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1
Burgess, Darren J. "The Research Doesn’t Always Apply: Practical Solutions to Evidence-Based Training-Load Monitoring in Elite Team Sports." International Journal of Sports Physiology and Performance 12, s2 (April 2017): S2–136—S2–141. http://dx.doi.org/10.1123/ijspp.2016-0608.
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Research describing load-monitoring techniques for team sport is plentiful. Much of this research is conducted retrospectively and typically involves recreational or semielite teams. Load-monitoring research conducted on professional team sports is largely observational. Challenges exist for the practitioner in implementing peer-reviewed research into the applied setting. These challenges include match scheduling, player adherence, manager/coach buy-in, sport traditions, and staff availability. External-load monitoring often attracts questions surrounding technology reliability and validity, while internal-load monitoring makes some assumptions about player adherence, as well as having some uncertainty around the impact these measures have on player performance This commentary outlines examples of load-monitoring research, discusses the issues associated with the application of this research in an elite team-sport setting, and suggests practical adjustments to the existing research where necessary.
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Hartwig, Timothy B., Geraldine Naughton, and John Searl. "Defining the Volume and Intensity of Sport Participation in Adolescent Rugby Union Players." International Journal of Sports Physiology and Performance 3, no. 1 (March 2008): 94–106. http://dx.doi.org/10.1123/ijspp.3.1.94.
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Purpose:Investigating adolescent training loads might help us understand optimal training adaptations. GPS tracking devices and training diaries were used to quantify weekly sport and other physical activity demands placed on adolescent rugby union players and profile typical rugby training sessions.Methods:Participants were 75 males age 14 to 18 y who were recruited from rugby teams representing 3 levels of participation: schoolboy, national representative, and a selective sports school talent squad.Results:Schoolboy players covered a distance of (mean ± SD) 3511 ± 836 m, representative-squad players 3576 ± 956 m, and talent-squad players 2208 ± 637 m per rugby training session. The representative squad recorded the highest weekly duration of sport and physical activity (515 ± 222 min/wk), followed by the talent squad (421 ± 211 min/week) and schoolboy group (370 ± 135 min/wk). Profiles of individual players identified as group outliers showed participation in up to 3 games and up to 11 training sessions per week, with twice the weekly load of the team averages.Conclusion:Optimal participation and performance of adolescent rugby union players might be compromised by many high-load, high-impact training sessions and games and commitments to other sports and physical activities. An improved understanding of monitoring and quantifying load in adolescent athletes is needed to facilitate best-practice advice for player management and training prescription.
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Marques Junior, Nelson Kautzner. "Periodization models used in the current sport." MOJ Sports Medicine 4, no. 2 (April 22, 2020): 27–34. http://dx.doi.org/10.15406/mojsm.2020.04.00090.
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Traditional periodization has some characteristics that are the individualization of the training load, training load response based on biological laws and most of these models have the objective of the athlete archive the peak. The contemporary periodization has the following characteristics: individualized training load with monitoring of the physiological adaptation, training of the specific motor capacities of the modality, use of the evolution time and of the residual training effect for the coach prescribes the session, much attention with technical and tactical training and attention in the training with the injury level. Which periodization (traditional and contemporary) models are indicated to be used in contemporary sports? The objective of the review was to determining the types of periodization (traditional and contemporary) for each sport (individual, team, and combat). Traditional periodization has four types of periodization for the coach prescribes the training. The periodization models are the traditional periodization of Matveev, the pendular periodization of Arosiev and Kalinin, the high load system of Vorobiev and the periodization of the structural scheme of high-intensity loads of Tschiene. Contemporary periodization are for the individual sport (block periodization, individualized periodization and ATR periodization), a model for the individualized and collective sports (periodization of the structural bells), five periodization for the collective sports games (periodization of long-form state, microstructure periodization, tactical periodization, non-linear periodization and selective load periodization) and a model for the volleyball (specific periodization for the volleyball). In conclusion, the coach that knows the periodization has more probability of success during a championship.
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Duggan, John D., Jeremy A. Moody, Paul J. Byrne, Stephen-Mark Cooper, and Lisa Ryan. "Training Load Monitoring Considerations for Female Gaelic Team Sports: From Theory to Practice." Sports 9, no. 6 (June 5, 2021): 84. http://dx.doi.org/10.3390/sports9060084.
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Athlete monitoring enables sports science practitioners to collect information to determine how athletes respond to training loads (TL) and the demands of competition. To date, recommendations for females are often adapted from their male counterparts. There is currently limited information available on TL monitoring in female Gaelic team sports in Ireland. The collection and analysis of female athlete monitoring data can provide valuable information to support the development of female team sports. Athletic monitoring can also support practitioners to help minimize risk of excessive TL and optimize potential athletic performance. The aims of this narrative review are to provide: (i) an overview of TL athlete monitoring in female team sports, (ii) a discussion of the potential metrics and tools used to monitor external TL and internal TL, (iii) the advantages and disadvantages of TL modalities for use in Gaelic team sports, and (iv) practical considerations on how to monitor TL to aid in the determination of meaningful change with female Gaelic team sports athletes.
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Kellmann, Michael, Dieter Altenburg, Werner Lormes, and Jürgen M. Steinacker. "Assessing Stress and Recovery during Preparation for the World Championships in Rowing." Sport Psychologist 15, no. 2 (June 2001): 151–67. http://dx.doi.org/10.1123/tsp.15.2.151.
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Training stress and adequate recovery have been identified as important factors to enhance performance in sports and to avoid overtraining. Research dealing with training monitoring and overtraining is mostly based on the Profile of Mood Stales (POMS). Recently, Kellmann and Kallus (2000, 2001) published the Recovery-Stress-Questionnaire for Athletes (RESTQ-Sport), which assesses training effects from the perspective of stress and recovery. During a six-week training camp before and at the World Championships, 24 female and 30 male rowers of the German Junior National Rowing Team completed the RESTQ-Sport and the POMS six times. Results of selected MANOVA’s revealed significant increases of stress and decreases of recovery when training load expands, and vice versa. Changes in mood, creatine kinase, and ergometer performance reflect the alteration and success of training. These results suggest that the RESTQ-Sport is a potential alternative to the POMS in evaluating the impact of various training schedules.
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Ritchie, Dean, Will G. Hopkins, Martin Buchheit, Justin Cordy, and Jonathan D. Bartlett. "Quantification of Training and Competition Load Across a Season in an Elite Australian Football Club." International Journal of Sports Physiology and Performance 11, no. 4 (May 2016): 474–79. http://dx.doi.org/10.1123/ijspp.2015-0294.
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Purpose:Load monitoring in Australian football (AF) has been widely adopted, yet team-sport periodization strategies are relatively unknown. The authors aimed to quantify training and competition load across a season in an elite AF team, using rating of perceived exertion (RPE) and GPS tracking.Methods:Weekly totals for RPE and GPS loads (including accelerometer data; PlayerLoad) were obtained for 44 players across a full season for each training modality and for competition. General linear mixed models compared mean weekly load between 3 preseason and 4 in-season blocks. Effects were assessed with inferences about magnitudes standardized with between-players SD.Results:Total RPE load was most likely greater during preseason, where the majority of load was obtained via skills and conditioning. There was a large reduction in RPE load in the last preseason block. During in-season, half the total load came from games and the remaining half from training, predominantly skills and upper-body weights. Total distance, high-intensity running, and PlayerLoad showed large to very large reductions from preseason to in-season, whereas changes in mean speed were trivial across all blocks. All these effects were clear at the 99% level.Conclusions:These data provide useful information about targeted periods of loading and unloading across different stages of a season. The study also provides a framework for further investigation of training periodization in AF teams.
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Lyakh, Vladimir, Kazimierz Mikołajec, Przemysław Bujas, Zbigniew Witkowski, Tomasz Zając, Ryszard Litkowycz, and Damian Banyś. "Periodization in Team Sport Games - A Review of Current Knowledge and Modern Trends in Competitive Sports." Journal of Human Kinetics 54, no. 1 (December 1, 2016): 173–80. http://dx.doi.org/10.1515/hukin-2016-0053.
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AbstractThe main goal of this study was to present a review of current knowledge and modern trends in periodization of the training process in team sports. The research objectives were: an analysis of various aspects of periodization of the annual training cycle for elite athletes practicing team sport games, an attempt to determine both the examined and unexamined issues related with periodization of training as well as to indicate directions for further research, and finally, presentation of different training loads and competitions in micro-, meso- and macrocycles. The research consisted of the analysis and generalization of the bibliography, methods of monitoring training and competition loads of the Polish national U17 female soccer team in the seasons 2011/2012 and 2012/2013, as well as of the female basketball division one club in the season 2014/2015. Findings of the present study indicate resolved as well as unresolved aspects of annual training cycle periodization in team sport games and provide information on the types of training and competitive workload planning in micro-, meso- and macrocycles.
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Svilar, Luka, and Igor Jukić. "Load monitoring system in top-level basketball team." Kinesiology 50, no. 1 (2018): 25–33. http://dx.doi.org/10.26582/k.50.1.4.
