Assessing pre-season workload variation in professional rugby union players by comparing three acute:Chronic workload ratio models based on playing positions

Quantifying the pre-season workload of professional Rugby Union players, in relation to their respective positions not only provides crucial insights into their physical demands and training needs but also underscores the significance of the acute:chronic workload ratio (ACWR) in assessing workload. However, given the diversity in ACWR calculation methods, their applicability requires further exploration. As a result, this study aims to analyze the workload depending on the player's positions and to compare three ACWR calculation methods. Fifty-seven players were categorized into five groups based on their playing positions: tight five (T5), third-row (3R), number nine (N9), center, and third line defense (3L). The coupled and uncoupled rolling averages (RA), as well as the exponentially weighted moving average ACWR method, were employed to compute measures derived from GPS data. Changes throughout the pre-season were assessed using the one-way and two-way analysis of variance. The results revealed that N9 covered significantly greater distances and exhibited higher player load compared to T5 and 3L [p < 0.05, effect size (ES) = 0.16-0.68]. Additionally, 3L players displayed the highest workload across various measures, including counts of accelerations and decelerations (>2.5 m s-2), accelerations (>2.5 m s-2), acceleration distance (>2 m s-2), high-speed running (>15 km h-1), very high-speed running (>21 km h-1, VSHR), sprint running (>25 km h-1, SR) distance. When using coupled RA ACWR method, centers exposed significantly greater values to T5 (p < 0.05, ES = 0.8) and 3R (p < 0.05, ES = 0.83). Moreover, centers exhibited greater (p < 0.05, ES = 0.67-0.91) uncoupled RA ACWR values for VHSR and SR than T5 and 3R. When comparing the three ACWR methods, although significant differences emerged in some specific cases, the ES were all small (0-0.56). In light of these findings, training should be customized to the characteristics of players in different playing positions and the three ACWR calculation methods can be considered as equally effective approaches.

Preseason and In-Season High-Speed Running Demands of 2 Professional Australian Rules Football Teams

BACKGROUND

Australian Rules Football athletes complete long preseasons, yet injuries occur frequently at early stages of the competitive season. Little is known about the high-speed running (HSR) prescription during a preseason or whether players are adequately prepared for competition. This study described absolute and relative preseason and in-season HSR demands of 2 professional Australian football teams.

HYPOTHESIS

HSR and sprinting volumes are significantly lower in elite Australian Rules football athletes during in-season compared with preseason.

STUDY DESIGN

Cohort study.

LEVEL OF EVIDENCE

Level 3.

METHODS

During the 2019 season, HSR volume was collected for 2 professional Australian football teams (n = 55). Individual maximum speeds (Vmax) were captured to calculate relative running speed thresholds, as reported in 5% increments from 70%Vmax to 100%Vmax.

RESULTS

Weekly volume of running above 70%Vmax (P = 0.01; r = 0.56) and 80%Vmax (P = 0.01; r = 0.58) was significantly greater in the preseason than the in-season. The weekly volume completed above 90%Vmax was not significantly greater in the preseason than the in-season (P = 0.10; r = 0.22). Individual variation in the distance completed at specific percentages of Vmax expressed as a coefficient of variation was reported as 51% at 71% to 80%Vmax, 39% at 81% to 90%Vmax, and 41% at 91% to 100%Vmax.

CONCLUSION

The volume of HSR completed by athletes is far greater in the initial 4 weeks of the preseason than in any other point in preseason or competitive phases. At the individual level, there is substantial variation in the distance covered. This supports the concept of a heavily individualized approach to high-speed prescription and monitoring.

CLINICAL RELEVANCE

Practitioners should carefully consider individual variation regarding sprinting volume during both preseason and in-season when prescribing and monitoring training to improve on-field performance and reduce the risk of injury.

