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1.
PLoS One ; 19(5): e0298709, 2024.
Article in English | MEDLINE | ID: mdl-38743656

ABSTRACT

This is the first study to assess longitudinal changes in anthropometric, physiological, and physical qualities of international women's rugby league players. Thirteen forwards and 11 backs were tested three times over a 10-month period. Assessments included: standing height and body mass, body composition measured by dual x-ray absorptiometry (DXA), a blood panel, resting metabolic rate (RMR) assessed by indirect calorimetry, aerobic capacity (i.e.,[Formula: see text]) evaluated by an incremental treadmill test, and isometric force production measured by a force plate. During the pre-season phase, lean mass increased significantly by ~2% for backs (testing point 1: 47 kg; testing point 2: 48 kg) and forwards (testing point 1: 50 kg; testing point 2: 51 kg) (p = ≤ 0.05). Backs significantly increased their [Formula: see text] by 22% from testing point 1 (40 ml kg-1 min-1) to testing point 3 (49 ml kg-1 min-1) (p = ≤ 0.04). The [Formula: see text] of forwards increased by 10% from testing point 1 (41 ml kg-1 min-1) to testing point 3 (45 ml kg-1 min-1), however this change was not significant (p = ≥ 0.05). Body mass (values represent the range of means across the three testing points) (backs: 68 kg; forwards: 77-78 kg), fat mass percentage (backs: 25-26%; forwards: 30-31%), resting metabolic rate (backs: 7 MJ day-1; forwards: 7 MJ day-1), isometric mid-thigh pull (backs: 2106-2180 N; forwards: 2155-2241 N), isometric bench press (backs: 799-822 N; forwards: 999-1024 N), isometric prone row (backs: 625-628 N; forwards: 667-678 N) and bloods (backs: ferritin 21-29 ug/L, haemoglobin 137-140 g/L, iron 17-21 umol/L, transferrin 3 g/L, transferring saturation 23-28%; forwards: ferritin 31-33 ug/L, haemoglobin 141-145 g/L, iron 20-23 umol/L, transferrin 3 g/L, transferrin saturation 26-31%) did not change (p = ≥ 0.05). This study provides novel longitudinal data which can be used to better prepare women rugby league players for the unique demands of their sport, underpinning female athlete health.


Subject(s)
Basal Metabolism , Body Composition , Football , Humans , Female , Adult , Body Composition/physiology , Football/physiology , Longitudinal Studies , Young Adult , Anthropometry , Athletes , Absorptiometry, Photon , Exercise Test , Body Mass Index , Rugby
2.
J Sci Med Sport ; 26(3): 195-201, 2023 Mar.
Article in English | MEDLINE | ID: mdl-37005119

ABSTRACT

OBJECTIVES: Identify the frequency, propensity, and factors related to tackle events which result in contact with the head in elite-level women's rugby league. DESIGN: Prospective video analysis study. METHODS: Video footage from 59 Women's Super League matches were analysed (n = 14,378 tackle events). All tackle events were coded as no head contact or head contact. Other independent variables included: area contacting head, impacted player, concussion outcome, penalty outcome, round of competition, time in match and team standard. RESULTS: There were 83.0 ±â€¯20.0 (propensity 304.0/1000 tackle events) head contacts per match. The propensity of head contact was significantly greater for the tackler than ball-carrier (178.5 vs. 125.7/1000 tackle events; incident rate ratio 1.42, 95 % confidence interval 1.34 to 1.50). Head contacts occurring from an arm, shoulder, and head occurred significantly more than any other contact type. The propensity of concussions was 2.7/1000 head contacts. There was no significant influence of team standard or time in match on the propensity of head contacts. CONCLUSIONS: The observed head contacts can inform interventions, primarily focusing on the tackler not contacting the ball-carrier's head. The tackler's head should also be appropriately positioned to avoid contact with the ball-carrier's knee (highest propensity for concussion). The findings are consistent with other research in men's rugby. Law modifications and/or enforcement (reducing the number of un-penalised head contacts), concurrent with coaching interventions (optimising head placement or reducing the head being contacted) may help minimise head contact risk factors for women's rugby league.


