alda-Blanco, Sergio Rodríguez-Barbero, Víctor Rodrigo-Carranza, Fernando Valero, Patricia Chico and Fernando González-Mohíno
Sports 2024, 12(12), 329; https://doi.org/10.3390/sports12120329 - 2 Dec 2024
Abstract
Objective: This study evaluated the effects of advanced footwear technology (AFT) spikes on running performance measures, spatiotemporal variables, and perceptive parameters on different surfaces (track and grass). Methods: Twenty-seven male trained runners were recruited for this study. In Experiment 1, participants performed 12
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Objective: This study evaluated the effects of advanced footwear technology (AFT) spikes on running performance measures, spatiotemporal variables, and perceptive parameters on different surfaces (track and grass). Methods: Twenty-seven male trained runners were recruited for this study. In Experiment 1, participants performed 12 × 200 m at a self-perceived 3000 m running pace with a recovery of 5 min. Performance (time in each repetition), spatiotemporal, and perceptive parameters were measured. In Experiment 2, participants performed 8 × 5 min at 4.44 m/s while energy cost of running (W/kg), spatiotemporal, and perceptive parameters were measured. In both experiments the surface was randomized and mirror order between spike conditions (Polyether Block Amide (PEBA) and PEBA + Plate) was used. Results: Experiment 1: Runners were faster on the track (p = 0.002) and using PEBA + Plate spike (p = 0.049). Experiment 2: Running on grass increased energy cost (p = 0.03) and heart rate (p < 0.001) regardless of the spike used, while PEBA + Plate spike reduced respiratory exchange ratio (RER) (p = 0.041). Step frequency was different across surfaces (p < 0.001) and spikes (p = 0.002), with increased performance and comfort perceived with PEBA + Plate spikes (p < 0.001; p = 0.049). Conclusions: Running on the track surface with PEBA + Plate spikes enhanced auto-perceived 3000 m running performance, showed lower RER, and improved auto-perceptive comfort and performance. Running on grass surfaces increased energy cost and heart rate without differences between spike conditions.
Full article
(This article belongs to the Special Issue Physiological Effects of Sports on the Cardiopulmonary System)
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<p>Force–displacement representation for AFT spikes condition used in this study. (<b>A</b>) AFT spike with PEBA midsole foam + carbon plate (Cloudspike Citus). (<b>B</b>) AFT spike PEBA midsole foam (Clouspike XC).</p> Full article ">Figure 2
<p>Experimental design. (<b>A</b>) Experiment 1: Efforts at self-perceived 3000 m race pace. (<b>B</b>) Experiment 2: Running economy protocol at 4.44 m/s.</p> Full article ">Figure 3
<p>Average speed and energy cost for track and grass repetitions in each spike condition. (<b>A</b>) Speed variable in Experiment 1. (<b>B</b>) Energy cost variable in Experiment 2. * Significant differences between shoe conditions (<span class="html-italic">p</span> < 0.05). # Significant differences between surface conditions (<span class="html-italic">p</span> < 0.05).</p> Full article ">
<p>Force–displacement representation for AFT spikes condition used in this study. (<b>A</b>) AFT spike with PEBA midsole foam + carbon plate (Cloudspike Citus). (<b>B</b>) AFT spike PEBA midsole foam (Clouspike XC).</p> Full article ">Figure 2
<p>Experimental design. (<b>A</b>) Experiment 1: Efforts at self-perceived 3000 m race pace. (<b>B</b>) Experiment 2: Running economy protocol at 4.44 m/s.</p> Full article ">Figure 3
<p>Average speed and energy cost for track and grass repetitions in each spike condition. (<b>A</b>) Speed variable in Experiment 1. (<b>B</b>) Energy cost variable in Experiment 2. * Significant differences between shoe conditions (<span class="html-italic">p</span> < 0.05). # Significant differences between surface conditions (<span class="html-italic">p</span> < 0.05).</p> Full article ">
Open AccessArticle
Children’s Individual Differences in the Responses to a New Method for Physical Education
by
Sara Pereira, Carla Santos, José Maia, Olga Vasconcelos, Eduardo Guimarães, Rui Garganta, Cláudio Farias, Tiago V. Barreira, Go Tani, Peter T. Katzmarzyk and Fernando Garbeloto
Sports 2024, 12(12), 328; https://doi.org/10.3390/sports12120328 - 29 Nov 2024
Abstract
Children’s fundamental movement skills (FMS) require planned and guided interventions to develop appropriately. We investigated the effect of a novel Physical Education (PE) method to develop children’s object control, locomotor skills, and motor competence. Further, we examined children’s trainability, i.e., their differential responses
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Children’s fundamental movement skills (FMS) require planned and guided interventions to develop appropriately. We investigated the effect of a novel Physical Education (PE) method to develop children’s object control, locomotor skills, and motor competence. Further, we examined children’s trainability, i.e., their differential responses to the new method, and identified low and high responders to the intervention. The study lasted three months and included six to seven-year-old children in two groups: control (the current, official PE program; n = 38) and experimental (the new method; n = 52). Twelve FMS [object control (OC), locomotor (LO)] were reliably assessed using the Meu Educativo® app. Using a mixed-effects model, results showed that the experimental group experienced greater changes (p < 0.05) than the control group in OC and LO. Positive individual changes were more frequent with the new method, but children showed a similar pattern in their interindividual variability in both methods. There was a greater reduction in the number of children with lower proficiency in the experimental group. In sum, the new PE method proved superior to the current, official one. Individual responses to the new method showed considerable variation, highlighting the need for personalization in teaching strategies and necessary support for children with lower proficiency levels, ensuring that no child is left behind in their motor development process.