Optimization of training for professional rugby union players: investigating the impact of different small-sided games models on GPS-derived performance metrics

Introduction: Professional rugby union players can improve their performance by engaging in small-sided games (SSGs), which simulate the movement patterns of the game. This study collected metrics related to running performance and mechanical workload and their relative values from both forward and back positions, aiming to explore the impact of different SSGs factors on athlete workload, as well as the workload difference between official games (OGs) and SSGs. Methods: The monitored GPS data were collected from SSGs with different player numbers and pitch sizes (five sessions), SSG rules (5 weeks, four sessions per week), and OGs conducted throughout the year. Additionally, the study compared changes in players' sprinting performance before and after two SSG sessions. Results: Backs had greater workload than forwards. Less space and number of players SSG (4 vs. 4, 660 m2) was conducive to facilitating training for players in acceleration and deceleration. Conversely, larger spaces were associated with improved running performance. However, the introduction of a floater had no significant impact on performance improvement. Additionally, the 7 vs. 4 model (seven players engaged with four opponents) resulted in the greatest workload during medium-hard accelerations (F = 52.76-88.23, p < 0.001, ηp 2 = 0.19-0.28). Japan touch model allowed for more high-speed running training (F = 47.93-243.55, p < 0.001, ηp 2 = 1.52). The workload performed by SSGs can almost cover that of OGs (F = 23.36-454.21, p < 0.05, ηp 2 = 0.03-0.57). In the context of ηp 2, values around 0.01, 0.06 and 0.14 indicate small, medium and large effects respectively. Discussion: However, given the significantly higher workload of SSGs and the slight decrease in sprinting performance, further research is required to examine the training patterns of SSGs. This study provided insight into the impact of player numbers, pitch size, and rules on rugby-specific SSGs. Coaches should optimize SSG setups for enhanced training outcomes, ensuring the long-term development of physical capacity, technical and tactical skills.

Changing gears: data-driven velocity zones to support monitoring and research in men's rugby league

OBJECTIVES

The study aimed to (1) apply a data-mining approach to league-wide microtechnology data to identify absolute velocity zone thresholds and (2) apply the respective velocity zones to microtechnology data to examine the locomotor demands of elite match-play.

METHODS

League-wide microtechnology data were collected from elite male rugby league players representing all National Rugby League (NRL) teams (n = 16 teams, one excluded due to a different microtechnology device; n = 4836 files) over one season. To identify four velocity zones, spectral clustering with a beta smoothing cut-off of 0.1 was applied to each players' instantaneous match-play velocity data. Velocity zones for each player were calculated as the median while the overarching velocity zones were determined through an incremental search to minimise root mean square error.

RESULTS

The velocity zones identified through spectral clustering were 0-13.99 km · h-1 (i.e., low velocity), 14.00-20.99 km · h-1 (i.e., moderate velocity), 21.00-24.49 km · h-1 (i.e., high velocity) and >24.50 km · h-1 (i.e., very-high velocity).

CONCLUSIONS

The application of spectral clustering (i.e., a data-mining method) to league-wide rugby league microtechnology data yielded insights into the distribution of velocity data, thereby informing the cut-off values which best place similar data points into the same velocity zones. As the identified zones are representative of the intensities of locomotion achieved by elite male rugby league players, it is suggested that when absolute zones are used, the consistent application of the identified zones would facilitate standardisation, longitudinal athlete monitoring as well as comparisons between teams, leagues and published literature.

Effect of Neuromuscular Fatigue on the Countermovement Jump Characteristics: Basketball-Related High-Intensity Exercises

ABSTRACT

Yoshida, N, Hornsby, WG, Sole, CJ, Sato, K, and Stone, MH. Effect of neuromuscular fatigue on the countermovement jump characteristics: basketball related high-intensity exercises. J Strength Cond Res 38(1): 164-173, 2024-The purpose of this study was to investigate basketball specific neuromuscular (NM) fatigue effect on countermovement jump (CMJ) force-time (F-T) curve characteristics. Eleven male college-level basketball athletes performed 6 CMJ trials at 3 baseline (pre) and 6 postexercise time points. The fatiguing protocol consisted of high-intensity basketball related exercises commensurate with basketball game or practice. Typical CMJ (CMJ-TYP) and phase-specific CMJ variables were derived from the F-T curve. Meaningful differences in CMJ performance were examined using effect size (ES) compared with baseline and previous postexercise time point. Baseline with 3 separated measurements demonstrated suitable CMJ variables reproducibility (CV, coefficient of variation). Most CMJ-TYP output and performance variables displayed substantial alterations immediately postexercise (0 hour) and returned to baseline at 24 hours postexercise, whereas the time and rate-related CMJ-TYP and CMJ-phase variables tended to display delayed decline peaked at 2 hours and delayed recovery to baseline at 48 hours postexercise. In conjunction with the return of the time and rate-related variables, CMJ performance displayed supercompensation at 72 hours postexercise. The results indicate altered NM functions with desired CMJ performance, such as jump height, which imply an altered movement strategy at early stage of recovery process. Full recovery may take 48-72 hours. Practitioners are, therefore, advised to monitor variables reflecting NM functions for precise manipulation of the intensity and volume of exercise to avoid prolonging the recovery from NM fatigue.