Subject(s)
Athletic Injuries , Brain Concussion , Football , Male , Humans , Female , Athletic Injuries/epidemiology , Athletic Injuries/prevention & control , Athletic Injuries/etiology , Rugby , Brain Concussion/epidemiology , Brain Concussion/prevention & control , Brain Concussion/complications , Risk Factors
3.
Eur J Sport Sci ; 23(7): 1131-1145, 2023 Jul.
Article in English | MEDLINE | ID: mdl-36803563

ABSTRACT

This study quantified and compared the collision and non-collision match characteristics across age categories (i.e. U12, U14, U16, U18, Senior) for both amateur and elite playing standards from Tier 1 rugby union nations (i.e. England, South Africa, New Zealand). Two-hundred and one male matches (5911 min ball-in-play) were coded using computerised notational analysis, including 193,708 match characteristics (e.g. 83,688 collisions, 33,052 tackles, 13,299 rucks, 1006 mauls, 2681 scrums, 2923 lineouts, 44,879 passes, 5568 kicks). Generalised linear mixed models with post-hoc comparisons and cluster analysis compared the match characteristics by age category and playing standard. Overall significant differences (p < 0.001) between age category and playing standard were found for the frequency of match characteristics, and tackle and ruck activity. The frequency of characteristics increased with age category and playing standard except for scrums and tries that were the lowest at the senior level. For the tackle, the percentage of successful tackles, frequency of active shoulder, sequential and simultaneous tackles increased with age and playing standard. For ruck activity, the number of attackers and defenders were lower in U18 and senior than younger age categories. Cluster analysis demonstrated clear differences in all and collision match characteristics and activity by age category and playing standard. These findings provide the most comprehensive quantification and comparison of collision and non-collision activity in rugby union demonstrating increased frequency and type of collision activity with increasing age and playing standard. These findings have implications for policy to ensure the safe development of rugby union players throughout the world.


The safety of rugby union, especially the tackle, has previously been questioned but limited data are available to understand the collision and non-collision match characteristics between different age categories and playing standards.The frequency of collision and non-collision match characteristics increase with age and playing standard except for the frequency of scrums and tries which are lowest at the Senior Elite level. The activity of the tackle and ruck are also different between age categories and playing standards.Hierarchical cluster analysis demonstrated clear differences in all and collision match characteristics between junior (i.e. U12, U14, U16), and amateur (i.e. U18 and senior) and elite (i.e. U18 and senior) playing levels.Governing bodies and practitioners should be aware of the differences in collision and non-collision match characteristics by age and playing standard, when reviewing future versions of rugby union.


Subject(s)
Football , Humans , Male , Rugby , Athletes , South Africa
4.
BMJ Open Sport Exerc Med ; 8(4): e001440, 2022.
Article in English | MEDLINE | ID: mdl-36249486

ABSTRACT

The importance of contributors that can result in negative player outcomes in sport and the feasibility and barriers to modifying these to optimise player health and well-being have yet to be established. Within rugby codes (rugby league, rugby union and rugby sevens), within male and female cohorts across playing levels (full-time senior, part-time senior, age grade), this project aims to develop a consensus on contributors to negative biopsychosocial outcomes in rugby players (known as the CoNBO study) and establish stakeholder perceived importance of the identified contributors and barriers to their management. This project will consist of three parts; part 1: a systematic review, part 2: a three-round expert Delphi study and part 3: stakeholder rating of feasibility and barriers to management. Within part 1, systematic searches of electronic databases (PubMed, Scopus, MEDLINE, SPORTDiscus, CINAHL) will be performed. The systematic review protocol is registered with PROSPERO. Studies will be searched to identify physical, psychological and/or social factors resulting in negative player outcomes in rugby. Part 2 will consist of a three-round expert Delphi consensus study to establish additional physical, psychological and/or social factors that result in negative player outcomes in rugby and their importance. In part 3, stakeholders (eg, coaches, chief executive officers and players) will provide perceptions of the feasibility and barriers to modifying the identified factors within their setting. On completion, several manuscripts will be submitted for publication in peer-reviewed journals. The findings of this project have worldwide relevance for stakeholders in the rugby codes. PROSPERO registration number CRD42022346751.