Full article
(This article belongs to the Special Issue Advances in Motor Behavior and Child Health)
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<p>Graphical display of study design.</p> Full article ">Figure 2
<p>Graphical display of the essence of the method used in the experimental study. Positive (+) and negative (−) signs show the degree of emphasis in teaching and learning.</p> Full article ">Figure 3
<p>Individual changes (Delta in %) in object control skills, locomotion skills, and motor competence in the control group (<b>left</b> panel) and the experimental group (<b>right</b> panel); (<b>a</b>) Object control skills in the control group; (<b>b</b>) Object control skills in the experimental group; (<b>c</b>) locomotion skills in the control group; (<b>d</b>) locomotion skills in the experimental group; (<b>e</b>) motor competence in the control group; (<b>f</b>) motor competence in the experimental group.</p> Full article ">Figure 4
<p>Box plot with jittering points showing children’s interindividual responses variability in object control skills, locomotion skills, and motor competence (control group labeled 0, and experimental group labeled 1).</p> Full article ">Figure 5
<p>Percentage of explorer-level children in object control skills for the control and experimental groups before (T0) and after (T1) the intervention program.</p> Full article ">Figure 6
<p>Percentage of explorer-level children in locomotor skills for the control and experimental groups before (T0) and after (T1) the intervention program.</p> Full article ">
<p>Graphical display of study design.</p> Full article ">Figure 2
<p>Graphical display of the essence of the method used in the experimental study. Positive (+) and negative (−) signs show the degree of emphasis in teaching and learning.</p> Full article ">Figure 3
<p>Individual changes (Delta in %) in object control skills, locomotion skills, and motor competence in the control group (<b>left</b> panel) and the experimental group (<b>right</b> panel); (<b>a</b>) Object control skills in the control group; (<b>b</b>) Object control skills in the experimental group; (<b>c</b>) locomotion skills in the control group; (<b>d</b>) locomotion skills in the experimental group; (<b>e</b>) motor competence in the control group; (<b>f</b>) motor competence in the experimental group.</p> Full article ">Figure 4
<p>Box plot with jittering points showing children’s interindividual responses variability in object control skills, locomotion skills, and motor competence (control group labeled 0, and experimental group labeled 1).</p> Full article ">Figure 5
<p>Percentage of explorer-level children in object control skills for the control and experimental groups before (T0) and after (T1) the intervention program.</p> Full article ">Figure 6
<p>Percentage of explorer-level children in locomotor skills for the control and experimental groups before (T0) and after (T1) the intervention program.</p> Full article ">
Open AccessSystematic Review
Heading in Female Soccer: A Scoping Systematic Review
by
Yinhao Shen, Shinting Chen, Qingguang Liu and Antonio Cicchella
Sports 2024, 12(12), 327; https://doi.org/10.3390/sports12120327 - 29 Nov 2024
Abstract
Heading is a key skill in soccer, and it is few investigated in females. Research on heading focused mostly on males and on young players. Data on females’ soccer players are sparse and it is difficult to draw firm conclusions. Thus, little is
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Heading is a key skill in soccer, and it is few investigated in females. Research on heading focused mostly on males and on young players. Data on females’ soccer players are sparse and it is difficult to draw firm conclusions. Thus, little is known is known about heading in females. The most investigated aspects of heading are the relationship between heading and play state, training level and anthropometrics. The relationship between the frequency and intensity of headings and long-time outcomes in terms of vigilance, and neuro-cognitive status is also a topic of interest. Aim of this scoping review is to survey the available knowledge about heading in female football to identify possible weaknesses and issues for future research direction in the field. A structured literature search was performed in the main databases. Results show research on heading in female soccer is sparse and to draw firm conclusion on the investigated aspects (effect of play position, occurrence, cognitive impairment, influence of muscle strength, and player’s level) is difficult. It emerged mild intensity heading is not dangerous, helmet does not help, play state and player position influences the heading and that high rotational velocities are achieved. The survey identified new directions for research, that should focus on how to ameliorate heading training and skills and develop a more effective and safe heading technique.
Full article
(This article belongs to the Special Issue Cutting-Edge Research on Physical Fitness Profile in Soccer Players)
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Open AccessSystematic Review
The Effect of Polarized Training Intensity Distribution on Maximal Oxygen Uptake and Work Economy Among Endurance Athletes: A Systematic Review
by
Henrik Lyngstad Nøst, Morten Andreas Aune and Roland van den Tillaar
Sports 2024, 12(12), 326; https://doi.org/10.3390/sports12120326 - 27 Nov 2024
Abstract
High-intensity training (HIT) has commonly been the most effective training method for improvement in maximal oxygen uptake (VO2max) and work economy, alongside a substantial volume of low-intensity training (LIT). The polarized training model combines both low- and high-intensity training into a
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High-intensity training (HIT) has commonly been the most effective training method for improvement in maximal oxygen uptake (VO2max) and work economy, alongside a substantial volume of low-intensity training (LIT). The polarized training model combines both low- and high-intensity training into a specific training intensity distribution and has gained attention as a comprehensive approach. The objective of this review was to systematically search the literature in order to identify the effects of polarized training intensity distribution on VO2max, peak oxygen uptake (VO2peak), and work economy among endurance athletes. A literature search was performed using PubMed and SPORTDiscus. A total of 1836 articles were identified, and, after the selection process, 14 relevant studies were included in this review. The findings indicate that a polarized training approach seems to be effective for enhancing VO2max, VO2peak, and work economy over a short-term period for endurance athletes. Specifically, a training intensity distribution involving a moderate to high volume of HIT (15–20%) combined with a substantial volume of LIT (75–80%) appears to be the most beneficial for these improvements. It was concluded that polarized training is a beneficial approach for enhancing VO2max, VO2peak, and work economy in endurance athletes. However, the limited number of studies restricts the generalizability of these findings.