The 50 Most Cited Papers on Rugby since 2000 Reveal a Focus Primarily on Strength and Conditioning in Elite Male Players

We sought to conduct a bibliometric analysis and review of the most cited publications relating to rugby since 2000 in order to identify topics of interest and those that warrant further investigations. Clarivate Web of Science database was used to perform a literature search using the search term "rugby." The top 200 papers by citation count were extracted and reviewed for the inclusion criteria: all subjects were rugby players. The top 50 manuscripts were included for analysis of author, publication year, country of lead authors, institution, journal name and impact factor, topic, participant sex, and level of rugby. The total number of citations was 9,071 (average of 181.4 citations/article), with an average journal impact factor of 7.21; the top article was cited 407 times at the time of analysis. The most frequent publication was the Journal of Strength and Conditioning Research (26%), followed by the British Journal of Sports Medicine (20%) and the Journal of Sports Sciences (18%). Forty-eight (96%) of the manuscripts contained only male subjects, with 1 manuscript including females only and 1 manuscript containing mixed sexes. Thirty-three (66%) of the manuscripts focused on professional rugby players, with the next highest player group being mixed levels (10%). Twenty-eight (56%) concentrated on topics regarding strength and conditioning, 11 (22%) on injury, and 4 (8%) on physiology. Despite rugby being one of the most injurious sports and community players representing the largest component of the player pool, most of the top-cited rugby articles are cohort studies of professional male athletes focused on performance and strength and conditioning, noting the bias in research towards socially relevant topics that may not impact the majority of stakeholders and long-term health of rugby athletes. These findings highlight the need for further research among women and community athletes and on topics in injury prevention.

Does External Load Reflect Acute Neuromuscular Fatigue and Rating of Perceived Exertion in Elite Young Soccer Players?

ABSTRACT

Martínez-Serrano, A, Freitas, TT, Franquesa, X, Enrich, E, Mallol, M, and Alcaraz, PE. Does external load reflect acute neuromuscular fatigue and rating of perceived exertion in elite young soccer players? J Strength Cond Res 37(3): e1-e7, 2023-This study aimed to analyze the acute and residual effects of increased high-speed running (HSR) demands during an in-season training microcycle in young elite soccer players on localized neuromuscular fatigue (NMF) of the knee extensors (KE), posterior chain muscles, and rating of perceived exertion (RPE). Thirty-four elite young soccer players (age = 17.1 ± 0.8 years) were assessed in 2 consecutive days at different time points (baseline, POST-activation gym-based session, POST-small-sided game [SSG], POST-training 1 [TR1], POST-6H, POST-24H, POST-preventive gym-based session, and POST-training 2 [TR2]). Neuromuscular fatigue of the KE and posterior chain muscles was measured with a maximum voluntary isometric contraction (MVIC). External (total distance, number of accelerations or decelerations, and HSR distance) and internal (RPE) load was assessed during the SSG, TR1, and TR2 sessions. Players were divided through a median split, into "HIGH" or "LOW" group according to the training demands. The alpha level was set at p ≤ 0.05. A 2-way mixed effects model ANOVA showed a significant decreased in 90:20 MVIC after TR1 in the "HIGH" HSR group ( p = 0.037; effect size [ES] = 0.45). No significant differences in RPE were found after TR1 ( p = 0.637; ES = 0.58) and TR2 ( p = 0.109; ES = 0.62) when comparing the "HIGH" HSR group with the "LOW" HSR group. Assessing player's force production capabilities can be an effective strategy to detect NMF when HSR demands are acutely increased. Special caution should be taken when prescribing the training load of the training session based solely on RPE, as NMF might be present.