5.
BMJ Open Sport Exerc Med ; 8(3): e001287, 2022.
Article in English | MEDLINE | ID: mdl-35979431

ABSTRACT

Objectives: In part 1, the objective was to undertake a systematic scoping review of applied sports science and sports medicine in women's rugby, and in part 2 to develop a consensus statement on future research priorities. Design: In part 1, a systematic search of PubMed (MEDLINE), Scopus and SPORTDiscus (EBSCOhost) was undertaken from the earliest records to January 2021. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, the PRISMA extension for Scoping Reviews, and the PRISMA extension protocols were followed. In part 2, 31 international experts in women's rugby (ie, elite players, sports scientists, medical clinicians, sports administrators) participated in a three-round Delphi consensus method. These experts reviewed the findings from part 1 and subsequently provided a list of priority research topics in women's rugby. Research topics were grouped into expert-based themes and expert-based subthemes via content analysis. Expert-based themes and expert-based subthemes were ranked from very low to very high research priority on a 1-5 Likert scale. Consensus was defined by ≥70% agreement. The median research priority agreement and IQR were calculated for each expert-based theme and subtheme. Data sources: PubMed (MEDLINE), Scopus and SPORTDiscus (EBSCOhost). Eligibility criteria for selecting studies: Studies were eligible for inclusion if they investigated applied sports science or sports medicine in women's rugby. Results: In part 1, the systematic scoping review identified 123 studies, which were categorised into six sports science and sports medicine evidence-based themes: injury (n=48), physical performance (n=32), match characteristics (n=26), fatigue and recovery (n=6), nutrition (n=6), and psychology (n=5). In part 2, the Delphi method resulted in three expert-based themes achieving consensus on future research priority in women's rugby: injury (5.0 (1.0)), female health (4.0 (1.0)) and physical performance (4.0 (1.0)). Summary/Conclusion: This two-part systematic scoping review and Delphi consensus is the first study to summarise the applied sports science and sports medicine evidence base in women's rugby and establish future research priorities. The summary tables from part 1 provide valuable reference information for researchers and practitioners. The three expert-based themes that achieved consensus in part 2 (injury, female health and physical performance) provide clear direction and guidance on future research priorities in women's rugby. The findings of this two-part study facilitate efficient and coordinated use of scientific resources towards high-priority research themes relevant to a wide range of stakeholders in women's rugby.

6.
J Sports Sci ; 40(13): 1436-1449, 2022 Jul.
Article in English | MEDLINE | ID: mdl-35694782

ABSTRACT

This study aimed to 1) develop a consensus (≥70% agreement between experts) on injury risk factors specific to women playing rugby league, 2) establish the importance of the identified injury risk factors and the feasibility of mitigating these risk factors and 3) establish context specific barriers to injury risk management. Aim 1: A Delphi panel, consisting of 12 experts in rugby league and injury (e.g., physiotherapists, research scientists) were asked to identify injury risk factors specific to women playing rugby league. Aim 2: seven coaches of women's rugby league teams were asked to rate each risk factor that achieved consensus by their importance and feasibility to manage. Aim 3: Coaches reported barriers which restrict injury risk factor mitigation. Of the 53 injury risk factors which achieved consensus, the five injury risk factors with the highest combination of importance and feasibility ratings were: "poor tackle technique", "a lack of pre-season intensity", "training session are too short", "the current medical standards", and "limited access to physiotherapists". Following the identification of injury risk factors, their feasibility to manage and context specific barriers, this study proposes three constraint driven, integrated solutions which may reduce the barriers which limit injury risk factor management.


Subject(s)
Athletic Injuries , Football , Athletic Injuries/prevention & control , Delphi Technique , Female , Football/injuries , Humans , Risk Factors , Rugby
7.
Sci Med Footb ; 6(1): 15-28, 2022 02.
Article in English | MEDLINE | ID: mdl-35236228

ABSTRACT

Rugby league tackle video analysis research typically uses technical criteria from coaching cues or tackle variables from rugby union. As such, content validity and relevance could be questioned. A video analysis framework that establishes appropriate variables for rugby league is therefore required. The study aimed to adopt a 5-stage process to establish a video analysis framework for the rugby league tackle, which was content valid, relevant and reliable.The 5-stage process included 1) creation of draft video analysis framework, using available rugby tackle research, 2) expert group recruitment and critique, 3) refinement of framework to establish content validity, 4) response process validity task and agreement within expert group, 5) intra- and inter-reliability testing using Kappa statistics.The agreed framework comprised six phases including; tackle event, defensive start point, pre-contact, initial contact, post-contact and play-the-ball. Within the identified phases, 63 variables were established. The intra- and inter-reliability testing resulted in strong agreement within all phases.The video analysis framework can be used in rugby league tackle research, categorising complex tackle events, such as injurious or optimal tackles, improving both player welfare and performance. The application of the framework to future rugby league research will increase coherence and usefulness of research findings.


Subject(s)
Communications Media , Football , Football/physiology , Reproducibility of Results , Rugby , Video Recording
8.
PLoS One ; 17(1): e0249803, 2022.
Article in English | MEDLINE | ID: mdl-35100275