Full article
(This article belongs to the Special Issue Human Physiology in Exercise, Health and Sports Performance)
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Open AccessArticle
To Change or Not to Change: Perceptions and Experiential Knowledge of Tennis Coaches When Modifying Grip Technique
by
Nicholas Busuttil, Kane J. Middleton, Marcus Dunn and Alexandra H. Roberts
Sports 2024, 12(12), 325; https://doi.org/10.3390/sports12120325 - 27 Nov 2024
Abstract
The purpose of this study was to explore the experiential knowledge of tennis coaches as it related to the development of grip positions in tennis athletes. Accredited tennis coaches (n = 11) completed semi-structured interviews consisting of open-ended questions about their coaching background,
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The purpose of this study was to explore the experiential knowledge of tennis coaches as it related to the development of grip positions in tennis athletes. Accredited tennis coaches (n = 11) completed semi-structured interviews consisting of open-ended questions about their coaching background, the importance of grip positions compared with other areas of foundational development, and their opinions on using physically-constraining tools (PCTs). Two major themes, “Grip positions are an adaptive skill” and “Why and how do I modify an athlete’s grip?”, were identified. Coaches expressed the opinion that grip positions were dynamic and a modifiable component of tennis stroke technique. Irrespective of shot type, grip positions were viewed as a non-negotiable aspect of talent development and intrinsically linked to other components of the stroke. Coaches questioned the necessity of technique refinement for grip positions given the complex and time-costly nature of bringing about effective motor-behaviour change. Some coaches expressed reservations about skill transfer into live match-play, intuitively expressing the concepts of the constraints-led approach to manipulate key variables within the athlete’s environment to foster learning. Future research should aim to assess the short- and long-term effects of PCT use in tennis and establish the extent to which PCTs can impact learning and skill transfer.
Full article
Open AccessArticle
The Acute Effect of Different Cluster Set Intra-Set Rest Interval Configurations on Mechanical Power Measures During a Flywheel Resistance Training Session
by
Shane Ryan, Declan Browne, Rodrigo Ramirez-Campillo, Jeremy Moody and Paul J. Byrne
Sports 2024, 12(12), 324; https://doi.org/10.3390/sports12120324 - 27 Nov 2024
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The aim of this study was to compare the acute effect of three cluster set (CS) intra-set rest intervals (15 s, 30 s, and 45 s) on mechanical performance measures during a flywheel resistance training session. Twelve amateur male field sport athletes attended
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The aim of this study was to compare the acute effect of three cluster set (CS) intra-set rest intervals (15 s, 30 s, and 45 s) on mechanical performance measures during a flywheel resistance training session. Twelve amateur male field sport athletes attended three training measurement sessions (separated by 14 days of wash-out), consisting of four sets of nine repetitions (as cluster-blocks: 3 + 3 + 3), using a 0.050 kg·m−2 inertial load. The flywheel quarter-squat (QS) and the flywheel Romanian deadlift (RDL) were selected as resistance training exercises. Participants were randomly allocated different CS intra-set rest durations: 15 s, 30 s, or 45 s. The mean power (MP), peak concentric power (PPcon), peak eccentric power (PPecc), and eccentric overload (EO) were measured. A two-way (within–within) repeated-measures ANOVA reported that MP, PPcon, PPecc, and EO achieved similar values during the QS and RDL sessions involving 30 s and 45 s CS intra-set rest durations. It was noted that the first set did not always result in the greatest performance output for the 30 s and 45 s intervals. Compared to 15 s, the 30 s and 45 s CS intra-set rest durations showed greater MP, PPcon, and PPecc during set 2 (all p ≤ 0.05), set 3 (all p < 0.001), and set 4 (all p < 0.001) for both QS and RDL, and greater EO in the QS exercise (the four sets combined). Compared to shorter (15 s) cluster set intra-set rest intervals, longer (30–45 s) configurations allow greater physical performance outcome measures during flywheel QS and RDL resistance training sessions. The implications for longer-term interventions merit further research.
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<p>Study design for intra-set rest duration intervention.</p> Full article ">Figure 2
<p>Inter-day inter-set mean power (MP), peak concentric power (PP<sub>con</sub>), and peak eccentric (PP<sub>ecc</sub>) output (watts) by intra-set rest duration during the flywheel quarter-squat exercise from sessions 1 to 4. * = significantly greater than day 1 (<span class="html-italic">p</span> ≤ 0.05); ● = significantly less than day 1 (<span class="html-italic">p</span> ≤ 0.05); # = significantly less than day 1 (<span class="html-italic">p</span> ≤ 0.001); ^ = significantly less than the result from set 2 (<span class="html-italic">p</span> ≤ 0.05); ◊ = significantly less than the result from set 2 (<span class="html-italic">p</span> ≤ 0.001); ∇ = significantly less than the result from set 3 (<span class="html-italic">p</span> ≤ 0.05).</p> Full article ">Figure 3
<p>Inter-day inter-set mean power (MP), peak concentric power (PP<sub>con</sub>), and peak eccentric (PP<sub>ecc</sub>) output (watts) by intra-set rest duration during the flywheel quarter-squat exercise from sessions 1 to 4. * = significantly greater than day 1 (<span class="html-italic">p</span> ≤ 0.05); # = significantly greater than day 1 (<span class="html-italic">p</span> ≤ 0.001); ^ = significantly less than the result from set 2 (<span class="html-italic">p</span> ≤ 0.05); ° = significantly greater than the result from set 3 (<span class="html-italic">p</span> ≤ 0.001).∇ = significantly less than the result from set 3 (<span class="html-italic">p</span> ≤ 0.05).</p> Full article ">Figure 4
<p>A comparison of the intra-set rest intervals (15 s (black), 30 s (grey), and 45 s (white)) by the eccentric overload generated from peak concentric and eccentric outputs (watts) for the Romanian deadlift and quarter-squat exercise (* <span class="html-italic">p</span> = 0.05; ** <span class="html-italic">p</span> < 0.001).</p> Full article ">
<p>Study design for intra-set rest duration intervention.</p> Full article ">Figure 2
<p>Inter-day inter-set mean power (MP), peak concentric power (PP<sub>con</sub>), and peak eccentric (PP<sub>ecc</sub>) output (watts) by intra-set rest duration during the flywheel quarter-squat exercise from sessions 1 to 4. * = significantly greater than day 1 (<span class="html-italic">p</span> ≤ 0.05); ● = significantly less than day 1 (<span class="html-italic">p</span> ≤ 0.05); # = significantly less than day 1 (<span class="html-italic">p</span> ≤ 0.001); ^ = significantly less than the result from set 2 (<span class="html-italic">p</span> ≤ 0.05); ◊ = significantly less than the result from set 2 (<span class="html-italic">p</span> ≤ 0.001); ∇ = significantly less than the result from set 3 (<span class="html-italic">p</span> ≤ 0.05).</p> Full article ">Figure 3
