Purpose: This study described and analyzed practices and perceptions of rhythmic gymnastics coaches, medical staff, and athletes on training-load management. Methods: Online surveys were distributed among professionals and gymnasts involved in rhythmic gymnastics training across the world. One hundred (50 coaches, 12 medical staff, and 38 gymnasts) participants from 25 different countries completed the surveys. Results: Respondents stated using coaches’ perception on a daily basis as a method of monitoring external (57%) and internal (58%) load, recovery/fatigue (52%), and performance (64%). Variables and methods (eg, wearable devices, athlete self-reported measures, session rating of perceived exertion), and metrics (eg, acute and chronic load) commonly reported in the training-load literature and other sports were not frequently used in rhythmic gymnastics. The majority of coaches (60.3% [17%]) perceived that maladaptation rarely or never occurred. Medical staff involvement in sharing and discussing training-load information was limited, and they perceived that the measurement of athletes’ recovery/fatigue was poor. Gymnasts noted good quality in relation to the measurement of performance. Most participants (≥85%) believed that a specific training-load management model for rhythmic gymnastics could be very or extremely effective. Conclusions: In conclusion, rhythmic gymnastics coaches’ perception is the most commonly used strategy to monitor load, recovery/fatigue, and performance; although, this could be a limited method to guarantee effective training-load management in this sport.
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Paula B. Debien, Thiago F. Timoteo, Tim J. Gabbett, and Maurício G. Bara Filho
Michael J.A. Speranza, Tim J. Gabbett, David A. Greene, Rich D. Johnston, and Andrew D. Townshend
This study investigated the relationship between 2 different assessments of tackling ability, physical qualities, and match-play performance in semiprofessional rugby league players. A total of 18 semiprofessional rugby league players (mean [SD]: age = 23.1 [2.0] y and body mass = 98.8 [11.8] kg) underwent tests of upper- and lower-body strength and power. Tackling ability was assessed using video analysis of under- and over-the-ball tackle drills. A total of 2360 tackles were analyzed from match play. Over-the-ball tackle ability was positively related to the proportion of dominant tackles (Spearman rank-order correlation coefficients [r s] = .52; 95% confidence interval [CI] .07–.79, P = .03) and average play-the-ball speeds (r s = .50; 95% CI .04–.78, P = .03) and negatively related to tackles that conceded offloads (r s = −.55; 95% CI −.78 to .04, P = .04). Under-the-ball tackle ability was significantly related to the proportion of dominant tackles (r s = .57; 95% CI .14–.82, P = .01) and missed tackles (r s = −.48; 95% CI −.77 to .02, P = .05). Good over-the-ball tacklers performed proportionally more dominant tackles, allowed significantly fewer offloads, and had longer average play-the-ball speeds. Good under-the-ball tacklers missed proportionately fewer tackles. This study suggests that both the under-the-ball and over-the-ball standardized tackle assessments are associated with varying indicators of match-play tackle performance and justifies the practical utility of these tests to assess and develop both types of tackles.
Nick B. Murray, Georgia M. Black, Rod J. Whiteley, Peter Gahan, Michael H. Cole, Andy Utting, and Tim J. Gabbett
Throwing loads are known to be closely related to injury risk. However, for logistic reasons, typically only pitchers have their throws counted, and then only during innings. Accordingly, all other throws made are not counted, so estimates of throws made by players may be inaccurately recorded and underreported. A potential solution to this is the use of wearable microtechnology to automatically detect, quantify, and report pitch counts in baseball. This study investigated the accuracy of detection of baseball pitching and throwing in both practice and competition using a commercially available wearable microtechnology unit.
Seventeen elite youth baseball players (mean ± SD age 16.5 ± 0.8 y, height 184.1 ± 5.5 cm, mass 78.3 ± 7.7 kg) participated in this study. Participants performed pitching, fielding, and throwing during practice and competition while wearing a microtechnology unit. Sensitivity and specificity of a pitching and throwing algorithm were determined by comparing automatic measures (ie, microtechnology unit) with direct measures (ie, manually recorded pitching counts).
