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[This corrects the article DOI: 10.3389/fpsyg.2023.1048642.].
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Coaches and psychologists can use time-motion analysis to elaborate specific interventions for female BJJ athletes, increasing specific training context and reducing unnecessary psychological and physical demands and injuries. Therefore, the present study aimed to analyze high-level BJJ female athletes in the 2020 Pan-American Games by comparing the weight categories on the time-motion analysis. The time-motion analysis (i.e., approach, gripping, attack, defensive actions, transition, mounting, guard, side control, and submissions) of 422 high-level female BJJ combats was divided and compared by weight category as follows: Rooster (n = 8), Light Feather (n = 18), Feather (n = 122), Light (n = 84), Middle (n = 74), Medium Heavy (n = 44), Heavy (n = 36), Super Heavy (n = 36), using p ≤ 0.05. The main results indicated that the Super heavyweight category [3.1 (5.8;119.9) s] had a shorter gripping time than other weight categories, p ≤ 0.05. In contrast, roosters [7.2 (3.5;64.6) s] had longer gripping, transition [14.0 (4.8;29.6) s], and attack time [76.2 (27.7, 93.2)] than the light feather, middlers, and heavier weight categories, p ≤ 0.05. These findings should be considered for the psychological interventions and training prescription.
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This research study verified the technical-tactical actions during the mixed martial arts (MMA) fights to generate serious enough injury to stop the MMA round, determining technical-tactical potential risk factors for injury in official MMA combats, according to Concussion or Resignation per Submission. A total of 990 rounds with concussions and 627 resignations per submission were considered with severe injury (i.e., a fight ended by a doctor or referee). All injuries were diagnosed and managed by attending ringside physicians during the MMA fights and rounds and had a continuous technical-tactical behavior analysis, p ≤ 0.05. The leading cause of concussion was due to head trauma (~90%), with higher dependence on head strikes scored actions. Comparisons between Concussion and Resignation per Submission combats demonstrated differences between distance head strikes actions [13(6,25) vs. 9(4,18) frequencies], clinch head strikes actions [1(0;4) vs. 1(0;3) frequencies], ground head strikes actions [1(0;8) vs. 2(0;10) frequencies] and takedowns actions [0(0;1) vs. 1(0;2) frequencies]. This information may provide significant evidence regarding the doctor stoppage in concussion combats and when it could be called by officials supervising MMA.
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This study aimed to synthesize literature data on male judo combat time in international competitions between 2010 and 2019. The search was carried out from May 8th to June 11th, 2021, in electronic databases using the following keywords: ("technical-tactical" OR "time motion" OR "combat time") AND ("judo" OR "combat sports" OR "martial arts"). After the selection process, 8 articles were included in the systematic review and 7 in the meta-analysis. These studies analyzed 2,562 international male judo combats over the years 2010-2019. We observed that the average male judo combat time changed (2010 = 202.8; 2011-2012 = 304.8; 2016 = 237.4; 2018-2019 = 189.8 s) after each rule change (2010, 2013, 2017, and 2018). There was a significant difference between combats that ended up to the regular time and those that needed overtime (Golden Score: 2013 = 3% vs. 2018-2019 = 21%; p = 0.03). There were differences between 60 kg (p ≤ 0.019) and + 100 kg (p ≤ 0.04) categories and the others in 2011-2012. However, no significant difference was found between the combat time by weight division after the 2017 rule changes, although there are still differences in relation to the end of the combats (p < 0.001). There were significant changes in the male judo combat time with each rule change (2010, 2013, 2017, and 2018), and the data from the included studies point to a trend of homogeneity in the combat time spent between the weight divisions over the years, and an increase in the occurrence of Golden Score. More studies need to be carried out to identify the new temporal behaviors of athletes.
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In this study, we explore a 100 years of Work and Organizational Psychology (WOP). To do this, we carry out a bibliometric performance and network analysis (BPNA) to understand the evolution structure and the most important themes in the field of study. To perform the BNPA, 8,966 documents published since 1919 were exported from the Web of Science and Scopus databases. The SciMAT software was used to process data and to create the evolution structure, the strategic diagram, and the thematic network structure of the strategic themes of the field of WOP. We identified 29 strategic clusters and discuss the most important themes (motor themes) and their relationship with other clusters. This research presents the complete evolution of the field of study, identifying emerging themes and others with a high degree of development. We hope that this work will support researchers and future research in the field of WOP.
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The purpose of the study was to investigate the sensitivity of an alternative maximal accumulated oxygen deficit (MAODALT) method to discriminate the "anaerobic" capacity while comparing: least trained (LT) participants (n = 12), moderately trained (MT) participants (n = 12), endurance trained (ET) participants (n = 16), and rugby (RG) players (n = 11). Participants underwent a graded exercise test on a treadmill and a supramaximal effort for assessing MAODALT. MAODALT was calculated as the sum of oxygen equivalents from the phosphagen and glycolytic metabolic pathways. MAODALT was significantly higher (P < 0.05) in RG (64.4 ± 12.1 mL · kg-1) than in ET (56.8 ± 5.4 mL · kg-1; effect size [ES] = 0.77; +13.5%), MT (53.8 ± 5.3 mL · kg-1; ES = 1.08; +19.8%), and LT (49.9 ± 4.5 mL · kg-1; ES = 1.50; +36.4%). In addition, the magnitude-based inference analysis revealed that MAODALT was likely (LT vs. MT), very likely (MT vs. RG, and ET vs. RG) and most likely (LT vs. ET, and LT vs. RG) different between all groups, except for MT and ET, which presented an unclear difference. In conclusion, MAODALT was sensitive enough to distinguish the "anaerobic" capacity in individuals with different training status, especially for RG players compared with LT participants and MT participants.