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The study aimed to describe and compare the external training load, monitored using microtechnology, with the internal training load, expressed as the session rating of perceived exertion (sRPE), in elite male basketball training sessions. Thirteen professional basketball players participated in this study (age=25.7±3.3 years; body height=199.2±10.7 cm; body mass=96.6±9.4 kg). All players belonged to the same team, competing in two leagues, ACB and the Euroleague, in the 2016/2017 season. The variables assessed within the external motion analysis included: Player Load (PL), acceleration and deceleration (ACC/DEC), jumps (JUMP), and changes of direction (CoD). The internal demands were registered using the sRPE method. Pearson product-moment correlations were used to determine relationships between the variables. A significant correlation was observed between the external load variables and sRPE (range r=0.71–0.93). Additionally, the sRPE variable showed a high correlation with the total PL, ACC, DEC, and CoD. The contrary was observed with respect to the relationship between sRPE and JUMP variables: the correlation was higher for the high band and lower for the total number of jumps. With respect to the external load variables, a stronger correlation was found between PL and the total number of ACC, DEC and COD than the same variables within the high band. The only contrary finding was the correlation between PL and JUMP variables, which showed a stronger correlation for hJUMP. Tri-axial accelerometry technology and the sRPE method serve as valuable tools for monitoring the training load in basketball. Even though the two methods exhibit a strong correlation, some variation exists, likely due to frequent static movements (i.e., isometric muscle contractions) that accelerometers are not able to detect. Finally, it is suggested that both methods are to be used complementary, when possible, in order to design and control the training process as effectively as possible.
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Duignan, Ciara, Cailbhe Doherty, Brian Caulfield, and Catherine Blake. "Single-Item Self-Report Measures of Team-Sport Athlete Wellbeing and Their Relationship With Training Load: A Systematic Review." Journal of Athletic Training 55, no. 9 (September 1, 2020): 944–53. http://dx.doi.org/10.4085/1062-6050-0528.19.
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Background Single-item athlete self-report measures consist of a single question to assess a dimension of wellbeing. These methods are recommended and frequently used for athlete monitoring, yet their uniformity has not been well assessed, and we have a limited understanding of their relationship with measures of training load. Objective To investigate the applications and designs of single-item self-report measures used in monitoring team-sport athletes and present the relationship between these measures and measures of training load. Data Sources PubMed, Scopus, and SPORTDiscus were searched between inception and March 2019. Study Selection Articles were included if they concerned adult athletes from field- or court-sport domains, if athlete well-being was measured using a single-item self-report, and if the relationship with a measure of modifiable training load was investigated over at least 7 days. Data Extraction Data related to participant characteristics, self-report measures, training load measures, and statistical analysis and outcomes were extracted by 2 authors (C.D. and C.D.). Data Synthesis A total of 21 studies were included in the analysis. A narrative synthesis was conducted. The measures used most frequently were muscle soreness, fatigue, sleep quality, stress, and mood. All measures presented various relationships with metrics of training load from no association to a very large association, and the associations were predominantly trivial to moderate in the studies with the largest numbers of observations. Relationships were largely negative associations. Conclusions The implications of this review should be considered by users in the application and clinical utility of single-item self-report measures in athlete monitoring. Great emphasis has been placed on examining the relationship between subjective and objective measures of training load. Although the relationship is still unclear, such an association may not be expected or useful. Researchers should consider the measurement properties of single-item self-report measures and seek to establish their relationship with clinically meaningful outcomes. As such, further study is required to inform practitioners on the appropriate objective application of data from single-item self-report measures.
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Fisher, Kevin M., Lindsay Fuller, and Judy P. Chandler. "A Review of the Relationship between Heart Rate Monitoring, Training Load, and Injury in Field-Based Team Sport Athletes." International Journal of Sport, Exercise and Health Research 6, no. 1 (June 25, 2022): 43–54. http://dx.doi.org/10.31254/sportmed.6108.
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Outdoor, field-based team sports have been a staple of American and international cultures throughout recorded history and are currently played by millions of athletes around the globe. In modern competition, it is critical for athletes and support staff such as coaches, strength and conditioning specialists, and medical personnel to cooperate to optimize competitive readiness and performance. Important variables that can enhance or reduce physiological adaptations related to these areas include the relationship between the prescribed training workload and potential injuries. Therefore, it is important to understand and modify these aspects to fit the unique needs of individual athletes and specific teams. Recent advancements in technology now allow aspects of performance to be monitored in real time via methods that are reliable, cost effective, and noninvasive. The purpose of this literature review is to summarize and elucidate the available information on the potential relationship between heart rate monitoring and training load and how it may be used to prevent, predict, or detect an injury among athletes who participate in field-based sports. Overall, results indicate that while such technology has been used to describe and prescribe training workload, little research has been done to monitor the relationship between these variables and proclivity for or recovery from injury. Future longitudinal studies that encapsulate and address the highly dynamic nature and relationship of these variables are needed to better understand how they interact. Such an understanding may allow personnel such as coaches and staff to better support athletes on and off the field.
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Vanrenterghem, Jos, Niels Jensby Nedergaard, Mark A. Robinson, and Barry Drust. "Training Load Monitoring in Team Sports: A Novel Framework Separating Physiological and Biomechanical Load-Adaptation Pathways." Sports Medicine 47, no. 11 (March 10, 2017): 2135–42. http://dx.doi.org/10.1007/s40279-017-0714-2.
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Heishman, Aaron, Keldon Peak, Ryan Miller, Brady Brown, Bryce Daub, Eduardo Freitas, and Michael Bemben. "Associations Between Two Athlete Monitoring Systems Used to Quantify External Training Loads in Basketball Players." Sports 8, no. 3 (March 11, 2020): 33. http://dx.doi.org/10.3390/sports8030033.
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Monitoring external training load (eTL) has become popular for team sport for managing fatigue, optimizing performance, and guiding return-to-play protocols. During indoor sports, eTL can be measured via inertial measurement units (IMU) or indoor positioning systems (IPS). Though each device provides unique information, the relationships between devices has not been examined. Therefore, the purpose of this study was to assess the association of eTL between an IMU and IPS used to monitor eTL in team sport. Retrospective analyses were performed on 13 elite male National Collegiate Athletic Association (NCAA) Division I basketball players (age: 20.2 ± 1.2 years, height: 201.1 ± 7.6 cm, mass: 96.8 ± 8.8 kg) from three practices during the off-season training phase. A one-way analysis of variance was used to test differences in eTL across practices. Pearson’s correlation examined the association between the Distance traveled during practice captured by IPS compared to PlayerLoad (PL), PlayerLoad per Minute (PL/Min), 2-Dimensional PlayerLoad (PL2D), 1-Dimensional PlayerLoad Forward (PL1D-FWD), Side (PL1D-SIDE), and Up (PL1D-UP) captured from the IMU. Regression analyses were performed to predict PL from Distance traveled. The eTL characteristics during Practice 1: PL = 420.4 ± 102.9, PL/min = 5.8 ± 1.4, Distance = 1645.9 ± 377.0 m; Practice 2: PL = 472.8 ± 109.5, PL/min = 5.1 ± 1.2, Distance = 1940.0 ± 436.3 m; Practice 3: PL = 295.1 ± 57.8, PL/min = 5.3 ± 1.0, Distance = 1198.2 ± 219.2 m. Significant (p ≤ 0.05) differences were observed in PL, PL2D, PL1D-FWD, PL1D-SIDE, PL1D-UP, and Distance across practices. Significant correlations (p ≤ 0.001) existed between Distance and PL parameters (Practice 1: r = 0.799–0.891; Practice 2: r = 0.819–0.972; and Practice 3: 0.761–0.891). Predictive models using Distance traveled accounted for 73.5–89.7% of the variance in PL. Significant relationships and predictive capacities exists between systems. Nonetheless, each system also appears to capture unique information that may still be useful to performance practitioners regarding the understanding of eTL.
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Bartlett, Jonathan D., Fergus O’Connor, Nathan Pitchford, Lorena Torres-Ronda, and Samuel J. Robertson. "Relationships Between Internal and External Training Load in Team-Sport Athletes: Evidence for an Individualized Approach." International Journal of Sports Physiology and Performance 12, no. 2 (February 2017): 230–34. http://dx.doi.org/10.1123/ijspp.2015-0791.
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Purpose:The aim of this study was to quantify and predict relationships between rating of perceived exertion (RPE) and GPS training-load (TL) variables in professional Australian football (AF) players using group and individualized modeling approaches.Methods:TL data (GPS and RPE) for 41 professional AF players were obtained over a period of 27 wk. A total of 2711 training observations were analyzed with a total of 66 ± 13 sessions/player (range 39–89). Separate generalized estimating equations (GEEs) and artificial-neural-network analyses (ANNs) were conducted to determine the ability to predict RPE from TL variables (ie, session distance, high-speed running [HSR], HSR %, m/min) on a group and individual basis.Results:Prediction error for the individualized ANN (root-mean-square error [RMSE] 1.24 ± 0.41) was lower than the group ANN (RMSE 1.42 ± 0.44), individualized GEE (RMSE 1.58 ± 0.41), and group GEE (RMSE 1.85 ± 0.49). Both the GEE and ANN models determined session distance as the most important predictor of RPE. Furthermore, importance plots generated from the ANN revealed session distance as most predictive of RPE in 36 of the 41 players, whereas HSR was predictive of RPE in just 3 players and m/min was predictive of RPE in just 2 players.Conclusions:This study demonstrates that machine learning approaches may outperform more traditional methodologies with respect to predicting athlete responses to TL. These approaches enable further individualization of load monitoring, leading to more accurate training prescription and evaluation.
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He, Guojian, Guanghui Liu, and Jinliang Zhao. "PHYSIOLOGICAL MONITORING OF INTENSITY TRAINING IN FEMALE WRESTLERS." Revista Brasileira de Medicina do Esporte 28, no. 6 (December 2022): 804–6. http://dx.doi.org/10.1590/1517-8692202228062022_0037.