ABSTRACT

Participation in women's rugby league has been growing since the foundation of the English women's rugby league Super League in 2017. However, the evidence base to inform women's rugby league remains sparse. This study provides the largest quantification of anthropometric and physical qualities of women's rugby league players to date, identifying differences between positions (forwards & backs) and playing level (Women's Super League [WSL] vs. International). The height, weight, body composition, lower body strength, jump height, speed and aerobic capacity of 207 players were quantified during the pre-season period. Linear mixed models and effects sizes were used to determine differences between positions and levels. Forwards were significantly (p < 0.05) heavier (forwards: 82.5 ± 14.8kg; backs: 67.7 ± 9.2kg) and have a greater body fat % (forwards: 37.7 ± 6.9%; backs: 30.4 ± 6.3%) than backs. Backs had significantly greater lower body power measured via jump height (forwards: 23.5 ± 4.4cm; backs: 27.6 ± 4.9cm), speed over 10m (forwards: 2.12 ± 0.14s; backs: 1.98 ± 0.11s), 20m (forwards: 3.71 ± 0.27s; backs: 3.46 ± 0.20s), 30m (forwards: 5.29 ± 0.41s; backs: 4.90 ± 0.33s), 40m (forwards: 6.91 ± 0.61s; backs: 6.33 ± 0.46s) and aerobic capacity (forwards: 453.4 ± 258.8m; backs: 665.0 ± 298.2m) than forwards. Additionally, international players were found to have greater anthropometric and physical qualities in comparison to their WSL counterparts. This study adds to the limited evidence base surrounding the anthropometric and physical qualities of elite women's rugby league players. Comparative values for anthropometric and physical qualities are provided which practitioners may use to evaluate the strengths and weaknesses of players, informing training programs to prepare players for the demands of women's rugby league.


Subject(s)
Body Weights and Measures/statistics & numerical data , Physical Fitness , Adult , Body Composition , Body Height , Body Weight , Female , Humans , Muscle Strength , Rugby , Running , Young Adult
9.
BMJ Open Sport Exerc Med ; 7(3): e001108, 2021.
Article in English | MEDLINE | ID: mdl-34394953

ABSTRACT

Women's rugby (rugby league, rugby union and rugby sevens) has recently grown in participation and professionalisation. There is under-representation of women-only cohorts within applied sport science and medicine research and within the women's rugby evidence base. The aims of this article are: Part 1: to undertake a systematic-scoping review of the applied sport science and medicine of women's rugby, and Part 2: to develop a consensus statement on future research priorities. This article will be designed in two parts: Part 1: a systematic-scoping review, and Part 2: a three-round Delphi consensus method. For Part 1, systematic searches of three electronic databases (PubMed (MEDLINE), Scopus, SPORTDiscus (EBSCOhost)) will be performed from the earliest record. These databases will be searched to identify any sport science and medicine themed studies within women's rugby. The Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews will be adhered to. Part 2 involves a three-round Delphi consensus method to identify future research priorities. Identified experts in women's rugby will be provided with overall findings from Part 1 to inform decision-making. Participants will then be asked to provide a list of research priority areas. Over the three rounds, priority areas achieving consensus (≥70% agreement) will be identified. This study has received institutional ethical approval. When complete, the manuscript will be submitted for publication in a peer-reviewed journal. The findings of this article will have relevance for a wide range of stakeholders in women's rugby, including policymakers and governing bodies.

10.
Int J Sports Physiol Perform ; 16(12): 1880-1887, 2021 12 01.
Article in English | MEDLINE | ID: mdl-34193624

ABSTRACT

PURPOSE: To compare the physical qualities between academy and international youth rugby league (RL) players using principal component analysis. METHODS: Six hundred fifty-four males (age = 16.7 [1.4] y; height = 178.4 [13.3] cm; body mass = 82.2 [14.5] kg) from 11 English RL academies participated in this study. Participants completed anthropometric, power (countermovement jump), strength (isometric midthigh pull; IMTP), speed (10 and 40 m speed), and aerobic endurance (prone Yo-Yo IR1) assessments. Principal component analysis was conducted on all physical quality measures. A 1-way analysis of variance with effect sizes was performed on 2 principal components (PCs) to identify differences between academy and international backs, forwards, and pivots at under 16 and 18 age groups. RESULTS: Physical quality measures were reduced to 2 PCs explaining 69.4% of variance. The first PC (35.3%) was influenced by maximum and 10-m momentum, absolute IMTP, and body mass. Ten and forty-meter speed, body mass and fat, prone Yo-Yo, IMTP relative, maximum speed, and countermovement jump contributed to PC2 (34.1%). Significant differences (P < .05, effect size = -1.83) were identified between U18 academy and international backs within PC1. CONCLUSION: Running momentum, absolute IMTP, and body mass contributed to PC1, while numerous qualities influenced PC2. The physical qualities of academy and international youth RL players are similar, excluding U18 backs. Principal component analysis can reduce the dimensionality of a data set and help identify overall differences between playing levels. Findings suggest that RL practitioners should measure multiple physical qualities when assessing physical performance.