Moving beyond velocity derivatives; using global positioning system data to extract sequential movement patterns at different levels of rugby league match-play

This study aims to (a) quantify the movement patterns during rugby league match-play and (b) identify if differences exist by levels of competition within the movement patterns and units through the sequential movement pattern (SMP) algorithm. Global Positioning System data were analysed from three competition levels; four Super League regular (regular-SL), three Super League (semi-)Finals (final-SL) and four international rugby league (international) matches. The SMP framework extracted movement pattern data for each athlete within the dataset. Between competition levels, differences were analysed using linear discriminant analysis (LDA). Movement patterns were decomposed into their composite movement units; then Kruskal-Wallis rank-sum and Dunn post-hoc were used to show differences. The SMP algorithm found 121 movement patterns comprised mainly of "walk" and "jog" based movement units. The LDA had an accuracy score of 0.81, showing good separation between competition levels. Linear discriminant 1 and 2 explained 86% and 14% of the variance. The Kruskal-Wallis found differences between competition levels for 9 of 17 movement units. Differences were primarily present between regular-SL and international with other combinations showing less differences. Movement units which showed significant differences between competition levels were mainly composed of low velocities with mixed acceleration and turning angles. The SMP algorithm found 121 movement patterns across all levels of rugby league match-play, of which, 9 were found to show significant differences between competition levels. Of these nine, all showed significant differences present between international and domestic, whereas only four found differences present within the domestic levels. This study shows the SMP algorithm can be used to differentiate between levels of rugby league and that higher levels of competition may have greater velocity demands.Highlights This study shows that movement patterns and movement units can be used to investigate team sports through the application of the SMP frameworkOne hundred and twenty-one movement patterns were found to be present within rugby league match-play, with the walk- and jog-based movement units most prevalent. No movement pattern was unique to a single competition level.Further analysis revealed that the majority of movement units analysed had significant differences between international and domestic rugby league, whereas only four movement units (i.e. f,m,n,q) had significant differences within the two domestic rugby league levels.International rugby league had higher occurrences of the movement patterns consisting of higher velocity movement units (ie. T,S,y). This suggests that international rugby league players may need greater high velocity exposure in training.

The introduction of the six-again rule has increased acceleration intensity across all positions in the National Rugby League competition

The impact of the six-again rule change on the movement of National Rugby League (NRL) athletes was examined. Player Global Navigation Satellite System (GNSS) data (10 Hz) was collected from 42 athletes who competed in 56 matches across the 2019 to 2021 NRL seasons. Maximal mean speed (m·min^-1) and acceleration (m·s^-2) were established across a 10 s to 10-min duration via raw GNSS files, with subsequent intercept (mean estimates) and slope values determined via power law analysis. The distributions of match distance (m) and impulse (kN·s^-1) were established during ball-in-play time. To determine the significance between positions and seasons under different rules, linear mixed models were used. Effects were described using standardised effect sizes (ES) with 90% confidence limits (CL). Acceleration intercepts (power law-derived) across all positions were substantially greater (>0.6 SD) following the introduction of the six-again rule in the 2020 (mean ± SD; 1.02 ± 0.10 m·s^-2) and 2021 seasons (1.05 ± 0.08 m·s^-2) compared to the 2019 season (0.91 ± 0.07 m·s^-2). Mean acceleration during ball-in-play time was greater in 2020 (ES; 90% CL = 0.75; ± 0.32) compared to 2019. The acceleration requirements of rugby league increased across all positional groups following the modification in NRL competition rules. Practitioners should tailor training programs for athletes to reflect the increased acceleration intensity found under the revised competition format.

The field and resistance training loads of academy rugby league players during a pre-season: Comparisons across playing positions

Male academy rugby league players are required to undertake field and resistance training to develop the technical, tactical and physical qualities important for success in the sport. However, limited research is available exploring the training load of academy rugby league players. Therefore, the purpose of this study was to quantify the field and resistance training loads of academy rugby league players during a pre-season period and compare training loads between playing positions (i.e., forwards vs. backs). Field and resistance training load data from 28 adolescent male (age 17 ± 1 years) rugby league players were retrospectively analysed following a 13-week pre-season training period (85 total training observations; 45 field sessions and 40 resistance training sessions). Global positioning system microtechnology, and estimated repetition volume was used to quantify external training load, and session rating of perceived exertion (sRPE) was used to quantify internal training load. Positional differences (forwards n = 13 and backs n = 15) in training load were established using a linear mixed effect model. Mean weekly training frequency was 7 ± 2 with duration totaling 324 ± 137 minutes, and a mean sRPE of 1562 ± 678 arbitrary units (AU). Backs covered more high-speed distance than forwards in weeks two (p = 0.024), and 11 (p = 0.028). Compared to the forwards, backs completed more lower body resistance training volume in week one (p = 0.02), more upper body volume in week three (p< 0.001) and week 12 (p = 0.005). The findings provide novel data on the field and resistance-based training load undertaken by academy rugby league players across a pre-season period, highlighting relative uniformity between playing positions. Quantifying training load can support objective decision making for the prescription and manipulation of future training, ultimately aiming to maximise training within development pathways.