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ABSTRACT Introduction Currently, female wrestling has become one of the potential advantages in the Olympic Games, which has also allowed the sport to receive more attention. Physiological monitoring in intense physical training in female wrestlers is still little explored despite its importance in training conduction. Objective Explore special intensity physical training effects on female wrestlers through physiological monitoring. Methods Literature search, expert interview, and an experimental method conducted a situation analysis on 2-month training for 8 female wrestling team athletes, specific contents also included: analysis of female wrestlers’ body composition, changes in serum testosterone levels, and variations in cortisol levels. Results During the two-month training period, the various athletes’ physiological indicators underwent noticeable changes, remaining at the top of the normal range. Most of the athletes could adapt to the training load and intensity in this phase. Serum testosterone, cortisol, and hemoglobin levels in early athletes increased significantly. However, as training progresses, all indicators decrease, showing that the adaptability of the athlete’s body is consolidated. The hemoglobin content increased in most of the athletes, showing that the athlete’s own intensity of physical training was high. Conclusion The above physiological indicators can reflect the physical function of the athletes, providing a theoretical basis for coaches to develop evidence-based training plans. Evidence Level II; Therapeutic Studies - Investigating the result.
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Starling, Lindsay T., and Michael I. Lambert. "Monitoring Rugby Players for Fitness and Fatigue: What Do Coaches Want?" International Journal of Sports Physiology and Performance 13, no. 6 (July 1, 2018): 777–82. http://dx.doi.org/10.1123/ijspp.2017-0416.
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Purpose: The advantages of monitoring players in a team are well documented. However, barriers associated with lack of resources and time prevent teams from implementing systematic monitoring programs. This study aimed to identify (1) the methods rugby teams use to monitor the training load and associated response to the training load and (2) prerequisites of a monitoring protocol that are scientifically suitable and practically applicable for monitoring fitness and fatigue of rugby players. Methods: Coaches and support staff working with varying levels of rugby union were invited to complete an online questionnaire. Results: Of the 55 respondents, 96% indicated that although they regarded monitoring the training load and training-load response as important, there is no monitoring protocol that is cost-effective, time efficient, and nonaversive to the players. Respondents measured several variables when monitoring and incorporated more subjective than objective measures. Respondents (41%) indicated that they would like a protocol that is time efficient (5–10 min) and provides immediate feedback on players who identify as fatigued (50%). For coaches to have confidence in the information provided by the protocol, it needs to meet basic clinimetric principles of reliability and validity. The technical and biological error in the measurement needs to be known so that meaningful changes in fatigue and fitness can be distinguished from natural variations in the measurements. Conclusions: Prerequisites of an ideal monitoring protocol for rugby players were identified. It follows that a monitoring protocol that fulfills these prerequisites should satisfy both scientific principles and the coach’s demands.
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E., Wenjie, and Qiufen Yu. "Effect of Rehabilitation Physical Training on Basketball Injury under Ultrasound Examination." Scanning 2022 (August 8, 2022): 1–8. http://dx.doi.org/10.1155/2022/2554581.
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In order to solve the problem of observing the effect of rehabilitation physical training on basketball player injury, a kind of observation study on the effect of rehabilitation physical training on basketball player injury based on memory ultrasound examination was proposed. This study makes a comprehensive analysis of physical fitness training factors such as physical fitness test plan, training arrangement, training method, training monitoring, and effect evaluation. Through the experiment, it is found that there are still gaps in physical training, diagnostic standards, training plans and requirements, load monitoring, standardization of operation, nutrition, and recovery in the training organization. There are only 23.81% of full-time physical coaches and 25.40% of professional team doctors at all levels of sports teams. There were only 23.81% of full-time physical fitness coaches and 25.40% of professional team doctors in all levels of sports teams. Basketball players in the basketball injury survey had 67 sports injuries throughout the year, with a rate of 3.35 injuries per person and 2.48 injuries per 1000 hours. The location of chronic injuries is usually the lower back, knee joint, and ankle. The main injuries are due to the physical component, with injuries occurring most frequently throughout the training season in July, August, and September. Experiments show that good and professional physical training can reduce the risk of injury to a greater extent than strengthening the specific skills of athletes.
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Balsalobre-Fernández, Carlos, and Lorena Torres-Ronda. "The Implementation of Velocity-Based Training Paradigm for Team Sports: Framework, Technologies, Practical Recommendations and Challenges." Sports 9, no. 4 (March 30, 2021): 47. http://dx.doi.org/10.3390/sports9040047.
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While velocity-based training is currently a very popular paradigm to designing and monitoring resistance training programs, its implementation remains a challenge in team sports, where there are still some confusion and misinterpretations of its applications. In addition, in contexts with large squads, it is paramount to understand how to best use movement velocity in different exercises in a useful and time-efficient way. This manuscript aims to provide clarifications on the velocity-based training paradigm, movement velocity tracking technologies, assessment procedures and practical recommendations for its application during resistance training sessions, with the purpose of increasing performance, managing fatigue and preventing injuries. Guidelines to combine velocity metrics with subjective scales to prescribe training loads are presented, as well as methods to estimate 1-Repetition Maximum (1RM) on a daily basis using individual load–velocity profiles. Additionally, monitoring strategies to detect and evaluate changes in performance over time are discussed. Finally, limitations regarding the use of velocity of execution tracking devices and metrics such as “muscle power” are commented upon.
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McBurnie, Alistair J., Damian J. Harper, Paul A. Jones, and Thomas Dos’Santos. "Deceleration Training in Team Sports: Another Potential ‘Vaccine’ for Sports-Related Injury?" Sports Medicine 52, no. 1 (October 29, 2021): 1–12. http://dx.doi.org/10.1007/s40279-021-01583-x.
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AbstractHigh-intensity horizontal decelerations occur frequently in team sports and are typically performed to facilitate a reduction in momentum preceding a change of direction manoeuvre or following a sprinting action. The mechanical underpinnings of horizontal deceleration are unique compared to other high-intensity locomotive patterns (e.g., acceleration, maximal sprinting speed), and are characterised by a ground reaction force profile of high impact peaks and loading rates. The high mechanical loading conditions observed when performing rapid horizontal decelerations can lead to tissue damage and neuromuscular fatigue, which may diminish co-ordinative proficiency and an individual’s ability to skilfully dissipate braking loads. Furthermore, repetitive long-term deceleration loading cycles if not managed appropriately may propagate damage accumulation and offer an explanation for chronic aetiological consequences of the ‘mechanical fatigue failure’ phenomenon. Training strategies should look to enhance an athlete’s ability to skilfully dissipate braking loads, develop mechanically robust musculoskeletal structures, and ensure frequent high-intensity horizontal deceleration exposure in order to accustom individuals to the potentially damaging effects of intense decelerations that athletes will frequently perform in competition. Given the apparent importance of horizontal decelerations, in this Current Opinion article we provide considerations for sport science and medicine practitioners around the assessment, training and monitoring of horizontal deceleration. We feel these considerations could lead to new developments in injury-mitigation and physical development strategies in team sports.
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King, Marguerite Helen, Nathalia Costa, Amy Lewis, Kate Watson, and Bill Vicenzino. "Throwing in the deep end: athletes, coaches and support staff experiences, perceptions and beliefs of upper limb injuries and training load in elite women’s water polo." BMJ Open Sport & Exercise Medicine 8, no. 1 (March 2022): e001214. http://dx.doi.org/10.1136/bmjsem-2021-001214.
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To understand elite athlete, coach and support staff experiences, perceptions and beliefs in women’s water polo with managing upper limb injuries and monitoring training loads. Inductive qualitative design. Twenty athletes, coaches and support staff were purposively recruited and participated in semistructured interviews. Participants either had experienced an upper limb injury or had experience managing athletes with upper limb injuries. Interviews were conducted in-person or virtually, audio-recorded, deidentified, transcribed verbatim and cleaned to ensure accuracy. Data were thematically analysed. Analysis identified five cohesive themes: (1) upper limb injury management is adequate—but prevention, communication and knowledge need improving, (2) current training load monitoring generates uncertainty and lack of consistency of processes—due to reliance on internal, and lack of external load monitoring, (3) optimal training load monitoring requires objective measurement of training load—that accurately measures the external load of athletes’ upper limbs, (4) athlete-centred philosophy matters—including athlete-centred care to facilitate individually tailored rehabilitation programmes and their inclusion in management decisions, (5) mental, social and emotional aspects of upper limb injury management matter—acknowledging feelings of loss of team inclusion, fear of missing out and frustration felt by athletes as well as the emotional labour felt by coaches when supporting athletes with an upper limb injury. Upper limb injury management and training load monitoring are evolving areas where objective measurement of training load may assist in increasing consistency of communication, collaboration and coordination between all stakeholders, and to address uncertainty. Stakeholders placed value in intangible qualities such as trust and care in their relationships with other collaborators—facilitating athlete physical, mental and emotional recovery following upper limb injuries.
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Teixeira, José E., Pedro Forte, Ricardo Ferraz, Miguel Leal, Joana Ribeiro, António J. Silva, Tiago M. Barbosa, and António M. Monteiro. "Monitoring Accumulated Training and Match Load in Football: A Systematic Review." International Journal of Environmental Research and Public Health 18, no. 8 (April 8, 2021): 3906. http://dx.doi.org/10.3390/ijerph18083906.