The pitching and throwing algorithm was sensitive during both practice (100%) and competition (100%). Specificity was poorer during both practice (79.8%) and competition (74.4%).
These findings demonstrate that the microtechnology unit is sensitive to detect pitching and throwing events, but further development of the pitching algorithm is required to accurately and consistently quantify throwing loads using microtechnology.
Nicola Furlan, Mark Waldron, Kathleen Shorter, Tim J. Gabbett, John Mitchell, Edward Fitzgerald, Mark A. Osborne, and Adrian J. Gray
To investigate temporal variation in running intensity across and within halves and evaluate the agreement between match-analysis indices used to identify fluctuations in running intensity in rugby sevens.
Data from a 15-Hz global positioning system (GPS) were collected from 12 elite rugby sevens players during the IRB World Sevens Series (N = 21 full games). Kinematic (eg, relative distance [RD]) and energetic (eg, metabolic power [MP]) match-analysis indices were determined from velocity–time curves and used to investigate between-halves variations. Mean MP and RD were used to identify peak 2-minute periods of play. Adjacent 2-minute periods (prepeak and postpeak) were compared with peak periods to identify changes in intensity. MP and RD were expressed relative to maximal oxygen uptake (V̇O2max) and speed at V̇O2max, respectively, and compared in their ability to describe the intensity of peak periods and their temporal occurrence.
Small to moderate reductions were present for kinematic (RD; 8.9%) and energetic (MP; 6%) indices between halves. Peak periods (RD = 130 m/min, MP =13 W/kg) were higher (P < .001) than the match average (RD = 94 m/min, MP = 9.5 W/kg) and the prepeak and postpeak periods (P < .001). RD underestimated the intensity of peak periods compared with MP (bias 16%, limits of agreement [LoA] ± 6%). Peak periods identified by RD and MP were temporally dissociated (bias 21 s, LoA ± 212 s).
The findings suggest that running intensity varies between and within halves; however, the index used will influence both the magnitude and the temporal identification of peak periods.
Michael J.A. Speranza, Tim J. Gabbett, David A. Greene, Rich D. Johnston, Andrew D. Townshend, and Brett O’Farrell
This study investigated the relationship between 2 tests of tackling ability, muscle strength, and power in semiprofessional rugby league players. Thirty-one players, 19 first-grade and 12 second-grade, underwent tests of muscle strength (1-repetition-maximum bench press, chin-up, and squat) and power (plyometric push-up and countermovement jump). Tackling ability was assessed via video analysis of under-and over-the-ball tackle drills. The first-grade players had significantly greater scores in both the under-the-ball (P = .03, effect size [ES] = 0.84, 95% CI 0.07–1.50) and over-the-ball tackling-ability tests (P < .001, ES =1.86, 95% CI 0.83–2.52) than the second-grade players. A large, significant relationship was found between under- and over-the-ball tackling ability (r = .55, 95% CI .24–.76, P = .001). Lower-body strength (r = .37, 95% CI .02–.64, P = .04) was moderately associated with under-the-ball tackling ability, whereas over-the-ball tackling ability was moderately associated with plyometric push-up performance (r = .39, 95% CI .04–.65, P = .03). This study found that over-the-ball tackling ability was significantly associated with under-the-ball tackling in semiprofessional rugby league players. Furthermore, it was found that, compared with the second-grade players, the first-grade players had superior tackle ability in both tackle drills. In this study it was observed that plyometric push-up peak power was significantly related to over-the-ball tackling ability and absolute lower-body strength was associated with under-the-ball tackling ability. These findings provide skill coaches and strength and conditioning staff a greater understanding of elements that contribute to effective tackling ability.