Subject(s)
Athletic Performance , Football , Adolescent , Anthropometry , Humans , Male , Muscle Strength , Physical Fitness , Principal Component Analysis , Rugby
11.
Int J Sports Physiol Perform ; 16(4): 511-516, 2021 04 01.
Article in English | MEDLINE | ID: mdl-33440340

ABSTRACT

PURPOSE: To evaluate the relative importance and predictive ability of salivary immunoglobulin A (s-IgA) measures with regards to upper respiratory illness (URI) in youth athletes. METHODS: Over a 38-week period, 22 youth athletes (age = 16.8 [0.5] y) provided daily symptoms of URI and 15 fortnightly passive drool saliva samples, from which s-IgA concentration and secretion rate were measured. Kernel-smoothed bootstrapping generated a balanced data set with simulated data points. The random forest algorithm was used to evaluate the relative importance (RI) and predictive ability of s-IgA concentration and secretion rate with regards to URI symptoms present on the day of saliva sampling (URIday), within 2 weeks of sampling (URI2wk), and within 4 weeks of sampling (URI4wk). RESULTS: The percentage deviation from average healthy s-IgA concentration was the most important feature for URIday (median RI 1.74, interquartile range 1.41-2.07). The average healthy s-IgA secretion rate was the most important feature for URI4wk (median RI 0.94, interquartile range 0.79-1.13). No feature was clearly more important than any other when URI symptoms were identified within 2 weeks of sampling. The values for median area under the curve were 0.68, 0.63, and 0.65 for URIday, URI2wk, and URI4wk, respectively. CONCLUSIONS: The RI values suggest that the percentage deviation from average healthy s-IgA concentration may be used to evaluate the short-term risk of URI, while the average healthy s-IgA secretion rate may be used to evaluate the long-term risk. However, the results show that neither s-IgA concentration nor secretion rate can be used to accurately predict URI onset within a 4-week window in youth athletes.


Subject(s)
Respiratory Tract Infections , Adolescent , Athletes , Humans , Immunoglobulin A/metabolism , Immunoglobulin A, Secretory/metabolism , Saliva/metabolism , Secretory Rate
12.
J Strength Cond Res ; 35(4): 1066-1073, 2021 Apr 01.
Article in English | MEDLINE | ID: mdl-30358699

ABSTRACT

ABSTRACT: Sawczuk, T, Jones, B, Scantlebury, S, and Till, K. Influence of perceptions of sleep on well-being in youth athletes. J Strength Cond Res 35(4): 1066-1073, 2021-To date, most research considering well-being questionnaires has only considered the training stress imposed on the athlete, without evaluating the questionnaire's relationship with a measure of recovery (e.g., sleep). This study aimed to assess the influence of sleep duration (Sduration), sleep quality (Squality), and sleep index (Sindex; Sduration × Squality) on well-being in youth athletes, while accounting for the known training stressors of training load and exposure to match play. Forty-eight youth athletes (age 17.3 ± 0.5 years) completed a daily questionnaire including well-being (DWBno-sleep; fatigue, muscle soreness, stress, and mood) measures, Perceived Recovery Status Scale (PRS), the previous day's training loads, Sduration, and Squality every day for 13 weeks. Linear mixed models assessed the impact of Sduration, Squality, and Sindex on DWBno-sleep, its individual subscales, and PRS. Sduration had a small effect on DWBno-sleep (d = 0.31; ±0.09), fatigue (d = 0.42; ±0.11), and PRS (d = 0.25; ±0.09). Squality had a small effect on DWBno-sleep (d = 0.47; ±0.08), fatigue (d = 0.53; ±0.11), stress (d = 0.35; ±0.07), mood (d = 0.41; ±0.09), and PRS (d = 0.37; ±0.08). Sindex had a small effect on DWBno-sleep (d = 0.44; ±0.08), fatigue (d = 0.55; ±0.11), stress (d = 0.29; ±0.07), mood (d = 0.37; ±0.09), and PRS (d = 0.36; ±0.09). The results indicate that an athlete's perceptions of sleep are associated with deviations in well-being measures and should be used as an input to the monitoring process rather than as part of the outcome well-being score. The sleep index is suggested as a potential input because it provides information on both the duration and quality of the sleep experienced.