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(1) Background: Training load monitoring has become a relevant research-practice gap to control training and match demands in team sports. However, there are no systematic reviews about accumulated training and match load in football. (2) Methods: Following the preferred reporting item for systematic reviews and meta-analyses (PRISMA), a systematic search of relevant English-language articles was performed from earliest record to March 2020. The search included descriptors relevant to football, training load, and periodization. (3) Results: The literature search returned 7972 articles (WoS = 1204; Pub-Med = 869, SCOPUS = 5083, and SportDiscus = 816). After screening, 36 full-text articles met the inclusion criteria and were reviewed. Eleven of the included articles analyzed weekly training load distribution; fourteen, the weekly training load and match load distribution; and eleven were about internal and external load relationships during training. The reviewed articles were based on short-telemetry systems (n = 12), global positioning tracking systems (n = 25), local position measurement systems (n = 3), and multiple-camera systems (n = 3). External load measures were quantified with distance and covered distance in different speed zones (n = 27), acceleration and deceleration (n = 13) thresholds, accelerometer metrics (n = 11), metabolic power output (n = 4), and ratios/scores (n = 6). Additionally, the internal load measures were reported with perceived exertion (n = 16); heart-rate-based measures were reported in twelve studies (n = 12). (4) Conclusions: The weekly microcycle presented a high loading variation and a limited variation across a competitive season. The magnitude of loading variation seems to be influenced by the type of week, player’s starting status, playing positions, age group, training mode and contextual variables. The literature has focused mainly on professional men; future research should be on the youth and female accumulated training/match load monitoring.
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Hou, Lin. "TRAINING INTENSITY ADJUSTMENT BY CARDIAC MONITORING IN YOUNG ATHLETES." Revista Brasileira de Medicina do Esporte 28, no. 6 (December 2022): 840–42. http://dx.doi.org/10.1590/1517-8692202228062022_0044.
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ABSTRACT Introduction Cardiac monitoring can provide critical information for basketball training among young athletes. Using the data collected, adjustments on exercise load increase, workouts intervals, and the recovery time for each athlete can be made. It is believed that these indexes will provide fine-tuning in quantity and quality training. Objective Explore cardiac monitoring in the sports training center of young basketball players. Methods Two male basketball players were selected, using the Polar® brand heart rate monitoring team management system, to monitor the change in heart rate between positions and in different training periods. Results The measured maximum heart rate is between 181 and 192 BPM. During training, the average heart rate of the team was 146 BPM, the intermittent heart rate was between 99 and 121 BPM, the average difference in players’ heart rate recovery was 74 times. Conclusion This study proves that heart rate can be an effective monitoring indicator. The monitoring index can contribute profoundly to training among young basketball athletes, allowing coaches the adjustment of intensity and type of training with a practical evaluation method. Evidence Level II; Therapeutic Studies - Investigating the result.
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Malone, James J., Arne Jaspers, Werner Helsen, Brenda Merks, Wouter G. P. Frencken, and Michel S. Brink. "Seasonal Training Load and Wellness Monitoring in a Professional Soccer Goalkeeper." International Journal of Sports Physiology and Performance 13, no. 5 (May 1, 2018): 672–75. http://dx.doi.org/10.1123/ijspp.2017-0472.
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The purpose of this investigation was to (1) quantify the training load practices of a professional soccer goalkeeper and (2) investigate the relationship between the training load observed and the subsequent self-reported wellness response. One male goalkeeper playing for a team in the top league of the Netherlands participated in this case study. Training load data were collected across a full season using a global positioning system device and session-RPE (rating of perceived exertion). Data were assessed in relation to the number of days to a match (MD− and MD+). In addition, self-reported wellness response was assessed using a questionnaire. Duration, total distance, average speed, PlayerLoad™, and load (derived from session-RPE) were highest on MD. The lowest values for duration, total distance, and PlayerLoad™ were observed on MD−1 and MD+1. Total wellness scores were highest on MD and MD−3 and were lowest on MD+1 and MD−4. Small to moderate correlations between training load measures (duration, total distance covered, high deceleration efforts, and load) and the self-reported wellness response scores were found. This exploratory case study provides novel data about the physical load undertaken by a goalkeeper during 1 competitive season. The data suggest that there are small to moderate relationships between training load indicators and self-reported wellness response. This weak relation indicates that the association is not meaningful. This may be due to the lack of position-specific training load parameters that practitioners can currently measure in the applied context.
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Morin, Stéphane, Saïd Ahmaïdi, and Pierre-Marie Leprêtre. "Relevance of Damped Harmonic Oscillation for Modeling the Training Effects on Daily Physical Performance Capacity in Team Sport." International Journal of Sports Physiology and Performance 11, no. 7 (October 2016): 965–72. http://dx.doi.org/10.1123/ijspp.2015-0203.
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Context:Positive and negative effects of training induce apparent oscillations of performance, suggesting that the delayed cumulative effects of training on daily performance capacity (DPC) are best fitted by sine waves damped over time.Purpose:To compare the criterion validity of the impulse-response (IR) model of Banister et al and the damped harmonic oscillation (DHO) model for quantifying the training load (TL)–DPC relationship.Methods:Six female professional volleyball players (20.8 ± 2.4 y) were monitored using the session rating of perceived exertion (sRPE) for 9 mo to quantify TL. Countermovement-jump (CMJ) and 4-step-approach-CMJ (4sCMJ) performances were recorded once a month. Parameters of models were determined by minimizing residual-sum squares between predicted and real performances with a nonlinear regression.Results:DPC was best fitted by the DHO model rather than the IR model (CMJ, R2 = .80 ±.08 and.69 ±.20, respectively; 4sCMJ, R2 = .86 ± .09 and .67 ± .29, respectively). The damping parameter θ and the period T were positively correlated with age (ρ = 0.81, P < .05, and ρ = 0.86, P < .02, respectively).Conclusions:The DHO model is a useful tool for modeling DPC as the sum of the delayed DPCs from the consecutive training and recovery days. DPC could be considered the expression of the individual process of accumulation and dissipation of fatigue induced by training. DHO-model parameters were correlated with age, which prompts one to postulate that expertise has a major influence on DPC. The DHO model will help coaches develop a greater understanding of training effects and make monitoring of the training process more effective.
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Buchheit, Martin, and Ben Michael Simpson. "Player-Tracking Technology: Half-Full or Half-Empty Glass?" International Journal of Sports Physiology and Performance 12, s2 (April 2017): S2–35—S2–41. http://dx.doi.org/10.1123/ijspp.2016-0499.
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With the ongoing development of microtechnology, player tracking has become one of the most important components of load monitoring in team sports. The 3 main objectives of player tracking are better understanding of practice (provide an objective, a posteriori evaluation of external load and locomotor demands of any given session or match), optimization of training-load patterns at the team level, and decision making on individual players’ training programs to improve performance and prevent injuries (eg, top-up training vs unloading sequences, return to play progression). This paper discusses the basics of a simple tracking approach and the need to integrate multiple systems. The limitations of some of the most used variables in the field (including metabolic-power measures) are debated, and innovative and potentially new powerful variables are presented. The foundations of a successful player-monitoring system are probably laid on the pitch first, in the way practitioners collect their own tracking data, given the limitations of each variable, and how they report and use all this information, rather than in the technology and the variables per se. Overall, the decision to use any tracking technology or new variable should always be considered with a cost/benefit approach (ie, cost, ease of use, portability, manpower/ability to affect the training program).
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Rossi, Alessio, Enrico Perri, Luca Pappalardo, Paolo Cintia, and F. Iaia. "Relationship between External and Internal Workloads in Elite Soccer Players: Comparison between Rate of Perceived Exertion and Training Load." Applied Sciences 9, no. 23 (November 28, 2019): 5174. http://dx.doi.org/10.3390/app9235174.
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The use of machine learning (ML) in soccer allows for the management of a large amount of data deriving from the monitoring of sessions and matches. Although the rate of perceived exertion (RPE), training load (S-RPE), and global position system (GPS) are standard methodologies used in team sports to assess the internal and external workload; how the external workload affects RPE and S-RPE remains still unclear. This study explores the relationship between both RPE and S-RPE and the training workload through ML. Data were recorded from 22 elite soccer players, in 160 training sessions and 35 matches during the 2015/2016 season, by using GPS tracking technology. A feature selection process was applied to understand which workload features influence RPE and S-RPE the most. Our results show that the training workloads performed in the previous week have a strong effect on perceived exertion and training load. On the other hand, the analysis of our predictions shows higher accuracy for medium RPE and S-RPE values compared with the extremes. These results provide further evidence of the usefulness of ML as a support to athletic trainers and coaches in understanding the relationship between training load and individual-response in team sports.
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Ibáñez, Sergio J., Emilio Pérez-Goye, Javier García-Rubio, and Javier Courel-Ibáñez. "Effects of task constraints on training workload in elite women’s soccer." International Journal of Sports Science & Coaching 15, no. 1 (November 27, 2019): 99–107. http://dx.doi.org/10.1177/1747954119891158.
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The purposes of this study were to identify which major constraints contribute to greater task workload and to determine distinctive training task profiles using an integrative approach during a regular season from a professional women’s soccer team. Twenty-seven elite soccer players from a team competing in the first Spanish women’s soccer league participated in this study. Data were obtained from 46 training sessions (112 training tasks) along five competitive months. Workload measures were collected using the SIATE integrative assessment tool and heart rate monitors during the team’s regular training routine. Results from cluster analysis effectively classified four types of training activities that caused a distinct physiological response from players. The most relevant constraints that increased the task workload were, in order of influence: interaction possibilities, opposition degree, simultaneous participation, game space, competitive workload and intensity. In turn, internal training load monitoring by heart rate seems to be worthless during technical-tactical soccer drills. These results provide coaches an easy, affordable and more informative tool to quantify the training workload. Whereas this information requires observational assessment tools to be obtained, these methods should be considered as a complement to wearables devices for training load control and monitoring in field sports.
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Palmer, Branson L., Grant E. van der Ploeg, Pitre C. Bourdon, Scott R. Butler, and Robert G. Crowther. "Evaluation of Athlete Monitoring Tools across 10 Weeks of Elite Youth Basketball Training: An Explorative Study." Sports 11, no. 2 (January 25, 2023): 26. http://dx.doi.org/10.3390/sports11020026.