Changes in acceleration load as measured by inertial measurement units manifest in the upper body after an extended running task

The purpose of this study was to investigate the behaviour of physiological load measures as well as ground reaction forces (GRF) and acceleration load during a prolonged running task that simulated the running demands of an intermittent team sport. Nineteen males completed a maximal aerobic fitness test and an extended running protocol across two sessions. Participants wore a portable metabolic system, and four inertial measurement units (IMU), one on each foot, the lower back and upper back. GRF were measured via an instrumented treadmill. Change in metabolic, IMU and GRF variables across five blocks during the running protocol were assessed using a one-way repeated measures ANOVA. The running protocol elicited large increases in heart rate and oxygen consumption over time. No statistically significant changes in any peak impact accelerations were observed. Resultant acceleration area under the curve (AUC) increased at the lower and upper back locations but was unchanged at the foot. GRF active peak but not impact peak increased during the prolonged run. The results of this study indicate that the effect of an extended running task on IMU measures of external mechanical load is manifested in the upper body, and is effectively measured by AUC.

The Between-Competition Running Demands of Elite Hurling Match-Play

The current study aimed to investigate the differences in running demands between the National Hurling League (NHL) and the Championship, and within playing positions. GPS (10 Hz, STATSports Apex GNSS) were used to analyse the running demands during 34 games (2017–2020 seasons) of the Championship and the NHL. The running demands (total-, relative-, high-speed- [>17 km·h⁻¹] and sprint [≥22 km·h⁻¹] distance, number and length of sprints, and peak speed) were compared between competitions. Greater total- [ES = 0.32], relative- [ES = 0.26], and sprint-distance [ES = 0.41], and number of sprints [ES = 1.29] were completed in the Championship. The high-speed distance was similar between competitions. Half-backs and half-forwards covered greater total- (ES = 0.91 and 0.21, respectively), relative- (ES = 1.14 and 0.68, respectively), high-speed- (ES = 0.69 and 0.44, respectively), and sprint-distance (ES = 0.50 and 1.26, respectively), number of sprints (ES = 2.66 and 1.73, respectively), and peak speed (ES = 1.09 and 1.32, respectively) in the Championship. There was no difference (p < 0.05) in the sprint distance covered between positions in the Championship. The results showed that the Championship is more physically demanding. The findings present key implications for the transition between competitions.

Possible Association of Energy Availability with Transferrin Saturation and Serum Iron during Summer Camp in Male Collegiate Rugby Players

Low energy availability (LEA) may persist in rugby players. However, timely assessment of energy balance is important but is difficult. Therefore, a practical index that reflects energy availability (EA) is essential. A total of 19 male college rugby players participated in a 2-week pre-season summer camp. Their blood sample was collected after overnight fast prior to (Pre), in the middle (Middle), and after (Post) the camp. Their physical activity in the first half of the camp was calculated using the additive factor method in the forwards (FW; numbers 1–8) and backs (BK; numbers 9–15). The participants were categorized as tight five (T5; numbers 1–5), back row (BR; numbers 6–8), and BK for analysis. All the participants lost weight during the camp (range: from −5.9% to −0.1%). Energy balance in the first half of the camp was negative. Transferrin saturation (TSAT) and serum iron levels significantly decreased to half, or even less, compared with the Pre levels at week 1 and remained low. The changes in TSAT and serum iron levels exhibited a significant positive correlation with the changes in body weight (R = 0.720; R = 0.627) and with energy intake (R = 0.410; R = 461) in T5. LEA occurs in rugby summer camp but is difficult to assess using weight change. Alternately, TSAT and serum iron levels after overnight fast may be better predictors of LEA.