Subject(s)
Physical Conditioning, Human , Adolescent , Athletes , Fatigue/etiology , Humans , Perception , Sleep
13.
J Strength Cond Res ; 35(12): 3400-3406, 2021 Dec 01.
Article in English | MEDLINE | ID: mdl-32084108

ABSTRACT

ABSTRACT: Scantlebury, S, Till, K, Sawczuk, T, Dalton-Barron, N, Phibbs, P, and Jones, B. The frequency and intensity of representative and nonrepresentative late adolescent team-sport athletes' training schedules. J Strength Cond Res 35(12): 3400-3406, 2021-This study aimed to identify and compare the training frequency and intensity (via session rating of perceived exertion load [sRPE load]) of representative and nonrepresentative late adolescent athletes. Thirty-six team sport athletes completed a web-based questionnaire daily over an 8-month period, reporting their training/match activities from the previous day. Athletes were categorized as representative (academy/county/international) or nonrepresentative (club/school) depending on the highest level of their sport they participated. Mean weekly frequencies and sRPE load of different training/match activities were quantified for each athlete across 5 school terms. Mann-Whitney U tests established the significance of differences and effect sizes between playing standards for mean weekly frequencies and mean sRPE load. Within-athlete weekly sRPE loads were highly variable for both playing standards; however, representative level athletes participated in significantly more activity outside of school compared with nonrepresentative athletes during November-December (effect size; 0.43-club technical training; 0.36-club matches), January-February (effect size; 0.78-club technical training; 0.75-club matches), and February-March (effect size; 0.63-club technical training; 0.44-club matches). Therefore, club and school coaches must ensure that all elements of representative athletes training schedules are coordinated and flexible to promote positive adaptions to training such as skill and physical development and prevent maladaptive responses such as overuse injury and nonfunctional overreaching. A cooperative and malleable training schedule between club/school coaches and the athlete will allow the athlete to perform on multiple fronts while also being able to meet the demands of additional stressors such as schoolwork.


Subject(s)
Team Sports , Youth Sports , Adolescent , Athletes , Humans , Physical Exertion , Surveys and Questionnaires
14.
Sports (Basel) ; 8(9)2020 Sep 18.
Article in English | MEDLINE | ID: mdl-32961849

ABSTRACT

A plethora of research exists examining the physical qualities of rugby league players. However, no research has investigated practitioners' insights into the use, analysis and perceptions of such fitness testing data that is vital for applying research into practice. Therefore, this study aimed to examine practitioners' (coaches and strength & conditioning [S&C] coaches) perceptions and challenges of using fitness testing and the development of physical qualities. Twenty-four rugby league practitioners were purposefully sampled and completed a semi-structured interview. Interviews were transcribed and thematically analysed identifying five themes (it's important, but it's not everything; monitoring; evaluation and decision making; motivation; and other external challenges). The theme of "it's important, but it's not everything" emerged as a fundamental issue with regard fitness testing and the use of such data and that physical data alone does not inform coaches decisions. There appears conflicts between coaches and S&C coaches' perceptions and use of fitness data, identifying complexities of supporting players in multidisciplinary teams. Collectively, the findings highlight the multifaceted nature of academy rugby league and suggest that practitioners should utilise fitness testing to inform player evaluations, positively influence training and assist with decision making. Moreover, practitioners should understand the combination of factors that influence fitness testing and work collaboratively to enhance talent development strategies.

15.
J Sports Sci ; 38(14): 1674-1681, 2020 Jul.
Article in English | MEDLINE | ID: mdl-32314673

ABSTRACT

This study examined the relative contribution of exercise duration and intensity to team-sport athlete's training load. Male, professional rugby league (n = 10) and union (n = 22) players were monitored over 6- and 52-week training periods, respectively. Whole-session (load) and per-minute (intensity) metrics were monitored (league: session rating of perceived exertion training load [sRPE-TL], individualised training impulse, total distance, BodyLoad™; union: sRPE-TL, total distance, high-speed running distance, PlayerLoad™). Separate principal component analyses were conducted on the load and intensity measures to consolidate raw data into principal components (PC, k = 4). The first load PC captured 70% and 74% of the total variance in the rugby league and rugby union datasets, respectively. Multiple linear regression subsequently revealed that session duration explained 73% and 57% of the variance in first load PC, respectively, while the four intensity PCs explained an additional 24% and 34%, respectively. Across two professional rugby training programmes, the majority of the variability in training load measures was explained by session duration (~60-70%), while a smaller proportion was explained by session intensity (~30%). When modelling the training load, training intensity and duration should be disaggregated to better account for their between-session variability.