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The growth of sport science technology is enabling more sporting teams to implement athlete monitoring practices related to performance testing and load monitoring. Despite the increased emphasis on youth athlete development, the lack of longitudinal athlete monitoring literature in youth athletes is concerning, especially for indoor sports such as basketball. The aim of this study was to evaluate the effectiveness of six different athlete monitoring methods over 10 weeks of youth basketball training. Fourteen state-level youth basketball players (5 males and 9 females; 15.1 ± 1.0 yrs) completed this study during their pre-competition phase prior to their national basketball tournament. Daily wellness and activity surveys were completed using the OwnUrGoal mobile application, along with heart rate (HR) and inertial measurement unit (IMU) recordings at each state training session, and weekly performance testing (3x countermovement jumps [CMJs], and 3x isometric mid-thigh pulls [IMTPs]). All of the athlete monitoring methods demonstrated the coaching staff’s training intent to maintain performance and avoid spikes in workload. Monitoring IMU data combined with PlayerLoad™ data analysis demonstrated more effectiveness for monitoring accumulated load (AL) compared to HR analysis. All six methods of athlete monitoring detected similar trends for all sessions despite small-trivial correlations between each method (Pearson’s correlation: −0.24 < r < 0.28). The use of subjective monitoring questionnaire applications, such as OwnUrGoal, is recommended for youth sporting clubs, given its practicability and low-cost. Regular athlete education from coaches and support staff regarding the use of these questionnaires is required to gain the best data.
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Rabelo, Felipe N., Bruno N. Pasquarelli, Bruno Gonçalves, Fernando Matzenbacher, Fábio A. D. Campos, Jaime Sampaio, and Fábio Y. Nakamura. "Monitoring the Intended and Perceived Training Load of a Professional Futsal Team Over 45 Weeks." Journal of Strength and Conditioning Research 30, no. 1 (January 2016): 134–40. http://dx.doi.org/10.1519/jsc.0000000000001090.
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Thornton, Heidi R., Jace A. Delaney, Grant M. Duthie, and Ben J. Dascombe. "Importance of Various Training-Load Measures in Injury Incidence of Professional Rugby League Athletes." International Journal of Sports Physiology and Performance 12, no. 6 (July 2017): 819–24. http://dx.doi.org/10.1123/ijspp.2016-0326.
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Purpose:To investigate the ability of various internal and external training-load (TL) monitoring measures to predict injury incidence among positional groups in professional rugby league athletes.Methods:TL and injury data were collected across 3 seasons (2013–2015) from 25 players competing in National Rugby League competition. Daily TL data were included in the analysis, including session rating of perceived exertion (sRPE-TL), total distance (TD), high-speed-running distance (>5 m/s), and high-metabolic-power distance (HPD; >20 W/kg). Rolling sums were calculated, nontraining days were removed, and athletes’ corresponding injury status was marked as “available” or “unavailable.” Linear (generalized estimating equations) and nonlinear (random forest; RF) statistical methods were adopted.Results:Injury risk factors varied according to positional group. For adjustables, the TL variables associated most highly with injury were 7-d TD and 7-d HPD, whereas for hit-up forwards they were sRPE-TL ratio and 14-d TD. For outside backs, 21- and 28-d sRPE-TL were identified, and for wide-running forwards, sRPE-TL ratio. The individual RF models showed that the importance of the TL variables in injury incidence varied between athletes.Conclusions:Differences in risk factors were recognized between positional groups and individual athletes, likely due to varied physiological capacities and physical demands. Furthermore, these results suggest that robust machine-learning techniques can appropriately monitor injury risk in professional team-sport athletes.
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Horta, Thiago Andrade Goulart, Pedro Henrique Prazeres de Lima, Guilherme Garcia Matta, Jefferson Verbena de Freitas, Bernardo Miloski Dias, Jeferson Macedo Vianna, Heglison Custodio Toledo, Renato Miranda, Thiago Ferreira Timoteo, and Maurício Gattás Bara Filho. "TRAINING LOAD IMPACT ON RECOVERY STATUS IN PROFESSIONAL VOLLEYBALL ATHLETES." Revista Brasileira de Medicina do Esporte 26, no. 2 (April 2020): 158–61. http://dx.doi.org/10.1590/1517-869220202602209364.
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ABSTRACT Introduction: The success of training depends on the balance between training load magnitude and recovery. Objective: Verify the effect of training load distribution on recovery status, vigor and fatigue in volleyball players during a season. Methods: Nine male athletes from a professional volleyball team participated in the study. During 19 weeks of the season, quantification of the training load was performed through the session rating of perceived exertion (RPE) method, evaluation of the athletes' recovery status through the Total Quality Recovery (TQR) scale, and evaluation of the profile of mood state through the POMS questionnaire, with research focus for the subscales vigor and fatigue. Results: The average total weekly training load (TWTL) was 3206 ± 685.5 A. Us and the average recovery of the whole season was 15.3 ± 0.57. The mean values of fatigue and vigor were 11 ± 3.05 and 19.4 ± 2.84, respectively. Significant differences were found for the variables RPE, fatigue and Energy Index (Vigor - Fatigue) in the three different periods of the season (Preparatory Period, Competitive Period I and Competitive Period II). Conclusion: It was concluded that the training load and recovery monitoring methods used throughout the season were effective in controlling the variables, with a positive impact of training loads verified on the recovery values presented by the athletes. Level of Evidence III; Diagnostic study.
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Li, Deqi. "Design of Table Tennis Training Competition Knowledge Interaction Platform Integrating Improved Swarm Intelligence Algorithm." Computational Intelligence and Neuroscience 2022 (August 1, 2022): 1–13. http://dx.doi.org/10.1155/2022/2594430.
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Table tennis is China ’s national game and the proudest sport in China’s sports field. During the research and technology service work of the Chinese table tennis team for many years, it has accumulated a large amount of valuable data on the analysis of skills and tactics of training and matches, match video, training monitoring, and so on. This paper discusses the relevant theory of swarm intelligence algorithm processing big data on the table tennis training competition knowledge interaction platform system, as well as the technical support of Nginx and Tomcat, and determines the technical basis of the table tennis training competition knowledge interaction platform. Through the establishment of the firefly algorithm model, the resource search ability is enhanced, and the traditional firefly algorithm is improved. From the results of the system performance test, it can be found that the improved swarm intelligence algorithm adopted in this paper improves the global convergence, and the load balancing degree gradually decreases with the increase of time. The improved firefly algorithm shows good performance when the bandwidth is low, and the resource occupancy rate is greatly reduced. When the bandwidth is 20, it is reduced by 12.55%. It solves the shortcomings of long time and low success rate, so as to verify the convenience of the system operation and the power of functions and make the platform more intelligent and efficient.
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Blázquez López, José Antonio, Salvador García Martínez, Alberto Ferriz Valero, and Javier Olaya Cuartero. "Cuantificación de la carga de entrenamiento y competición: análisis comparativo por posiciones en un equipo de la Liga Española de Baloncesto Oro (Quantification of training and competition load: comparative analysis by position in a Spanish Golden Baske." Retos 42 (June 14, 2021): 882–90. http://dx.doi.org/10.47197/retos.v42i0.87268.
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El objetivo principal de este trabajo es cuantificar y analizar la carga de entrenamiento y competición de los jugadores de un equipo profesional de baloncesto de la categoría LEB Oro. Durante el estudio se han llevado a cabo procesos de análisis de carga objetiva y subjetiva mediante cuestionarios diarios de escalas de esfuerzo percibido (RPE) y control de minutos totales de entrenamiento y competición, obteniendo variables de carga media, semanal y total, índices de monotonía y fatiga y ratio de carga aguda-crónica. Se cuantificó la carga de entrenamiento y competición de 10 jugadores de un mismo equipo profesional (edad = 27.2 ± 5.3 años; altura = 196.4 ± 8.7 cm; peso = 91.1 ± 12.3 kg) diferenciando entre bases, exteriores (escoltas y aleros) e interiores (ala-pívots y pívots) durante 21 semanas de entrenamiento. Los resultados principales del presente estudio mostraron mayor percepción de la carga para la posición de los bases en comparación con los interiores y exteriores. La mayoría de los jugadores de la plantilla se mantuvieron durante toda la primera vuelta en un estado de forma óptimo o sweet point, lo que supone una disminución del estado de fatiga y riesgo de lesión, debido a este seguimiento y control de la carga. Este estudio servirá a entrenadores y preparadores físicos a la hora de elegir diferentes herramientas para realizar una correcta cuantificación e interpretación de la carga de entrenamiento en un deporte de equipo como el baloncesto.
Abstract. The main purpose of this study was to quantify and analyze the training and competition load of the players of a professional basketball team in “LEB Oro” category. During the study, objective and subjective load analysis processes have been carried out through daily Rating of Perceived Exertion (RPE) questionnaires and control of total training and competition minutes, getting variables of average, weekly and total load, training monotony and training fatigue indexes and acute: chronic workload ratio. The training and competition load of 10 players from the same professional team (age = 27.2 ± 5.3 years; height = 196.4 ± 8.7 cm; weight = 91.1 ± 12.3 kg) was quantified by differentiating point guards, perimeter players (shooting guards and forwards) and inside players (center and power forward) during 21 weeks of training. The main results of the present study showed a greater perception of the load for the position of the point guards in comparison with the inside players and perimeter players. Most of the players in the squad were kept in an optimal or sweet point state throughout the first part of the season, which means a decrease in the fatigue and risk of injury due to this monitoring and control of the load. This study will be useful for coaches and physical trainers when choosing different tools to carry out a correct quantification and interpretation of the training load in a team sport such as basketball.
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Qin, Panlong, and Wei Feng. "Design of the Exercise Load Data Monitoring System for Exercise Training Based on the Neural Network." Journal of Healthcare Engineering 2021 (September 24, 2021): 1–6. http://dx.doi.org/10.1155/2021/7340140.