<p>Inter-day inter-set mean power (MP), peak concentric power (PP<sub>con</sub>), and peak eccentric (PP<sub>ecc</sub>) output (watts) by intra-set rest duration during the flywheel quarter-squat exercise from sessions 1 to 4. * = significantly greater than day 1 (<span class="html-italic">p</span> ≤ 0.05); # = significantly greater than day 1 (<span class="html-italic">p</span> ≤ 0.001); ^ = significantly less than the result from set 2 (<span class="html-italic">p</span> ≤ 0.05); ° = significantly greater than the result from set 3 (<span class="html-italic">p</span> ≤ 0.001).∇ = significantly less than the result from set 3 (<span class="html-italic">p</span> ≤ 0.05).</p> Full article ">Figure 4
<p>A comparison of the intra-set rest intervals (15 s (black), 30 s (grey), and 45 s (white)) by the eccentric overload generated from peak concentric and eccentric outputs (watts) for the Romanian deadlift and quarter-squat exercise (* <span class="html-italic">p</span> = 0.05; ** <span class="html-italic">p</span> < 0.001).</p> Full article ">
Open AccessArticle
Visceral Fat Affects Heart Rate Recovery but Not the Heart Rate Response Post-Single Bout of Vigorous Exercise: A Cross-Sectional Study in Non-Obese and Healthy Participants
by
Alessandra Amato, Luca Petrigna, Martina Sortino and Giuseppe Musumeci
Sports 2024, 12(12), 323; https://doi.org/10.3390/sports12120323 - 27 Nov 2024
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Body composition could influence exercise physiology. However, no one has ever studied the effect of visceral fat (VF) on heart rate (HR) trends during and after exercise by using bioimpedance analysis (BIA). This study aims to investigate BIA variables as predictors of HR
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Body composition could influence exercise physiology. However, no one has ever studied the effect of visceral fat (VF) on heart rate (HR) trends during and after exercise by using bioimpedance analysis (BIA). This study aims to investigate BIA variables as predictors of HR trends during vigorous exercise. Ninety-six participants (age 22.5 ± 4.8 years) were included in the data analysis. After performing BIA, the HR was recorded at three time points: baseline HR (BHR), peak HR (PHR) at the end of vigorous exercise, and resting HR (RHR) 1 min after the end of the exercise. After BHR, a 30 s squat jump test was performed. Linear regression analysis showed the body fat percentage and VF as a predictor of HR recovery post-exercise (p < 0.01). However, body weight has no association with HR recovery (p > 0.05). On the other hand, BIA variables were not associated with the variation of HR from the baseline to the end of the exercise. The results show that higher VF is associated with a slower HR recovery. To schedule a training program, it would be safer to monitor visceral fat before prescribing recovery time.
Full article
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<p>Study design and timeline. BIA: bioimpedance analysis; BHR: baseline heart rate; SJT: squat jump test; PHR: peak heart rate; RHR: resting heart rate.</p> Full article ">Figure 2
<p>Picture of the bioimpedance meter “MC-780A TANITA” used for the study.</p> Full article ">Figure 3
<p>Picture of the heart rate monitor “Polar <sup>®</sup> OH1” used for the study.</p> Full article ">Figure 4
<p>Flow chart representing the recruitment process.</p> Full article ">Figure 5
<p>Regression variable plot. Dependent variable HRR was plotted against each variable, VFr (<b>a</b>) and BF (<b>b</b>), that resulted as significant predictors; In this scatter plot, each dot represents a participant tested HRR: heart rate recovery; VFr: visceral fat rating scale; BF: body fat percentage.</p> Full article ">
<p>Study design and timeline. BIA: bioimpedance analysis; BHR: baseline heart rate; SJT: squat jump test; PHR: peak heart rate; RHR: resting heart rate.</p> Full article ">Figure 2
<p>Picture of the bioimpedance meter “MC-780A TANITA” used for the study.</p> Full article ">Figure 3
<p>Picture of the heart rate monitor “Polar <sup>®</sup> OH1” used for the study.</p> Full article ">Figure 4
<p>Flow chart representing the recruitment process.</p> Full article ">Figure 5
<p>Regression variable plot. Dependent variable HRR was plotted against each variable, VFr (<b>a</b>) and BF (<b>b</b>), that resulted as significant predictors; In this scatter plot, each dot represents a participant tested HRR: heart rate recovery; VFr: visceral fat rating scale; BF: body fat percentage.</p> Full article ">
Open AccessArticle
Influence of Body Composition and Muscle Power Performance on Multiple Frequency Speed of Kick Test in Taekwondo Athletes
by
Gennaro Apollaro, Marco Panascì, Ibrahim Ouergui, Coral Falcó, Emerson Franchini, Piero Ruggeri and Emanuela Faelli
Sports 2024, 12(12), 322; https://doi.org/10.3390/sports12120322 - 27 Nov 2024
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The Multiple Frequency Speed of Kick Test (FSKTmult) is used to investigate which characteristics are necessary for, contribute to, or limit the ability to repeat high-intensity intermittent efforts in taekwondo. This cross-sectional study investigated the relationship between anthropometric and body composition
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The Multiple Frequency Speed of Kick Test (FSKTmult) is used to investigate which characteristics are necessary for, contribute to, or limit the ability to repeat high-intensity intermittent efforts in taekwondo. This cross-sectional study investigated the relationship between anthropometric and body composition characteristics, muscle power performance, and sport-specific anaerobic performance. Nineteen black belt taekwondo athletes (mean ± SD age: 17.2 ± 2.4 years) volunteered to participate. Anthropometric and body composition characteristics (i.e., body height (BH), body mass (BM), fat mass (FM), body fat (BF%), and muscle mass (MM)) and physical performance (squat jump (SJ), countermovement jump (CMJ) tests, and FSKTmult) were assessed. Data were analyzed with correlation coefficients and simple linear regression. The statistical significance was set at p < 0.05. The total number of kicks in FSKTmult (FSKTtotal) was significantly and positively correlated with MM (r = 0.521, R2 = 0.27, p < 0.05) and negatively with BF% (r = −0.499, R2 = 0.25, p < 0.05). The FSKTtotal was significantly and positively correlated with SJ (r = 0.520, R2 = 0.27, p < 0.05) and CMJ (r = 0.508, R2 = 0.26, p < 0.05) performance. Body composition optimization, with appropriate physical training and dietary planning, is relevant in taekwondo as the improvement in the ability to repeat high-intensity intermittent efforts depends on MM, and its worsening on BF%. Lower limb muscle power positively influences the ability to repeat high-intensity intermittent efforts. Therefore, training programs should emphasize ballistic and plyometric exercises.
