Qualities or skills discriminating under 19 rugby players by playing standards: a comparative analysis of elite, sub-elite and non-rugby players using the SCRuM test battery

What Tests are Used to Assess the Physical Qualities of Male, Adolescent Rugby League Players? A Systematic Review of Testing Protocols and Reported Data Across Adolescent Age Groups

BACKGROUND

Understanding the physical qualities of male, adolescent rugby league players across age groups is essential for practitioners to manage long-term player development. However, there are many testing options available to assess these qualities, and differences in tests and testing protocols can profoundly influence the data obtained.

OBJECTIVES

The aims of this systematic review were to: (1) identify the most frequently used tests to assess key physical qualities in male, adolescent rugby league players (12-19 years of age); (2) examine the testing protocols adopted in studies using these tests; and (3) synthesise the available data from studies using the most frequently used tests according to age group.

METHODS

A systematic search of five databases was conducted. For inclusion, studies were required to: (1) be original research that contained original data published in a peer-reviewed journal; (2) report data specifically for male, adolescent rugby league players; (3) report the age for the recruited participants to be between 12 and 19 years; (4) report data for any anthropometric quality and one other physical quality and identify the test(s) used to assess these qualities; and (5) be published in English with full-text availability. Weighted means and standard deviations were calculated for each physical quality for each age group arranged in 1-year intervals (i.e., 12, 13, 14, 15, 16, 17 and 18 years) across studies.

RESULTS

37 studies were included in this systematic review. The most frequently used tests to assess anthropometric qualities were body mass, standing height, and sum of four skinfold sites. The most frequently used tests to assess other physical qualities were the 10-m sprint (linear speed), 505 Agility Test (change-of-direction speed), Multistage Fitness Test (aerobic capacity), bench press and back squat one-repetition maximum tests (muscular strength), and medicine ball throw (muscular power). Weighted means calculated across studies generally demonstrated improvements in player qualities across subsequent age groups, except for skinfold thickness and aerobic capacity. However, weighted means could not be calculated for the countermovement jump.

CONCLUSION

Our review identifies the most frequently used tests, but highlights variability in the testing protocols adopted. If these tests are used in future practice, we provide recommended protocols in accordance with industry standards for most tests. Finally, we provide age-specific references for frequently used tests that were implemented with consistent protocols. Clinical Trial Registration This study was conducted in accordance with the Preferred Reporting Items of Systematic Review and Meta-analysis guidelines and was registered with PROSPERO (ID: CRD42021267795).

The Effects of Strength and Conditioning Interventions on Sprinting Performance in Team Sport Athletes: A Systematic Review and Meta-Analysis

Murphy, A, Burgess, K, Hall, AJ, Aspe, RR, and Swinton, PA. The effects of strength and conditioning interventions on sprinting performance in team sport athletes: a systematic review and meta-analysis. J Strength Cond Res 37(8): 1692–1702, 2023—Linear sprinting is a key determinant of athletic performance within team sports. The aims of the review were to quantify and compare the effectiveness of popular strength and conditioning (S&C) training modes to improve sprint performance in team sport athletes, with additional focus on potential moderators and the relationships between improvements in physical factors (e.g., strength, power, and jump performance) and improvements in sprint performance. Inclusion was restricted to resistance, plyometric, sprint, and combined training interventions comprising team sport athletes. Multilevel, Bayesian’s meta-analysis and meta-regression models conducted with standardized mean difference effect sizes were used to investigate training modes and potential moderators. Weighted regression models conducted on shrunken estimates from initial Bayesian’s meta-analyses were used to quantify relationships between improvements in physical factors and sprint performance. Certainty of evidence was assessed using the grading of recommendations assessment development and evaluation (GRADE) approach. Similar improvements in sprint performance were obtained across training modes, with some evidence of the largest effects with resistance training ( = 0.55 [95% credible interval [CrI]: 0.36–0.78; very low certainty]). A strong moderating effect of training intensity was identified across all training modes with evidence of greater improvements in sprint performance with high-intensity training ( = 0.17 [95% CrI: 0.01–0.33; very low certainty]). Strong positive relationships were identified between improvements in all physical factors and sprint performance ( = 0.56 [95% CrI: 0.36–0.77; low certainty], = 0.80 [95% CrI: 0.50–1.0; low certainty], = 0.78 [95% CrI: 0.57–0.97; low certainty]). The findings indicate that focus on developing speed in team sport athletes should be placed on S&C training with high intensities, including the use of resisted sprint training.