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In order to monitor the sports load data of athletes in sports training, this paper studies the methods and systems of sports load monitoring and fatigue warning based on neural network technology. In this paper, the neural network parallel optimization algorithm based on big data is used to accurately estimate the motion load and intensity according to the determined motion mode and acceleration data, so as to realize the real-time monitoring of the exercise training. The results show that the value of η is usually small to ensure that the weight correction can truly follow the direction of the gradient descent. In this paper, 176 samples were extracted from the monitoring data collected by the “National Tennis Team Information Platform,” 160 of which were selected as training samples and the other 16 as test samples. Ant colony size M = 20. The minimum value Wmin of the weight interval is −2, and the maximum value Wmax is 2. The maximum number of iterations is set to 200. σ = 1; that is, only one optimal solution is retained. The domain is divided into 60 parts evenly; that is, r = 60. Generally, η can be taken as any number [28] between [10-3, 10], but the value is usually small to ensure that the weight correction can truly follow the direction of the gradient descent. In this paper, the value is 0.003. In the early warning stage of exercise fatigue, reasonable measurement units of exercise fatigue time were divided according to the characteristics of different exercise items. It is proved that the Bayesian classification algorithm can effectively avoid the sports injury caused by overtraining by warning the fatigue and preventing the sports injury caused by overtraining.
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Weiss, Kaitlyn J., Sian V. Allen, Mike R. McGuigan, and Chris S. Whatman. "The Relationship Between Training Load and Injury in Men’s Professional Basketball." International Journal of Sports Physiology and Performance 12, no. 9 (October 2017): 1238–42. http://dx.doi.org/10.1123/ijspp.2016-0726.
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Purpose:To establish the relationship between the acute:chronic workload ratio and lower-extremity overuse injuries in professional basketball players over the course of a competitive season. Methods:The acute:chronic workload ratio was determined by calculating the sum of the current week’s session rating of perceived exertion of training load (acute load) and dividing it by the average weekly training load over the previous 4 wk (chronic load). All injuries were recorded weekly using a self-report injury questionnaire (Oslo Sports Trauma Research Center Injury Questionnaire20). Workload ratios were modeled against injury data using a logistic-regression model with unique intercepts for each player. Results:Substantially fewer team members were injured after workload ratios of 1 to 1.49 (36%) than with very low (≤0.5; 54%), low (0.5–0.99; 51%), or high (≥1.5; 59%) workload ratios. The regression model provided unique workload–injury trends for each player, but all mean differences in likelihood of being injured between workload ratios were unclear. Conclusions:Maintaining workload ratios of 1 to 1.5 may be optimal for athlete preparation in professional basketball. An individualized approach to modeling and monitoring the training load–injury relationship, along with a symptom-based injury-surveillance method, should help coaches and performance staff with individualized training-load planning and prescription and with developing athlete-specific recovery and rehabilitation strategies.
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Koryahin, Viktor. "Assessment of Training Loads of Highly Qualified Basketball Players." Physical Education Theory and Methodology 22, no. 3s (November 30, 2022): S137—S141. http://dx.doi.org/10.17309/tmfv.2022.3s.19.
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The purpose of the study is: 1) development and unification of a system of training loads monitoring by the nature of the physiological impact on the basketball players’ body; 2) study of the strategy of preparing a highly qualified basketball team for important international competitions, namely: to find out the nature of the distribution of means of different physiological, as well as technical-tactical and game orientation at different stages of preparation; 3) test basketball players before and after training.
Materials and methods. A team of highly qualified basketball players (masters of sports and masters of sports of international class) in the number of 15 people participated in the research. The assessment of physical load by the nature of the physiological impact on the body of basketball players during 18 microcycles using 4 – 1 system, that is, 4 working days and 1 day off, was carried out. Athletes were tested before and after training.
Results. The dynamics of the means of training by the nature of the physiological impact on the athletes’ body have been established. The nature of the distribution of means at different stages of preparation has been established. The test results before and after training are shown.
Conclusions. The research results showed that a certain accounting system based on assessments of the nature of the tasks to be solved and the degree of compliance with the specifics of their game activities has developed in basketball. At the same time, research have indicated the need for accounting and analyzing of the training loads by the nature of physiological impact on the body of athletes.
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Fuchs, Patrick, Live S. Luteberget, Philip X. Fuchs, and Herbert Wagner. "Comparative Analysis of the Indirect Calorimetry and the Metabolic Power Method to Calculate Energy Expenditure in Team Handball." Applied Sciences 12, no. 1 (December 24, 2021): 163. http://dx.doi.org/10.3390/app12010163.
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Monitoring physical activity, e.g., training load and energy expenditure (EE), is important to optimize the training process in various sports. Especially in team handball, where there is little information about EE in training and competition. The objective of the study was to compare EE in team handball derived from a respiratory gas exchange analysis (spiroergometry) and a local position measurement (LPM) system. Eleven participants completed a validated, team handball game-based performance test and wore a portable spiroergometry system (K5 Cosmed) and an LPM transponder (Catapult ClearSky T6). EE was determined via indirect calorimetry for spiroergometry data and via the metabolic power model for EE for LPM data. EE estimated via the metabolic power model was −66 to −63 ± 12% lower than via indirect calorimetry (p < 0.001, pη2 = 0.97). No correlation was found for the overall test (r = 0.32, p = 0.34), nor for every single heat (r ≤ 0.44, 0.18 ≤ p ≤ 0.99). Therefore, regression analyses predicting spiroergometry data based on LPM data were not feasible. In line with previous studies, the metabolic power model for EE in team handball (including short-distance movements, great accelerations, and non-locomotive actions) is not suitable.
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Leppänen, Mari, Kati Pasanen, Pekka Kannus, Tommi Vasankari, Urho Kujala, Ari Heinonen, and Jari Parkkari. "Epidemiology of Overuse Injuries in Youth Team Sports: A 3-year Prospective Study." International Journal of Sports Medicine 38, no. 11 (September 11, 2017): 847–56. http://dx.doi.org/10.1055/s-0043-114864.
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AbstractProspective studies on overuse injuries and their impact on athletic training among youth team sports are scarce. The purpose of this study was to investigate the incidence, severity and player related risk factors of overuse injuries among young (12–20 years) basketball and floorball players. A total of 387 players participated in a 3-year prospective study. Each player completed a baseline questionnaire regarding their background information. Overuse injuries that prevented players to fully or partly participate in their regular training were collected. In all, 204 overuse injuries were registered (injury incidence 1.51 injuries/1 000 h of exposure; 95% CI 1.35–1.78). Most of the injuries involved the knee (35%) and lower back (21%), and were classified as severe (44%). Injury incidence was 1.51 (95% CI 1.2–1.82) and 1.61 (95% CI 1.32–1.91) in basketball and floorball, respectively. Incidence was significantly higher among female compared with male players (incidence rate ratio 1.58; 95% CI 1.20–2.09). Previous injury and playing at adult level were the strongest factors associated with occurrence of an overuse injury. In conclusion, overuse injuries of the knee and low back are relatively common in youth basketball and floorball. Effective prevention strategies as well as training load monitoring is needed in youth team sports.
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Petrov, Roman Evgenyevich. "Sustainable Sport: Cardio-Differentiated Planning of Fitness Programs for High School Boys Engaged in Speed Skiing." Sustainability 11, no. 21 (November 1, 2019): 6077. http://dx.doi.org/10.3390/su11216077.
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In speed skiing, an athlete’s functional readiness is tested by means of a bicycle ergometer (EGM). The purpose of this research is to make various mesocycle plans for high school boys, engaged in speed skiing, with due account for their cardio-functional indicators obtained by means of the EGM. The study was attended by the 16–17 years old, first-category and sub-master racing skiers, included in the junior regional teams of the Russian Federation (Republic of Tatarstan and Udmurtia). The total number of subjects included eight men. In training young racing skiers, a differentiated approach combined with leg muscle testing will allow an improvement in sports results more effectively at different stages, as well as monitoring the young athlete’s response to the cardiovascular load. Low cardiac capacity indices have a negative impact on the racing skier’s performance. EGM testing allows determining the maximum cardiac capacity by measuring the amount of oxygen delivered to the working muscles at the HR of 190 beats per minute. Therefore, case-specific aerobic load was planned for each mesocycle according to these data. Based on the cardiac capacity growth, such means of physical training as interval, high-speed, and tempo training were planned.
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Choice, Erin, James Tufano, Kristen Jagger, Kayla Hooker, and Kristen C. Cochrane-Snyman. "Differences across Playing Levels for Match-Play Physical Demands in Women’s Professional and Collegiate Soccer: A Narrative Review." Sports 10, no. 10 (September 22, 2022): 141. http://dx.doi.org/10.3390/sports10100141.
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Advancements in sport technology have made quantifying match-play external load (e.g., total distance, sprint distance, number of sprints) a popular option for athletics personnel. These variables of volume and intensity are useful for both objectively monitoring training in field-based sports and for designing training programs. As physical abilities differ across playing levels, match-play demands likely also differ. This narrative review compiles and compares the match-play external load data for women’s soccer at the professional and collegiate levels. Databases were searched through July 2022, yielding 13 primary articles that assessed the match-play demands of women’s soccer (3 professional, 8 Division I, 1 Division II, and 1 Division III). The results indicate that the average total distance covered were similar between the professional, Division I and Division III levels, but the variability was greater among Division III compared to professional and Division I players. Data for Division II are scarce, but the total distance covered appears to be less than for professional, Division I and Division III. There was also large variability for sprint distance and number of sprints across data at all playing levels. Considering the lack of studies of Division II and Division III players, more research is necessary to determine how playing level may affect external load profiles, as isolated studies likely only reflect data from isolated teams.