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Open AccessArticle
Evolution of Key Factors Influencing Performance Across Phases in Junior Short Sprints
by
Kyosuke Oku, Yoshihiro Kai, Hitoshi Koda, Megumi Gonno, Maki Tanaka, Tomoyuki Matsui, Yuya Watanabe, Toru Morihara and Noriyuki Kida
Sports 2024, 12(12), 321; https://doi.org/10.3390/sports12120321 - 27 Nov 2024
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Sprint performance plays a crucial role in various sports. Short sprints vary depending on the size of the court/playing field and on competitive characteristics, but are common in many sports. Although the relationship between age and muscle strength has been explored in short
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Sprint performance plays a crucial role in various sports. Short sprints vary depending on the size of the court/playing field and on competitive characteristics, but are common in many sports. Although the relationship between age and muscle strength has been explored in short sprints, there is limited understanding of how various physical factors interact, particularly concerning differences in the acceleration phase. This study examined the relationship between sprint times at 0–2.5 m, 2.5–5 m, and 5–10 m intervals and various factors (body composition, flexibility, muscle strength, physical fitness) in junior athletes (13 boys; 13 girls; average age 11.37 ± 1.30 years; 7 in badminton, 8 in fencing, 5 in rowing, and 6 in climbing). The sprint time was measured using four timing lights at 0 m (start point), 2.5 m, 5 m, and 10 m (finish point). The results indicated that sprint times increased with age, and is correlated with muscle strength and flexibility. A partial correlation analysis showed that faster times in the 0–2.5 m interval were associated with higher hip flexibility (right: r = −0.42, p = 0.035; left: r = −0.60, p = 0.001); in the 2.5–5 m interval, faster times were associated with higher core flexibility (right: r = −0.34, p = 0.091; left: r = −0.40, p = 0.046); and in the 5–10 m interval, a relationship with standing long jump performance was confirmed (r = −0.56, p = 0.003). Furthermore, a lower fat-free body weight translated to higher performance (0–2.5 m: r = 0.40, p = 0.047; 2.5 m: r = 0.37, p = 0.071; 5–10 m: r = 0.55, p = 0.004). In the acceleration phase of 10 m, flexibility immediately after the start and the subsequent horizontal propulsive force are important factors that are strongly related to performance change in each interval. These results emphasize that even over a short distance such as 10 m, the factors influencing performance can change significantly. This highlights the importance of overall flexibility, propulsive power and body fat regulation in junior short sprinters, as well as the need for daily training carefully tailored to the specific sprint distances required in each sport.
Full article
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Open AccessArticle
Diurnal Variations in Upper and Lower Body Power in Adolescent Volleyball Players: Exploring Time-of-Day Effects on Performance
by
Nebojša Trajković, Vladan Milić, Tomislav Đurković, Tomica Rešetar and Georgiy Korobeynikov
Sports 2024, 12(12), 320; https://doi.org/10.3390/sports12120320 - 26 Nov 2024
Abstract
Background/Objectives: This study aims to investigate the daily variations in upper and lower body power performance in adolescent volleyball players. Methods: The sample consisted of 50 young male volleyball players (14.12 ± 0.8 years), actively involved in regular training and competition. Players were
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Background/Objectives: This study aims to investigate the daily variations in upper and lower body power performance in adolescent volleyball players. Methods: The sample consisted of 50 young male volleyball players (14.12 ± 0.8 years), actively involved in regular training and competition. Players were tested for vertical jump tests and medicine ball throws twice, once in the morning (8:00–9:30 h) and once in the evening (18:00–19:30 h). Results: Significant differences (p < 0.05; ES = 0.35–0.42) in vertical jump were observed when comparing the morning and evening performance except for counter movement jump with arm swing, where there were no significant differences (p = 0.21). The results for the upper body power tests revealed a significant difference only in the standing medicine ball throw (p = 0.05; ES = 0.35). There were no significant differences in lying and seated medicine ball throw (p > 0.05). Conclusions: This study demonstrated that lower body power, manifested in vertical jump performance, was significantly better in the evening compared to the morning. For upper body assessments, the standing medicine ball throw appears more reflective of volleyball-specific movements, while the lying and sitting throw may be less applicable. These findings suggest that volleyball training and testing, especially for leg power, may be more effective later in the day, while upper body performance appears less affected by time.