Subject(s)
Football/physiology , Physical Conditioning, Human/methods , Adult , Humans , Linear Models , Male , Perception/physiology , Physical Exertion/physiology , Principal Component Analysis , Running/physiology , Time Factors
16.
J Sports Sci ; 38(10): 1124-1131, 2020 May.
Article in English | MEDLINE | ID: mdl-32228154

ABSTRACT

Identifying the external training load variables which influence subjective internal response will help reduce the mismatch between coach-intended and athlete-perceived training intensity. Therefore, this study aimed to reduce external training load measures into distinct principal components (PCs), plot internal training response (quantified via session Rating of Perceived Exertion [sRPE]) against the identified PCs and investigate how the prescription of PCs influences subjective internal training response. Twenty-nine school to international level youth athletes wore microtechnology units for field-based training sessions. SRPE was collected post-session and assigned to the microtechnology unit data for the corresponding training session. 198 rugby union, 145 field hockey and 142 soccer observations were analysed. The external training variables were reduced to two PCs for each sport cumulatively explaining 91%, 96% and 91% of sRPE variance in rugby union, field hockey and soccer, respectively. However, when internal response was plotted against the PCs, the lack of separation between low-, moderate- and high-intensity training sessions precluded further analysis as the prescription of the PCs do not appear to distinguish subjective session intensity. A coach may therefore wish to consider the multitude of physiological, psychological and environmental factors which influence sRPE alongside external training load prescription.


Subject(s)
Perception/physiology , Physical Conditioning, Human/psychology , Physical Exertion/physiology , Youth Sports/psychology , Adolescent , Female , Fitness Trackers , Football/psychology , Hockey/psychology , Humans , Longitudinal Studies , Male , Physical Conditioning, Human/physiology , Principal Component Analysis , Prospective Studies , Soccer/psychology , Youth Sports/physiology
17.
J Strength Cond Res ; 34(9): 2636-2643, 2020 Sep.
Article in English | MEDLINE | ID: mdl-30358700

ABSTRACT

Emmonds, S, Sawczuk, T, Scantlebury, S, Till, K, and Jones, B. Seasonal changes in the physical performance of elite youth female soccer players. J Strength Cond Res 34(9): 2636-2643, 2020-This study investigated the seasonal change in physical performance of 113 (Under 10: U10 [n = 20], U12 [n = 30], U14 [n = 31], and U16 [n = 32]) elite youth female soccer players. Players completed testing pre-, mid-, and post-season, including speed (10- and 30-m sprint), change of direction (CoD; 505 test), power (countermovement jump [CMJ]), strength (isometric midthigh pull), and aerobic capacity (Yo-Yo intermittent recovery test level 1 [YYIRL1]). A general linear model was used to evaluate the change in physical characteristics and the influence of covariates (baseline performance; change in maturity status) on each characteristic across the season. U10's speed and CoD performance decreased from pre-post season, whereas relative strength likely improved. U12's relative strength very likely improved; however, 10-m sprint performance decreased. Relative strength likely decreased, whereas 30-m sprint and CoD time very likely improved in U14's. U16's likely improved relative strength, CMJ, and 10-m sprint, and very likely improved 30-m sprint and CoD from pre-post season. U12-U16's improved YYIRL1 performance pre-post season. Strength and conditioning coaches working with U10-U12 players should look to develop speed, lower-body power, and CoD ability as part of structured strength and conditioning sessions as well as within warm-ups before pitch-based sessions. With U14-U16 players' manipulation of small-sided games combined with short-duration high-intensity running drills may provide an efficient training stimulus to develop the aerobic system while concurrently developing technical/tactical skills. Findings of this study provide a basis for the implementation of strategies to enhance the long-term athletic development of youth female soccer players.


Subject(s)
Athletic Performance/physiology , Soccer/physiology , Adolescent , Child , Female , Humans , Muscle Strength/physiology , Muscle, Skeletal/physiology , Running/physiology , Seasons , Time Factors
18.
J Strength Cond Res ; 34(8): 2321-2328, 2020 Aug.
Article in English | MEDLINE | ID: mdl-30199446

ABSTRACT

Emmonds, S, Scantlebury, S, Murray, E, Turner, L, Robsinon, C, and Jones, B. Physical characteristics of elite youth female soccer players characterized by maturity status. J Strength Cond Res 34(8): 2321-2328, 2020-The purpose of this study was to investigate the influence of maturity status on the physical characteristics of youth female soccer players. One hundred fifty-seven players from 3 elite soccer academies in England completed assessments of anthropometry, strength (isometric midthigh pull), lower-body power (countermovement jump [CMJ]), aerobic capacity (Yo-Yo intermittent recovery test level 1), change of direction (CoD: 505-left/right), and speed (10 and 30 m). Each player was classified into 1 of 6 maturity groups based on their estimated years from peak height velocity (YPHV). Magnitude-based inferences were used to assess for the practical significance between consecutive groups. Speed, CoD time, CMJ, and aerobic capacity were all possibly most likely better in more mature players. However, there was a likely difference in relative peak force between maturity groups -0.5 YPHV (27.13 ± 4.24 N·Kg) and 0.5 YPHV (24.62 ± 3.70 N·Kg), which was associated with a likely difference in 10-m sprint time (-0.5 YPHV: 2.00 ± 0.12 vs. 0.5 YPHV 2.08 ± 0.16 seconds) and unclear changes in CMJ and CoD time. Findings provide novel comparative data for this cohort relative to maturity status and can be used by strength and conditioning coaches to inform the design of training programs for youth female soccer players. Strength and conditioning coaches should be aware that youth female soccer players may experience a decrease in relative strength around peak height velocity, which may impact upon the speed, CoD time, and CMJ of players.