Georgia M. Black, Tim J. Gabbett, Richard D. Johnston, Geraldine Naughton, Michael H. Cole, and Brian Dawson
Purpose: With female Australian football (AF) gaining popularity, understanding match demands is becoming increasingly important. The aim of this study was to compare running performances of rotated and whole-quarter state-level female AF players during match quarters. Methods : Twenty-two state-level female AF midfielders wore Global Positioning System units during 14 games to evaluate activity profiles. The Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1) was used as a measure of high-intensity running ability. Data were categorized into whole quarter, rotation bout 1, and rotation bout 2 before being further divided into quartiles. Players were separated into high- or low-Yo-Yo IR1 groups using a median split based on their Yo-Yo IR1 performance. Short (4–6 min), moderate (6–12 min), and long (12–18 min) on-field bout activity profiles were compared with whole-quarter players. Results: High Yo-Yo IR1 performance allowed players to cover greater relative distances (ES = 0.57–0.88) and high-speed distances (ES = 0.57–0.86) during rotations. No differences were reported between Yo-Yo IR1 groups when players were required to play whole quarters (ES ≤ 0.26, likelihood ≤64%). Players who were on field for short to moderate durations exhibited greater activity profiles than whole-quarter players. Conclusions: Superior high-speed running ability results in a greater activity profile than for players who possess lower high-speed running ability. The findings also highlight the importance of short to moderate (4–12 min) rotation periods and may be used to increase high-intensity running performance within quarters in female AF players.
Jake Schuster, Dan Howells, Julien Robineau, Anthony Couderc, Alex Natera, Nick Lumley, Tim J. Gabbett, and Nick Winkelman
Rugby sevens, a sport new to the Olympics, features high-intensity intermittent running and contact efforts over short match durations, normally 6 times across 2 to 3 d in a tournament format. Elite rugby sevens seasons often include over a dozen competitive tournaments over less than 9 months, demanding deliberate and careful training-stress balance and workload management alongside development of the necessary physical qualities required for competition. Focus on running and repeated power skills, strength, and match-specific conditioning capacities is advised. Partial taper approaches in combination with high-speed running (>5 m/s from GPS measures) before and between tournaments in succession may reduce injury rates and enhance performance. In a sport with substantial long-haul intercontinental travel and repetitive chronic load demands, management of logistics including nutrition and recovery is inclusive of the formula for success in the physical preparation of elite rugby sevens athletes.
Georgia M. Black, Tim J. Gabbett, Rich D. Johnston, Michael H. Cole, Geraldine Naughton, and Brian Dawson
Purpose: The transition of female Australian football (AF) players from amateur to semielite competitions has the potential for athletes to be underprepared for match play. To gain an understanding of the match demands of female football, the aims of this study were to highlight the physical qualities that discriminate selected and nonselected female AF players, investigate activity profiles of female AF players, and gain an understanding of the influence of physical qualities on performance in female AF Methods: Twenty-two female AF state academy players (mean [SD]: age = 23.2 [4.5] y) and 27 nonselected players (mean [SD]: age = 23.4 [4.9] y) completed a Yo-Yo intermittent recovery test level 1, countermovement jump, and 30-m sprint tests were completed prior to the competitive season. During 14 matches, players wore global positioning system units to describe the running demands of match play. Results: Selected players were faster over 30 m (ES = 0.57; P = .04) and covered greater distances on the Yo-Yo IR1 (ES = 1.09; P < .001). Selected midfielders spent greater time on the field and covered greater total distances (ES = 0.73–0.85; P < .01). Players faster over 5 m (r = −.612) and 30 m (r = −.807) and who performed better on the Yo-Yo IR1 (r = .489) covered greater high-speed distances during match play. Conclusions: An emphasis should be placed on the development of physical fitness in this playing group to ensure optimal preparation for the national competition.
Pitre C. Bourdon, Marco Cardinale, Andrew Murray, Paul Gastin, Michael Kellmann, Matthew C. Varley, Tim J. Gabbett, Aaron J. Coutts, Darren J. Burgess, Warren Gregson, and N. Timothy Cable
Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best methodologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the field has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on “Monitoring Athlete Training Loads—The Hows and the Whys” was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary practices in this rapidly growing field and also to investigate where it may branch to in the future. This consensus statement brings together the key findings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.