Full article
(This article belongs to the Special Issue Promoting and Monitoring Physical Fitness in All Contexts)
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Open AccessArticle
Levels of Stress in Volleyball Referees During Official Matches—The Influence of the Referee Role and Level of Competition
by
Zoran Nikolovski, Dario Vrdoljak, Nikola Foretić, Mia Perić, Vladimir Pavlinović, Ratko Perić and Vuk Karanović
Sports 2024, 12(12), 319; https://doi.org/10.3390/sports12120319 - 26 Nov 2024
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Volleyball referees, as athletes and staff members, are exposed to different stress levels which can be determined by measuring pre- and post-match levels of salivary cortisol (C) and alpha-amylase (AA). This study aimed to determine the dynamics of stress biomarkers in referees during
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Volleyball referees, as athletes and staff members, are exposed to different stress levels which can be determined by measuring pre- and post-match levels of salivary cortisol (C) and alpha-amylase (AA). This study aimed to determine the dynamics of stress biomarkers in referees during official volleyball matches and the connection to the roles or level of competition. The participants in this study were nine international volleyball referees (three females and six males) with a mean chronological age of 48.23 ± 2.31 years. In this study, saliva samples were collected during 24 official matches during the European championship for senior women’s teams (Eurovolley 2021). The AA activity and C concentrations were determined from saliva samples. When the referees’ roles were assessed in line with their duties, the first referees’ salivary C levels showed a significant increase between the pre- and post-match measurements (p = 0.01), while in the second referees remained low. The reserve and challenge referees demonstrated a significant drop in their C concentrations (p = 0.00 and p = 0.02, respectively). Additionally, when assessing AA which accounts for the responsibilities of referees and the intensity of competition, the first (p = 0.06 and p = 0.07) and second referees (p = 0.01 and p = 0.00) showed an increase between the pre- and post-match measurements, respectively. At the same time, the AA activity did not show any significant change concerning the reserve and challenge referees. Our results indicate that referees’ roles and the level of competition may cause higher responses in “active referee roles”—mainly the first and second referees—while reserve and challenge referees showed no increase or even a decrease in the measured biomarkers. The observed changes in the stress markers can be explained by psychological or emotional effects and are dependent on the level of competition and the role referees are fulfilling.
Full article
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Open AccessArticle
Characterization of the External Load of Soccer Goalkeepers Depending on the Category and Sports Context
by
Víctor Hernández-Beltrán, Boryi A. Becerra-Patiño, Abian Perdomo-Alonso, Jesús Barguerias-Martínez, Sergio Gómez-Carrero, Mário C. Espada and José M. Gamonales
Sports 2024, 12(12), 318; https://doi.org/10.3390/sports12120318 - 26 Nov 2024
Abstract
Background/Objectives: Studies focused on the soccer goalkeeper position in training and official matches are scarce. The present study aimed to analyze the external load during training sessions and official matches in semi-professional goalkeepers. Methods: Data from goalkeepers (n = 6) from the youth
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Background/Objectives: Studies focused on the soccer goalkeeper position in training and official matches are scarce. The present study aimed to analyze the external load during training sessions and official matches in semi-professional goalkeepers. Methods: Data from goalkeepers (n = 6) from the youth ranks of a professional team belonging to the first Spanish soccer league have been used. The sample is made up of a total of 758 data collected during all the training and competitions carried out by the analyzed teams that made up the squad during the 2021/2022 and 2022/2023 seasons. A descriptive and inferential analysis was carried out based on the category (Youth B or Youth C) and the sports context (training or competition). Results: The results showed significant differences depending on the category (average time to feet left, average time to feet right, total jumps, total dives, total left dives, total right dives, high metabolic load distance (HMLD), and high metabolic power efforts (HMPE)), and the sport context (average time to feet right, total jumps, total dives, total left dives, total right dives, total distance, distance 18–21 km/h, distance 21–24 km/h, Dec 2–3, efforts, and HMLD). Conclusions: The EL of the GKs shows differences regarding the category and the context. Therefore, it is necessary to analyze and determine the threshold of each player considering different variables related to the external and internal load to individualize the training tasks and prevent injuries due to overload.
Full article
Open AccessArticle
Biomechanical Insights in Ancient Greek Combat Sports: A Static Analysis of Selected Pottery Depictions
by
Andreas Bourantanis, Nikitas Nomikos and Weijie Wang
Sports 2024, 12(12), 317; https://doi.org/10.3390/sports12120317 - 26 Nov 2024
Abstract
Background: Though ancient Greece preserves many pictures of combat sports, there is limited research in terms of biomechanical analysis of their sports. This research aimed to investigate the Pankration postures of ancient Greek athletics, expecting to bridge the gap between historical sports practices
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Background: Though ancient Greece preserves many pictures of combat sports, there is limited research in terms of biomechanical analysis of their sports. This research aimed to investigate the Pankration postures of ancient Greek athletics, expecting to bridge the gap between historical sports practices and contemporary biomechanical applications. Methods: This study employed computer vision (OpenPose) to analyze two images, one as readiness and another as kicking postures, from ancient Greek Pankration by constructing a static multi-segmental model. Using Newton’s Laws, the models simulated the postures as presented in historical depictions, estimated joint forces and moments, and calculated weight distribution and ground reaction forces for these postures. Results: For the readiness posture, it was found that the right hind leg experienced significant forces, with the highest moment at the knee joint, while the ankle and hip joints showed similar slightly lower moments. The front leg encountered lower forces and moments. For the kick posture, the supporting leg experienced the highest moment at the knee, while the kicking leg showed minimal moments at the ankle, knee, and hip. Conclusions: The static analysis provided quantitative estimates of joint forces and moments in the depicted Pankration postures, suggesting that these postures were biomechanically effective for their intended functions in combat. While the analysis cannot confirm whether ancient athletes deliberately applied biomechanical principles, the results highlight the potential of biomechanical modeling to enhance our understanding of ancient sports practices. The research demonstrates the possible benefits of integrating static analysis with historical elements to study the physical demands and techniques of ancient combat sports.