Subject(s)
Adolescent Development/physiology , Athletic Performance/physiology , Child Development/physiology , Muscle Strength/physiology , Soccer/physiology , Adolescent , Anthropometry , Child , Cross-Sectional Studies , England , Exercise Tolerance/physiology , Female , Humans , Male , Muscle, Skeletal/physiology , Running
19.
J Strength Cond Res ; 32(7): 1975-1980, 2018 Jul.
Article in English | MEDLINE | ID: mdl-29939948

ABSTRACT

Scantlebury, S, Till, K, Sawczuk, T, Phibbs, P, and Jones, B. Validity of retrospective session rating of perceived exertion to quantify training load in youth athletes. J Strength Cond Res 32(7): 1975-1980, 2018-Youth athletes frequently participate in multiple sports or for multiple teams within the same sport. To optimize player development and minimize undesirable training outcomes (e.g., overuse injuries), practitioners must be cognizant of an athlete's training load within and outside their practice. This study aimed to establish the validity of a 24-hour (s-RPE24) and 72-hour (s-RPE72) recall of session rating of perceived exertion (s-RPE) against the criterion measure of s-RPE collected 30 minutes' post training (s-RPE30). Thirty-eight adolescent athletes provided a s-RPE30 following the first field based training session of the week. Approximately 24 hours later subjects were asked to recall the intensity and duration of the previous days training. The following week subjects once again provided an s-RPE30 measure after training before recalling the intensity and duration of the session approximately 72 hours later. A nearly perfect correlation (0.98 [0.97-0.99]) was found between s-RPE30 and s-RPE24, with a small typical error of estimate (TEE; 8.3% [6.9-10.5]) and trivial mean bias (-1.1% [-2.8 to 0.6]). Despite a large correlation between s-RPE30 and s-RPE72 (0.73 [0.59-0.82]) and a trivial mean bias (-0.2% [-6.8 to 6.8]), there was a large TEE (35.3% [29.6-43.9]). s-RPE24 provides a valid measure of retrospectively quantifying s-RPE; however, the large error associated with s-RPE72 suggests that it is not a suitable method for monitoring training load in youth athletes.


Subject(s)
Athletes/psychology , Exercise/physiology , Mental Recall , Physical Exertion/physiology , Adolescent , Humans , Perception , Retrospective Studies
20.
J Sports Sci ; 36(21): 2431-2437, 2018 Nov.
Article in English | MEDLINE | ID: mdl-29620966

ABSTRACT

This study assessed the influence of training load, exposure to match play and sleep duration on two daily wellbeing measures in youth athletes. Forty-eight youth athletes (age 17.3 ± 0.5 years) completed a daily wellbeing questionnaire (DWB), the Perceived Recovery Status scale (PRS), and provided details on the previous day's training loads (TL) and self-reported sleep duration (sleep) every day for 13 weeks (n = 2727). Linear mixed models assessed the effect of TL, exposure to match play and sleep on DWB and PRS. An increase in TL had a most likely small effect on muscle soreness (d = -0.43;± 0.10) and PRS (d = -0.37;± 0.09). Match play had a likely small additive effect on muscle soreness (d = -0.26;± 0.09) and PRS (d = -0.25;± 0.08). An increase in sleep had a most likely moderate effect on sleep quality (d = 0.80;± 0.14); a most likely small effect on DWB (d = 0.45;± 0.09) and fatigue (d = 0.42;± 0.11); and a likely small effect on PRS (d = 0.25;± 0.09). All other effects were trivial or did not reach the pre-determined threshold for practical significance. The influence of sleep on multiple DWB subscales and the PRS suggests that practitioners should consider the recovery of an athlete alongside the training stress imposed when considering deviations in wellbeing measures.


Subject(s)
Competitive Behavior/physiology , Physical Conditioning, Human , Sleep/physiology , Soccer/physiology , Soccer/psychology , Adolescent , Affect , Fatigue/etiology , Female , Humans , Male , Myalgia/etiology , Perception , Physical Conditioning, Human/adverse effects , Stress, Psychological , Surveys and Questionnaires , Time Factors
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