Psychosocial and Physiological Factors Affecting Selection to Regional Age-Grade Rugby Union Squads: A Machine Learning Approach

Talent selection programmes choose athletes for talent development pathways. Currently, the set of psychosocial variables that determine talent selection in youth Rugby Union are unknown, with the literature almost exclusively focusing on physiological variables. The purpose of this study was to use a novel machine learning approach to identify the physiological and psychosocial models that predict selection to a regional age-grade rugby union team. Age-grade club rugby players (n = 104; age, 15.47 ± 0.80; U16, n = 62; U18, n = 42) were assessed for physiological and psychosocial factors during regional talent selection days. Predictive models (selected vs. non-selected) were created for forwards, backs, and across all players using Bayesian machine learning. The generated physiological models correctly classified 67.55% of all players, 70.09% of forwards, and 62.50% of backs. Greater hand-grip strength, faster 10 m and 40 m sprint, and power were common features for selection. The generated psychosocial models correctly classified 62.26% of all players, 73.66% of forwards, and 60.42% of backs. Reduced burnout, reduced emotional exhaustion, and lower reduced sense of accomplishment, were common features for selection. Selection appears to be predominantly based on greater strength, speed, and power, as well as lower athlete burnout.

Talent Identification in an English Premiership Rugby Union Academy: Multidisciplinary Characteristics of Selected and Non-selected Male Under-15 Players

Entry into an academy can be a defining moment for a promising young player. The aim of this study was to explore the multidimensional characteristics that differentiated selected and non-selected male under-15 rugby union players at an English Premiership academy. Seventy-four players (mean age 14.6 ± 0.3 years: selected n = 29; non-selected n = 45) were measured across nine characteristics from four overarching factors: (a) anthropometric (n = 2), (b) physiological (n = 5), (c) cognitive (n = 1), and (d) birth quartile. An ANOVA compared differences between groups (selected vs. non-selected), whilst a Welch's t-test and Cohen's d were used for further comparisons. A multivariate logistic regression was also used to predict selection. Results showed significant differences between selected and non-selected players for anthropometric (P = 0.021) and physiological factors (P < 0.001). Moreover, relatively older players were overrepresented with 65% born in the first half of the year, whereas no significant differences were apparent for the cognitive test. More specifically, selected players possessed greater body mass (P = 0.022, d = 0.5) and handgrip strength (P = 0.020, d = 0.5) compared to non-selected players, whilst multivariate analysis showed the 20 m sprint explained 25.4% of the variance (P = 0.001). Overall, it appears selection into an English Premiership rugby union academy may be due to enhanced physical attributes rather than cognitive abilities.

Strength and Power Characteristics in National Amateur Rugby Players

Rugby players need muscular strength and power to meet the demands of the sport; therefore, a proper assessment of the performance in rugby players should include both variables. The purpose of this study was to examine the strength and power characteristics (SPC) during the squat (SQ) and bench press (BP) in national amateur rugby players and to analyze gender- and position-related differences. A total of 47 players (30 males and 17 females; age: 25.56 ± 1.14 and 23.16 ± 1.38 years, respectively) participated in the study. The one repetition-maximum (1-RM) and SPC in SQ and BP were obtained using a Smith Machine. Then, subjects performed one set of five repetitions on the SQ and BP against six relative loads (30-40-50-60-70-80% 1-RM) using a linear transducer. Differences between genders were found in 1-RM for maximal power, kilograms lifted at maximal power, maximal power, maximal strength and maximal speed in BP (p < 0.00) and 1-RM, kilograms lifted at maximal power, maximal power, maximal strength and maximal speed in SQ (p < 0.00). Comparisons between variables in SQ and BP present a significant relationship (p < 0.01) in SQ and BP 1-RM with kilograms lifted at maximal power (r = 0.86 and r = 0.84), maximal strength (r = 0.53 and r = 0.92) and maximal power (r = 0.76 and r = 0.93). This study confirms the importance of the SPC assessment for training prescription in rugby amateur players.