Full article
(This article belongs to the Special Issue Biomechanics and Sports Performances)
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Figure 1
Figure 1
<p>A typical readiness posture of ancient Greek athletes in combat. The image depicts an athlete engaged in the ancient Greek sport of Pankration, as illustrated on a red-figure amphora housed in the Staatliche Antikensammlungen Museum in Munich, Germany [<a href="#B24-sports-12-00317" class="html-bibr">24</a>].</p> Full article ">Figure 2
<p>The final posture presents an athlete who receives a kick, possibly aimed at the opponent’s abdomen area. The present illustrates a scene of a Pankration match depicted on a black-figure amphora from the classical period (5th century BCE) [<a href="#B24-sports-12-00317" class="html-bibr">24</a>].</p> Full article ">Figure 3
<p>Modified foot position emphasizing the heel strike. The altered foot orientation is consistent with ancient textual descriptions of defensive maneuvers, as exemplified by the attacker–defender interaction depicted in <a href="#sports-12-00317-f002" class="html-fig">Figure 2</a>.</p> Full article ">Figure 4
<p>Biomechanical model of lower limbs in the sagittal plane, used for calculating ground reaction forces. The model was used to estimate the ground reaction forces (GRFs). The model consisted of seven segments: two thighs, two shanks, two feet, and the pelvis (represented by the horizontal rectangle connecting the limbs).</p> Full article ">Figure 5
<p>Biomechanical model of the lower limbs in the sagittal plane, adjusted for calculating ground reaction forces across different postures. The model, consisting of seven segments—two thighs, two shanks, two feet, and the pelvis (represented by the horizontal rectangle connecting the limbs)—was used to estimate ground reaction forces (GRF) while accounting for variations in posture, joint angles, and load distribution. The left free body diagram (<b>a</b>) represents the initial posture found in <a href="#sports-12-00317-f001" class="html-fig">Figure 1</a> while the right (<b>b</b>) corresponds to <a href="#sports-12-00317-f002" class="html-fig">Figure 2</a>. It is important to note that, due to the kick facing the opposite direction compared to the readiness posture, the reference system has been adjusted to align with the depictions. Specifically, while the negative sign in the readiness posture indicates clockwise moments, this convention is reversed in the second depiction, where the negative sign now represents a counterclockwise moment.</p> Full article ">Figure 6
<p>Diagram illustrating the equilibrium of forces on the foot. The figure is a free body diagram that presents the lever arms in vector form, along with the forces and moments acting on the respective segment, i.e., the foot.</p> Full article ">Figure 7
<p>Representation of lower leg forces from ankle to knee, showing equilibrium conditions.</p> Full article ">Figure 8
<p>Analysis of the femur demonstrating force and moment equilibrium, as forces are transmitted from the knee to the hip joint.</p> Full article ">Figure 9
<p>Vertical forces on lower extremity joints during “readiness” static posture and kick posture highlight differences in force distribution between the right and left legs. Since the vertical forces were calculated, it is clear that the reactions will have opposite signs. As the weight of each segment is subtracted, the vertical force progressively decreases from the foot up to the hip.</p> Full article ">Figure 10
<p>Joint moments at the ankle, knee, and hip for “readiness” posture (<b>left</b>) and kick posture (<b>right</b>). Positive moments indicate counterclockwise rotation, and negative moments indicate clockwise rotation.</p> Full article ">
<p>A typical readiness posture of ancient Greek athletes in combat. The image depicts an athlete engaged in the ancient Greek sport of Pankration, as illustrated on a red-figure amphora housed in the Staatliche Antikensammlungen Museum in Munich, Germany [<a href="#B24-sports-12-00317" class="html-bibr">24</a>].</p> Full article ">Figure 2
<p>The final posture presents an athlete who receives a kick, possibly aimed at the opponent’s abdomen area. The present illustrates a scene of a Pankration match depicted on a black-figure amphora from the classical period (5th century BCE) [<a href="#B24-sports-12-00317" class="html-bibr">24</a>].</p> Full article ">Figure 3
<p>Modified foot position emphasizing the heel strike. The altered foot orientation is consistent with ancient textual descriptions of defensive maneuvers, as exemplified by the attacker–defender interaction depicted in <a href="#sports-12-00317-f002" class="html-fig">Figure 2</a>.</p> Full article ">Figure 4
<p>Biomechanical model of lower limbs in the sagittal plane, used for calculating ground reaction forces. The model was used to estimate the ground reaction forces (GRFs). The model consisted of seven segments: two thighs, two shanks, two feet, and the pelvis (represented by the horizontal rectangle connecting the limbs).</p> Full article ">Figure 5
<p>Biomechanical model of the lower limbs in the sagittal plane, adjusted for calculating ground reaction forces across different postures. The model, consisting of seven segments—two thighs, two shanks, two feet, and the pelvis (represented by the horizontal rectangle connecting the limbs)—was used to estimate ground reaction forces (GRF) while accounting for variations in posture, joint angles, and load distribution. The left free body diagram (<b>a</b>) represents the initial posture found in <a href="#sports-12-00317-f001" class="html-fig">Figure 1</a> while the right (<b>b</b>) corresponds to <a href="#sports-12-00317-f002" class="html-fig">Figure 2</a>. It is important to note that, due to the kick facing the opposite direction compared to the readiness posture, the reference system has been adjusted to align with the depictions. Specifically, while the negative sign in the readiness posture indicates clockwise moments, this convention is reversed in the second depiction, where the negative sign now represents a counterclockwise moment.</p> Full article ">Figure 6
<p>Diagram illustrating the equilibrium of forces on the foot. The figure is a free body diagram that presents the lever arms in vector form, along with the forces and moments acting on the respective segment, i.e., the foot.</p> Full article ">Figure 7
<p>Representation of lower leg forces from ankle to knee, showing equilibrium conditions.</p> Full article ">Figure 8
<p>Analysis of the femur demonstrating force and moment equilibrium, as forces are transmitted from the knee to the hip joint.</p> Full article ">Figure 9