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Conte, Daniele, Nicholas Kolb, Aaron T. Scanlan, and Fabrizio Santolamazza. "Monitoring Training Load and Well-Being During the In-Season Phase in National Collegiate Athletic Association Division I Men’s Basketball." International Journal of Sports Physiology and Performance 13, no. 8 (September 1, 2018): 1067–74. http://dx.doi.org/10.1123/ijspp.2017-0689.
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Purpose: To characterize the weekly training load (TL) and well-being of college basketball players during the in-season phase. Methods: Ten (6 guards and 4 forwards) male basketball players (age 20.9 [0.9] y, stature 195.0 [8.2] cm, and body mass 91.3 [11.3] kg) from the same Division I National Collegiate Athletic Association team were recruited to participate in this study. Individualized training and game loads were assessed using the session rating of perceived exertion at the end of each training and game session, and well-being status was collected before each session. Weekly changes (%) in TL, acute-to-chronic workload ratio, and well-being were determined. Differences in TL and well-being between starting and bench players and between 1-game and 2-game weeks were calculated using magnitude-based statistics. Results: Total weekly TL and acute-to-chronic workload ratio demonstrated high week-to-week variation, with spikes up to 226% and 220%, respectively. Starting players experienced a higher (most likely negative) total weekly TL and similar (unclear) well-being status compared with bench players. Game scheduling influenced TL, with 1-game weeks demonstrating a higher (likely negative) total weekly TL and similar (most likely trivial) well-being status compared with 2-game weeks. Conclusions: These findings provide college basketball coaches information to optimize training strategies during the in-season phase. Basketball coaches should concurrently consider the number of weekly games and player status (starting vs bench player) when creating individualized periodization plans, with increases in TL potentially needed in bench players, especially in 2-game weeks.
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Marques, Mário, Francisco Saavedra, Catarina Abrantes, and Felipe Aidar. "Associations Between Rate of Force Development Metrics and Throwing Velocity in Elite Team Handball Players: a Short Research Report." Journal of Human Kinetics 29A, Special-Issue (September 1, 2011): 53–57. http://dx.doi.org/10.2478/v10078-011-0059-0.
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Associations Between Rate of Force Development Metrics and Throwing Velocity in Elite Team Handball Players: a Short Research ReportPerformance assessment has become an invaluable component of monitoring participant's development in distinct sports, yet limited and contradictory data are available in trained subjects. The purpose of this study was to examine the relationship between ball throwing velocity during a 3-step running throw in elite team handball players and selected measures of rate of force development like force, power, velocity, and bar displacement during a concentric only bench press exercise in elite male handball players. Fitteen elite senior male team handball players volunteered to participate. Each volunteer had power and bar velocity measured during a concentric only bench press test with 25, 35, and 45 kg as well as having one-repetition maximum strength determined. Ball throwing velocity was evaluated with a standard 3-step running throw using a radar gun. The results of this study indicated significant associations between ball velocity and time at maximum rate of force development (0, 66; p<0.05) and rate of force development at peak force (0, 56; p<0.05) only with 25kg load. The current research indicated that ball velocity was only median associated with maximum rate of force development with light loads. A training regimen designed to improve ball-throwing velocity in elite male team handball players should emphasize bench press movement using light loads.
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Carey, D. L., K. Ong, M. E. Morris, J. Crow, and K. M. Crossley. "Predicting ratings of perceived exertion in Australian football players: methods for live estimation." International Journal of Computer Science in Sport 15, no. 2 (December 1, 2016): 64–77. http://dx.doi.org/10.1515/ijcss-2016-0005.
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Abstract The ability of machine learning techniques to predict athlete ratings of perceived exertion (RPE) was investigated in professional Australian football players. RPE is commonly used to quantifying internal training loads and manage injury risk in team sports. Data from global positioning systems, heart-rate monitors, accelerometers and wellness questionnaires were recorded for each training session (n=3398) from 45 professional Australian football players across a full season. A variety of modelling approaches were considered to investigate the ability of objective data to predict RPE. Models were compared using nested cross validation and root mean square error (RMSE) on RPE predictions. A random forest model using player normalised running and heart rate variables provided the most accurate predictions (RMSE ± SD = 0.96 ± 0.08 au). A simplification of the model using only total distance, distance covered at speeds between 18-24 km·h−1, and the product of total distance and mean speed provided similarly accurate predictions (RMSE ± SD = 1.09 ± 0.05 au), suggesting that running distances and speeds are the strongest predictors of RPE in Australian football players. The ability of non-linear machine learning models to accurately predict athlete RPE has applications in live player monitoring and training load planning.
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Iannaccone, Alice, Andrea Fusco, Antanas Skarbalius, Audinga Kniubaite, Cristina Cortis, and Daniele Conte. "Relationship Between External and Internal Load Measures in Youth Beach Handball." International Journal of Sports Physiology and Performance 17, no. 2 (February 1, 2022): 256–62. http://dx.doi.org/10.1123/ijspp.2021-0225.
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Purpose: Assessing the relationship between external load (EL) and internal load (IL) in youth male beach handball players. Methods: A total of 11 field players from the Lithuanian U17 beach handball team were monitored across 14 training sessions and 7 matches. The following EL variables were assessed by means of inertial movement units: PlayerLoad™, accelerations, decelerations, changes of direction, and jumps and total of inertial movements. IL was assessed objectively and subjectively using the summated heart rate zones and training load calculated via session rating of perceived exertion, respectively. Spearman correlations (ρ) were used to assess the relationship between EL and IL. The interindividual variability was investigated using linear mixed models with random intercepts with IL as dependent variable, PlayerLoad™ as the independent variable, and players as random effect. Results: The lowest significant (P < .05) relationship was for high jumps with objective (ρ = .56) and subjective (ρ = .49) IL. The strongest relationship was for PlayerLoad™ with objective (ρ = .9) and subjective (ρ = .84) IL. From the linear mixed model, the estimated SD of the random intercepts was 19.78 arbitrary units (95% confidence interval, 11.75–33.31); SE = 5.26, and R2 = .47 for the objective IL and 6.03 arbitrary units (95% confidence interval, 0.00–7330.6); SE = 21.87; and R2 = .71 for the subjective IL. Conclusions: Objective and subjective IL measures can be used as a monitoring tool when EL monitoring is not possible. Coaches can predict IL based on a given EL by using the equations proposed in this study.
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Iannaccone, Alice, Andrea Fusco, Antanas Skarbalius, Audinga Kniubaite, Cristina Cortis, and Daniele Conte. "Relationship Between External and Internal Load Measures in Youth Beach Handball." International Journal of Sports Physiology and Performance 17, no. 2 (February 1, 2022): 256–62. http://dx.doi.org/10.1123/ijspp.2021-0225.
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Purpose: Assessing the relationship between external load (EL) and internal load (IL) in youth male beach handball players. Methods: A total of 11 field players from the Lithuanian U17 beach handball team were monitored across 14 training sessions and 7 matches. The following EL variables were assessed by means of inertial movement units: PlayerLoad™, accelerations, decelerations, changes of direction, and jumps and total of inertial movements. IL was assessed objectively and subjectively using the summated heart rate zones and training load calculated via session rating of perceived exertion, respectively. Spearman correlations (ρ) were used to assess the relationship between EL and IL. The interindividual variability was investigated using linear mixed models with random intercepts with IL as dependent variable, PlayerLoad™ as the independent variable, and players as random effect. Results: The lowest significant (P < .05) relationship was for high jumps with objective (ρ = .56) and subjective (ρ = .49) IL. The strongest relationship was for PlayerLoad™ with objective (ρ = .9) and subjective (ρ = .84) IL. From the linear mixed model, the estimated SD of the random intercepts was 19.78 arbitrary units (95% confidence interval, 11.75–33.31); SE = 5.26, and R2 = .47 for the objective IL and 6.03 arbitrary units (95% confidence interval, 0.00–7330.6); SE = 21.87; and R2 = .71 for the subjective IL. Conclusions: Objective and subjective IL measures can be used as a monitoring tool when EL monitoring is not possible. Coaches can predict IL based on a given EL by using the equations proposed in this study.
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Luteberget, Live Steinnes, and Matthias Gilgien. "Validation methods for global and local positioning-based athlete monitoring systems in team sports: a scoping review." BMJ Open Sport & Exercise Medicine 6, no. 1 (August 2020): e000794. http://dx.doi.org/10.1136/bmjsem-2020-000794.
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Background/ObjectiveGlobal navigation satellite systems (GNSS) and local positioning systems (LPS) are to date common tools to measure external training load in athletes. The aim of this scoping review was to map out and critically appraise the methods used to validate different GNSS and LPS used in team sports.MethodA total of 48 studies met the eligibility criteria and were included in the review. The reference systems applied in the validations, and the parameters investigated were extracted from the studies.ResultsThe results show a substantial range of reference systems used to validate GNSS and LPS and a substantial number of investigated parameters. The majority of the validation studies have employed relatively simple field-based research designs, with use of measure tape/known distance as reference measure for distance. Timing gates and radar guns were frequently used as reference system for average and peak speed. Fewer studies have used reference system that allow for validation of instantaneous dynamic position, such as infrared camera-based motion capture systems.ConclusionsBecause most validation studies use simple and cost-effective reference systems which do not allow to quantify the exact path athletes travel and hence misjudge the true path length and speed, caution should be taken when interpreting the results of validation studies, especially when comparing results between studies. Studies validating instantaneous dynamic position-based measures is warranted, since they may have a wider application and enable comparisons both between studies and over time.