Testing methods and physical qualities of male age grade rugby union players: A systematic review

BACKGROUND

Rugby union match demands are complex, requiring the development of multiple physical qualities concurrently. Quantifying the physical qualities of age grade rugby union players is vital for practitioners to support athlete preparation and long-term development.

AIM

This systematic review aimed to identify the methods used to quantify the physical qualities of male age grade (≤ Under-20) rugby union players, present the normative values for physical qualities, and compare physical qualities between age grades and positions.

METHODS

Electronic databases were systematically reviewed from the earliest record to November 2019 using key words relating to sex, age, sport and physical testing.

RESULTS

Forty-two studies evaluated the physical qualities of age grade rugby union players. Seventy-five tests were used to quantify body composition, muscular strength, muscular power, linear speed, change of direction ability, aerobic capacity and anaerobic endurance. Thirty-one studies met the eligibility criteria to present the physical qualities. Physical qualities differentiate between age groups below Under-16, while differences in older age groups (Under-16 to Under-20) are not clear. Positional differences are present with forwards possessing greater height, body mass, body fat percentage and strength while backs are faster and have greater aerobic capacities.

CONCLUSIONS

A wide variety of tests are used to assess physical qualities limiting between study comparisons. Although differences in older age grades are unclear, older age groups (Under-19-20) generally performed better in physical tests. Positional differences are associated with match demands where forwards are exposed to less running but a greater number of collisions. Practitioners can use the results from this review to evaluate the physical qualities of age grade rugby union players to enhance training prescription, goal setting and player development. Future research should consider the use of national standardised testing batteries due to the inconsistency in testing methods and small samples limiting the reporting of positional differences.

Anthropometric, physiological characteristics and rugby-specific game skills of schoolboy players of different age categories and playing standards

Background

Rugby is increasingly gaining popularity among school-aged male junior players in countries hardly known for dominating international rugby, such as Zimbabwe. Given rugby combativeness, participating adolescents should possess qualities or skills commensurate with the physical demands of the sport for effective participation. This study investigated the independent and interactive effects of age category and playing standard on anthropometric, physiological characteristics and rugby-specific game skills among Zimbabwean athletes.

Methods

Two hundred and eight elite, sub-elite and non-rugby players competing at Under 16 and Under 19 age categories were assessed using the School Clinical Rugby Measure (SCRuM) test battery. Participants underwent height, sitting height, mass, skinfolds, speed, agility, upper-and-lower muscular strength and power, prolonged high-intensity intermittent running ability, tackling, passing and catching assessments in a cross-sectional experimental design.

Results

Age categories had significant main effect on all SCRuM test items except sum of seven skinfolds (p = 0.45, η²p = 0.003). Playing standard had significant main effects for all variables except height (p = 0.40, η²p = 0.01) and sum of seven skinfolds (p = 0.11, η²p = 0.02). Specifically, upper-and-lower muscular strength and power, prolonged high-intensity intermittent running ability, tackling, passing and catching improved with increasing playing standards. However, two-way analysis of variance only demonstrated significant interactions between the effects of age category and playing standards for vertical jump height (VJ) test, 2-kg medicine ball chest throw (2-kg MBCT) test, Yo-Yo intermittent recovery test level 1 (Yo-Yo IRT L1), and tackling and catching tests. Yo-Yo IRT L1, VJ, tackling and catching tests demonstrated greater discriminative ability among Under 16 s, whereas the 2-kg MBCT test showed better ability in Under 19 s.

Conclusion

All SCRuM variables except skinfolds improved with age, highlighting relative sensitivity in differentiating older from younger athletes. However, the discriminative ability by playing standards for VJ, 2-kg MBCT, Yo-Yo IRT L1, tackling and catching ability tests was age-dependent. These findings informs on general attribute development in junior rugby players with age and on specific players attributes in need of monitoring for attainment of elite status at U16 or U19 level.