Wearable Technologies in Field Hockey Competitions: A Scoping Review

The aim of this review is to investigate the common wearable devices currently used in field hockey competitions, and to understand the hockey-specific parameters these devices measure. A systematic search was conducted by using three electronic databases and search terms that included field hockey, wearables, accelerometers, inertial sensors, global positioning system (GPS), heart rate monitors, load, performance analysis, player activity profiles, and competitions from the earliest record. The review included 39 studies that used wearable devices during competitions. GPS units were found to be the most common wearable in elite field hockey competitions, followed by heart rate monitors. Wearables in field hockey are mostly used to measure player activity profiles and physiological demands. Inconsistencies in sampling rates and performance bands make comparisons between studies challenging. Nonetheless, this review demonstrated that wearable devices are being used for various applications in field hockey. Researchers, engineers, coaches, and sport scientists can consider using GPS units of higher sampling rates, as well as including additional variables such as skin temperatures and injury associations, to provide a more thorough evaluation of players’ physical and physiological performances. Future work should include goalkeepers and non-elite players who are less studied in the current literature.

Analysis of the worst-case scenarios in an elite football team: Towards a better understanding and application

This study investigated the variability in the worst-case scenario (WCS) and suggested a framework to improve the definition and guide further investigation. Optical tracking data from 26 male players across 38 matches were analysed to determine the WCS for total distance, high-speed running (>5.5 m.s-1) and sprinting (>7.0 m.s-1) using a 3-minute rolling window. Position, total output, previous epoch, match half, time of occurrence, classification of starter vs substitute, and minutes played were modelled as selected contextual factors hypothesized to have associations with the WCS. Linear mixed effects models were used to account for cross-sectional observations and repeated measures. Unexplained variance remained high (total distance R2 = 0.53, high-speed running R2 = 0.53 and sprinting R2 = 0.40). Intra-individual variability was also high (total distance CV = 4.6-8.2%; high-speed CV = 15.6-37.8% and Sprinting CV = 21.1-76.4%). The WCS defined as the maximal physical load in a given time-window, produces unstable metrics lacking context, with high variability. Furthermore, training drills targetting this metric concurrently across players may not have representative designs and may underprepare athletes for complete match demands and multifaceted WCS scenarios. Using WCS as benchmarks (reproducing similar physical activity for training purposes) is conceptually questionable.

The Relationship between Training Load Measures and Next-Day Well-Being in Rugby Union Players

The aim of this study is to identify the relationship between different internal and external load measures and next day subjective wellbeing. With institutional ethics approval, ten academy rugby union players (Five forwards, and five backs) with a local National League One club agreed to participate in the study (aged; 18.4 ± 1.0 years, height; 181.3 ± 5.9 cm, body mass 85.9 ± 13.0 kg, VO2max 56.2 ± 6.8 mL·kg−1·min−1). Before the 6-week in-season data collection period, participants completed an incremental treadmill test to determine lactate thresholds at 2 mmol·L−1 (LT) and 4 mmol·L−1 and the heart rate blood lactate (HR-BLa) profile for individualized training impulse (iTRIMP) calculations. Internal training load was quantified using Banister’s TRIMP, Edward’s TRIMP, Lucia’s TRIMP, individualised TRIMP and session-RPE. External training load was reported using total distance, PlayerLoadTM, high-speed distances (HSD) > 18 km∙h−1 and >15 km∙h−1, and individualized high-speed distance (iHSD) based on each player’s velocity at OBLA. On arrival and prior to all training sessions players completed a well-being questionnaire (WB). Bayesian linear mixed model analysis identified that a range of internal and external load measures explained between 30% and 37% of next-day total wellbeing and between 65% and 67% of next-day perceived stress. All other internal and external load measures demonstrated very weak to moderate relationships (R2 = 0.08 to 0.39) with all other wellbeing components. Internal sRPE, iTRIMP and bTRIMP loads alongside external HSD loads provide coaches with the most practical measures to influence players’ perceived wellbeing.

Influence of Contextual Factors, Technical Performance, and Movement Demands on the Subjective Task Load Associated With Professional Rugby League Match-Play

PURPOSE

To identify the association between several contextual match factors, technical performance, and external movement demands on the subjective task load of elite rugby league players.

METHODS

Individual subjective task load, quantified using the National Aeronautics and Space Administration Task Load Index (NASA-TLX), was collected from 29 professional rugby league players from one club competing in the European Super League throughout the 2017 season. The sample consisted of 26 matches (441 individual data points). Linear mixed modeling revealed that various combinations of contextual factors, technical performance, and movement demands were associated with subjective task load.