<p>Vertical forces on lower extremity joints during “readiness” static posture and kick posture highlight differences in force distribution between the right and left legs. Since the vertical forces were calculated, it is clear that the reactions will have opposite signs. As the weight of each segment is subtracted, the vertical force progressively decreases from the foot up to the hip.</p> Full article ">Figure 10
<p>Joint moments at the ankle, knee, and hip for “readiness” posture (<b>left</b>) and kick posture (<b>right</b>). Positive moments indicate counterclockwise rotation, and negative moments indicate clockwise rotation.</p> Full article ">
Open AccessArticle
Quantification of Ground Reaction Forces During the Follow Through in Trained Male Cricket Fast Bowlers: A Laboratory-Based Study
by
Jeffrey Fleming, Corey Perrett, Onesim Melchi, Jodie McClelland and Kane Middleton
Sports 2024, 12(12), 316; https://doi.org/10.3390/sports12120316 - 22 Nov 2024
Abstract
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Ground reaction forces (GRFs) are known to be high during front foot contact of fast bowling deliveries in cricket. There is a lack of published data on the GRFs during follow through foot contacts. The aim of this study was to quantify and
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Ground reaction forces (GRFs) are known to be high during front foot contact of fast bowling deliveries in cricket. There is a lack of published data on the GRFs during follow through foot contacts. The aim of this study was to quantify and compare peak GRFs and impulse of the delivery stride and the follow through of fast bowling deliveries. Ten trained male fast bowlers (ball release speed mean ± SD; 32.6 ± 2.3 m/s) competing in the Men’s Victorian Premier League participated in the study. Peak GRF and impulse data were collected using in-ground force plates in a laboratory setting. Linear mixed modelling of GRFs and impulse showed a significant effect of foot strike (p < 0.001). Front foot contact had the greatest magnitude of peak vertical GRF (5.569 ± 0.334 BW) but was not significantly greater than back foot recontact (4.471 ± 0.285 BW) (p = 0.07). Front foot impact had the greatest vertical impulse (0.408 ± 0.018 BW·s) but was similar to back foot (0.377 ± 0.012 BW·s) and front foot (0.368 ± 0.006 BW·s) recontacts (p = 0.070 to 0.928). The high GRF and impulse during the follow through highlights the need for further kinetic and kinematic research on this phase of the fast bowling delivery.
Full article
Figure 1
Figure 1
<p>Schematic of testing set-up. Set-up 1 was used to collect data for back foot contact (BF1) on force plate 1 (FP1), front foot contact (FF1) on force plate 2 (FP2), and back foot recontact (BF2) on force plate 3 (FP3). Set-up 2 was used to collect data for front foot contact (FF1) on force plate 1 (FP1), back foot recontact (BF2) on force plate 2 (FP2), and front foot recontact (FF2) on force plate 3 (FP3).</p> Full article ">Figure 2
<p>Scatter plot combined with a box plot to illustrate the distribution of the vertical ground reaction force (GRF) data collected at each foot strike. Scatter plot points are colour-coded by participant to aid in visualising both intra-participant and inter-participant variability of the data. Colour coding of participants is consistent across figures. The full width line represents the median of the data. The upper and lower hinges of the boxes represent the first and third quartiles of data, respectively, the whiskers extending to the largest or smallest value no more than 1.5 times the distance between the first and third quartile. To aid in discerning individual data points, a random amount of noise has been added to the x value for each scatter plot point; the y values are unaltered. * Denotes estimated marginal mean of foot strikes are different to at least the 0.05 level.</p> Full article ">Figure 3
<p>Scatter plot combined with a box plot to illustrate the distribution of the vertical impulse data collected at each foot strike. Scatter plot points are colour-coded by participant to aid in visualising both intra-participant and inter-participant variability of the data. Colour coding of participants is consistent across figures. The full width line represents the median of the data. The upper and lower hinges of the boxes represent the first and third quartiles of data, respectively, the whiskers extending to the largest or smallest value no more than 1.5 times the distance between the first and third quartile. To aid in discerning individual data points a random amount of noise has been added to the x value for each scatter plot point, the y values are unaltered. * Denotes estimated marginal mean of foot strikes are different to at least the 0.05 level.</p> Full article ">
<p>Schematic of testing set-up. Set-up 1 was used to collect data for back foot contact (BF1) on force plate 1 (FP1), front foot contact (FF1) on force plate 2 (FP2), and back foot recontact (BF2) on force plate 3 (FP3). Set-up 2 was used to collect data for front foot contact (FF1) on force plate 1 (FP1), back foot recontact (BF2) on force plate 2 (FP2), and front foot recontact (FF2) on force plate 3 (FP3).</p> Full article ">Figure 2
<p>Scatter plot combined with a box plot to illustrate the distribution of the vertical ground reaction force (GRF) data collected at each foot strike. Scatter plot points are colour-coded by participant to aid in visualising both intra-participant and inter-participant variability of the data. Colour coding of participants is consistent across figures. The full width line represents the median of the data. The upper and lower hinges of the boxes represent the first and third quartiles of data, respectively, the whiskers extending to the largest or smallest value no more than 1.5 times the distance between the first and third quartile. To aid in discerning individual data points, a random amount of noise has been added to the x value for each scatter plot point; the y values are unaltered. * Denotes estimated marginal mean of foot strikes are different to at least the 0.05 level.</p> Full article ">Figure 3
<p>Scatter plot combined with a box plot to illustrate the distribution of the vertical impulse data collected at each foot strike. Scatter plot points are colour-coded by participant to aid in visualising both intra-participant and inter-participant variability of the data. Colour coding of participants is consistent across figures. The full width line represents the median of the data. The upper and lower hinges of the boxes represent the first and third quartiles of data, respectively, the whiskers extending to the largest or smallest value no more than 1.5 times the distance between the first and third quartile. To aid in discerning individual data points a random amount of noise has been added to the x value for each scatter plot point, the y values are unaltered. * Denotes estimated marginal mean of foot strikes are different to at least the 0.05 level.</p> Full article ">
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