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Rago, Vincenzo, João Brito, Pedro Figueiredo, Peter Krustrup, and António Rebelo. "Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer." Journal of Human Kinetics 72, no. 1 (March 31, 2020): 279–89. http://dx.doi.org/10.2478/hukin-2019-0113.
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AbstractThis study aimed to examine the interchangeability of two external training load (ETL) monitoring methods: arbitrary vs. individualized speed zones. Thirteen male outfield players from a professional soccer team were monitored during training sessions using 10-Hz GPS units over an 8-week competitive period (n = 302 observations). Low-speed activities (LSA), moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary speed zones as <14.4, 14.4–19.8, 19.8–25.1 and ≥25.2 km·h-1, and using individualized speed zones based on a combination of maximal aerobic speed (MAS, derived from the Yo-yo Intermittent recovery test level 1), maximal sprinting speed (MSS, derived from the maximal speed reached during training) and anaerobic speed reserve (ASR) as <80% MAS, 80–100% MAS, 100% MAS or 29% ASR and ≥30% ASR. Distance covered in both arbitrary and individualized methods was almost certainly correlated in all speed zones (p < 0.01; r = 0.67-0.78). However, significant differences between methods were observed in all speed zones (p < 0.01). LSA was almost certainly higher when using the arbitrary method than when using the individualized method (p < 0.01; ES = 5.47 [5.18; 5.76], respectively). Conversely, MSR, HSR and sprinting speed were higher in the individualized method than in the arbitrary method (p < 0.01; ES = 5.10 [4.82; 5.37], 0.86 [0.72; 1.00] and 1.22 [1.08; 1.37], respectively). Arbitrary and individualized methods for ETL quantification based on speed zones showed similar sensitivity in depicting player locomotor demands. However, since these methods significantly differ at absolute level (based on measurement bias), arbitrary and individualized speed zones should not be used interchangeably.
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Fernandes, Iohanna, João H. Gomes, Levy de Oliveira, Marcos Almeida, João G. Claudino, Camila Resende, Dermival R. Neto, et al. "Monitoring of the Training Load and Well-Being of Elite Rhythmic Gymnastics Athletes in 25 Weeks: A Comparison between Starters and Reserves." Sports 10, no. 12 (November 28, 2022): 192. http://dx.doi.org/10.3390/sports10120192.
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The objective of this study was to monitor the training loads (TL) and well-being of elite rhythmic gymnastics (RG) athletes, as well as compare these variables between starters and reserve gymnasts during 25 weeks of training. Ten athletes from the Brazilian national RG team (17.4 ± 1.1 y of age) were monitored during the general preparatory period (GPP), specific preparatory period (SPP), and pre-competitive period (PCP). The internal TL was quantified with the use of sessional ratings of perceived exertion (sRPE). We assessed well-being daily with a well-being scale. The TL, duration, monotony, and strain were calculated weekly. We found that the internal TL and session durations were 9242 ± 2511 AU and 2014 ± 450 min, respectively. The internal TL, strain, and monotony were greater in the PCP than in the GPP and SPP for starters. In the SPP, there were statistical differences in internal TL (p = 0.036) and strain (p = 0.027) between starters and reserves. In the PCP, there were also statistical differences between starters vs. reserves athletes regarding internal TL (p = 0.027) and strain (p = 0.05). There was no statistically significant difference in well-being between the periods assessed. In conclusion, RG athletes display a higher TL magnitude during the PCP, whereas only reporting non-significant minor variations in well-being. In addition, there is a discrepancy in the TL between starters and reserves.
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Op De Beéck, Tim, Arne Jaspers, Michel S. Brink, Wouter G. P. Frencken, Filip Staes, Jesse J. Davis, and Werner F. Helsen. "Predicting Future Perceived Wellness in Professional Soccer: The Role of Preceding Load and Wellness." International Journal of Sports Physiology and Performance 14, no. 8 (September 1, 2019): 1074–80. http://dx.doi.org/10.1123/ijspp.2017-0864.
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Purpose: The influence of preceding load and future perceived wellness of professional soccer players is unexamined. This paper simultaneously evaluates the external load (EL) and internal load (IL) for different time frames in combination with presession wellness to predict future perceived wellness using machine learning techniques. Methods: Training and match data were collected from a professional soccer team. The EL was measured using global positioning system technology and accelerometry. The IL was obtained using the rating of perceived exertion multiplied by duration. Predictive models were constructed using gradient-boosted regression trees (GBRT) and one naive baseline method. The individual predictions of future wellness items (ie, fatigue, sleep quality, general muscle soreness, stress levels, and mood) were based on a set of EL and IL indicators in combination with presession wellness. The EL and IL were computed for acute and cumulative time frames. The GBRT model’s performance on predicting the reported future wellness was compared with the naive baseline’s performance by means of absolute prediction error and effect size. Results: The GBRT model outperformed the baseline for the wellness items such as fatigue, general muscle soreness, stress levels, and mood. In addition, only the combination of EL, IL, and presession perceived wellness resulted in nontrivial effects for predicting future wellness. Including the cumulative load did not improve the predictive performances. Conclusions: The findings may indicate the importance of including both acute load and presession perceived wellness in a broad monitoring approach in professional soccer.
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Lacome, Mathieu, Christopher Carling, Jean-Philippe Hager, Gerard Dine, and Julien Piscione. "Workload, Fatigue, and Muscle Damage in an Under-20 Rugby Union Team Over an Intensified International Tournament." International Journal of Sports Physiology and Performance 13, no. 8 (September 1, 2018): 1059–66. http://dx.doi.org/10.1123/ijspp.2017-0464.
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Purpose:To examine the effects of an intensified tournament on workload, perceptual and neuromuscular fatigue, and muscle-damage responses in an international under-20 rugby union team.Methods:Players were subdivided into a high-exposure group (HEG, n = 13) and a low-exposure group (LEG, n = 11) according to match-play exposure time. Measures monitored over the 19-d period included training session (n = 10) and match (n = 5) workload determined via global positioning systems and session rating of perceived exertion. Well-being scores, countermovement jump height performance, and blood creatine kinase concentrations were collected at various time points.Results:Analysis of workload cumulated across the tournament entirety for training and match play combined showed that high-speed running distance was similar between groups, while a very likely larger session rating of perceived exertion load was reported in HEG vs LEG. In HEG, high-speed activity fluctuated across the 5 successive matches, albeit with no clear trend for a progressive decrease. No clear tendency for a progressive decrease in well-being scores prior to or following matches was observed in either group. In HEG, trivial to possibly small reductions in postmatch countermovement jump performance were observed, while unclear to most likely moderate increases in prematch blood creatine kinase concentrations occurred until prior to match 4.Conclusions:The magnitude of match-to-match changes in external workload, perceptual and neuromuscular fatigue, and muscle damage was generally unclear or small. These results suggest that irrespective of exposure time to match play players generally maintained performance and readiness to play across the intensified tournament. These findings support the need for holistic systematic player-monitoring programs.
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Tang, Yunqi, Zhaoyang Chen, and Xiangyun Lin. "Characteristics and Rehabilitation Training Effects of Shoulder Joint Dysfunction in Volleyball Players under the Background of Artificial Intelligence." Computational Intelligence and Neuroscience 2022 (June 29, 2022): 1–12. http://dx.doi.org/10.1155/2022/4512795.
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With the development of volleyball technology, the frequent competition, the fierce competition, and the increase of sports load, the requirements for the athletes’ own body, intelligence, combat, heart, and skills are getting higher and higher. Volleyball is one of the most popular sports in the world. It attracts people all over the world with its strong team appeal and its own unique charm. This study mainly discusses the characteristics of shoulder joint dysfunction in volleyball players and the effect of rehabilitation training under the background of artificial intelligence. By sorting out the development process of artificial intelligence technology, it can be analyzed that artificial intelligence technology already has a certain knowledge reserve, can make corresponding mechanized feedback, and can make correct judgments based on experience in more complex situations. This study compared volleyball athletes with handicap and barrier-free shoulder joints and observed the characteristics of shoulder pain, stability, and flexibility caused by subacromial impingement syndrome. It also looked at whether subacromial impingement syndrome athletes differ in volleyball spiking sequence and mobilization and recruitment of muscle power during swing spikes compared to athletes with normal shoulder function in the full kinetic chain. According to the volleyball intelligent competition platform, the implementation and application of ideas such as data collection, result feedback, adjustment of training plan, implementation of training plan, and real-time monitoring are regularly monitored. On the one hand, through timely assessment and detection of shoulder function of volleyball players, functional training is carried out for weaknesses to prevent injury; on the other hand, after a mild injury occurs, timely targeted training should be taken to find and correct wrong actions, and strengthen the weak part of muscle strength, so as to reduce the probability of repeated injury and improve sports performance and athletic ability. In the new system, after collecting and sorting, testers can directly upload to the web page in the form of Excel for automatic filling, grasp the test information of athletes in time, generate automatic warning, and save time. The monitoring content determined by this study mainly includes three index systems, including load, training preparation performance, and recovery. According to the self-provided evaluation system of relevant test equipment and the experience of expert coaches, the evaluation standards for each index are formulated. There was a statistically significant difference in the scores between the rehabilitation group and the pre-rehabilitation group during the study ( P < 0.05 ). This study attempts to find the characteristics and rules of FMS scores of women’s volleyball players of different levels, so as to provide more targeted physical training for volleyball players, promote the all-round development of physical fitness, and avoid the risk of sports injuries. This study provides more effective and comprehensive recommendations for the prevention and recovery of shoulder injuries in volleyball players. This study provides more effective and comprehensive recommendations for the prevention and recovery of shoulder injuries in volleyball players. The results of the study can provide reference for the scientific training and rehabilitation of volleyball players and make suggestions for the treatment and prevention of subacromial impingement syndrome.