RESULTS

Greater number of tackles (effect size correlation ± 90% confidence intervals; η2 = .18 ± .11), errors (η2 = .15 ± .08), decelerations (η2 = .12 ± .08), increased sprint distance (η2 = .13 ± .08), losing matches (η2 = .36 ± .08), and increased perception of effort (η2 = .27 ± .08) led to most likely-very likely increases in subjective total task load. The independent variables included in the final model for subjective mental demand (match outcome, time played, and number of accelerations) were unclear, excluding a likely small correlation with technical errors (η2 = .10 ± .08).

CONCLUSIONS

These data provide a greater understanding of the subjective task load and their association with several contextual factors, technical performance, and external movement demands during rugby league competition. Practitioners could use this detailed quantification of internal loads to inform recovery sessions and current training practices.

Relationship Between Reactive Strength Index Variants in Rugby League Players

ABSTRACT

McMahon, JJ, Suchomel, TJ, Lake, JP, and Comfort, P. Relationship between reactive strength index variants in rugby league players. J Strength Cond Res 35(1): 280-285, 2021-Two reactive strength index (RSI) variants exist, the RSI and RSI modified (RSImod), which are typically calculated during the drop jump (DJ) and countermovement jump (CMJ), respectively. Both RSI variants have been used to monitor athletes' ability to complete stretch-shortening cycle actions quickly, but they have never been compared. The purpose of this study was to determine whether they yield relatable information about reactive strength characteristics. Male professional rugby league players (n = 21, age = 20.8 ± 2.3 years, height = 1.82 ± 0.06 m and body mass = 94.3 ± 8.4 kg) performed 3 DJs (30 cm) and CMJs on a force plate. Reactive strength index and RSImod were subsequently calculated by dividing jump height (JH) by ground contact time (GCT) and time to take-off (TTT), respectively. All variables were highly reliable (intraclass correlation coefficient ≥0.78) with acceptable levels of variability (coefficient of variation ≤8.2%), albeit larger variability was noted for DJ variables. Moreover, there was a large relationship between RSI and RSImod (r = 0.524, p = 0.007), whereas very large relationships were noted between JHs (r = 0.762, p < 0.001) and between GCT and TTT (ρ = 0.705, p < 0.001). In addition, RSI (0.90 ± 0.22) was largely and significantly (d = 2.57, p < 0.001) greater than RSImod (0.47 ± 0.08). The DJ-derived RSI yields much larger values than the CMJ-derived RSImod and although a large relationship was noted between them, it equated to just 22% shared variance. These results suggest that the 2 RSI variants do not explain each other well, indicating that they do not assess entirely the same reactive strength qualities and should not be used interchangeably.

Relationship Between Preseason Training Load, Match Performance, and Match Activities in Professional Rugby League

Crang, ZL, Hewitt, A, Scott, TJ, Kelly, VG, and Johnston, RD. Relationship between pre-season training load, match performance and match activities in professional rugby league. J Strength Cond Res XX(X): 000-000, 2020-This study aimed to establish the relationship between preseason training loads, technical match performance, and physical match activities in rugby league. Twenty-two professional rugby league players (age: 24.7 ± 4.0 years; height: 184.3 ± 4.7 cm; and body mass: 101.1 ± 9.9 kg) participated in the study. Training loads and physical match activities were monitored using global positioning systems. Total distance (m), high-speed running distance (VT1IFT; distance covered above estimated first ventilatory threshold [≥68% of 30-15 intermittent fitness test]) and total session rating of perceived exertion from all field-based (32.5 ± 8.5) and gym-based sessions (39.1 ± 12.5) were used to quantify preseason loads. Physical match activities were measured as total and high-speed running distance relative to individual playing time, whereas technical match activities and performance scores were used to evaluate individual match performance. To examine the relationship between physical match activities, technical performance, and preseason load, Pearson's correlation coefficients were quantified for each in-season game before performing a Fisher Z Transformation. Preseason high-speed running distance was positively associated with high-speed match activities (r = 0.34-0.51), whereas negatively associated with technical performance scores (r = -0.51 to -0.35) and hit up m·min of match-play (r = -0.30 to -0.17). It seems high speed running performed in the preseason period positively influences in-season physical match activity profiles, however, are unlikely to positively impact technical match performance.

Positional In-Match Running Demands of University Rugby Players in South Africa

The implementation of the Varsity Cup rugby competition among South African universities has sparked interest in university rugby cultures around the country. The Varsity Cup has established itself as one of the most important rugby competitions for full-time students. The development of specific conditioning programs for rugby players requires a thorough understanding of the game and the unique demands of playing positions. Therefore, the study aimed to investigate the in-match running demands of South African university rugby players by using GPS during match play for primary and secondary positional groups. Rugby players (n = 40) from two universities were assessed during match play (n = 17) over a competitive season by using GPS. Players were grouped into two primary positional groups, forwards (n = 22) and backs (n = 18), and five secondary positional groups, tight forwards (n = 14), loose forwards (n = 8), half backs (n = 5), inside backs (n = 6), and outside backs (n = 7). The GPS analysis provided the following match-play movements: total distance, high-speed meters, maximum velocity, match intensity, the number of accelerations and decelerations, and velocity zone. Halfbacks recorded the highest total distance (6620.9 ± 784.4 m; p = 0.02) and match intensity (77.7 ± 11.6 m/min; p = 0.01). Outside backs recorded the highest maximum velocity (8.385 ± 1.242 m/s; p = 0.00). Loose forwards registered the highest number of accelerations (385.5 ± 122.1) and decelerations (378.7 ± 108.1). Backs and their specific subgroups play at and within high velocity thresholds, significantly higher (p = 0.01) than that of the forwards. Forwards tend to be involved in a higher amount of accelerations and decelerations during match play, suggesting that forward play is at close quarters to the opposition. During university rugby matches, the backs covered greater distances and speeds than the forwards, whereas the forwards achieved more accelerations and decelerations than backs. Results from the study can assist Varsity Cup strength and conditioning coaches to prepare players for the position-specific demands of the competition.

Measurement of lower-limb asymmetry in professional rugby league: a technical note describing the use of inertial measurement units

Background

Quantifying lower-limb load and asymmetry during team sport match-play may be important for injury prevention and understanding performance. However, current analysis methods of lower-limb symmetry during match-play employ wearable microtechnology that may not be best suited to the task. A popular microtechnology is global positioning systems (GPS), which are torso worn. The torso location, and the summary workload measures calculated by GPS are not suited to the calculation of lower-limb load. Instead, research grade accelerometers placed directly on the lower-limb may provide better load information than GPS. This study proposes a new technique to quantify external mechanical load, and lower-limb asymmetry during on-field team sport play using inertial measurement units.

Methods

Four professional rugby league players (Age: 23.4  ± 3.1 years; Height: 1.89  ± 0.05 m; Mass: 107.0  ± 12.9 kg) wore two accelerometers, one attached to each foot by the boot laces, during match simulations. Custom Matlab (R2017b, The Mathworks Inc, Natick, MA) code was used to calculate total time, area under the curve (AUC), and percentage of time (%Time) spent in seven acceleration categories (negative to very high, <0 g to >16 g), as well as minimum and maximum acceleration during match simulations. Lower-limb AUC and %Time asymmetry was calculated using the Symmetry Angle Equation, which does not require normalization to a reference leg.

Results

The range of accelerations experienced across all participants on the left and right sides were 15.68–17.53 g, and 16.18–17.69 g, respectively. Clinically significant asymmetry in AUC and %Time was observed for all but one participant, and only in negative (<0 g) and very high accelerations (>16 g). Clinically significant AUC differences in very high accelerations ranged from 19.10%–26.71%. Clinically significant %Time differences in negative accelerations ranged from 12.65%–25.14%, and in very high accelerations from 18.59%–25.30%. All participants experienced the most AUC at very low accelerations (2–4 g), and the least AUC at very high accelerations (165.00–194.00 AU vs. 0.32–3.59 AU). The %Time results indicated that all participants spent the majority of match-play (73.82–92.06%) in extremely low (0–2 g) to low (4–6 g) acceleration intensities, and the least %Time in very high accelerations (0.01%–0.05%).

Discussion

A wearable located on the footwear to measure lower-limb load and asymmetry is feasible to use during rugby league match-play. The location of the sensor on the boot is suited to minimize injury risk occurring from impact to the sensor. This technique is able to quantify external mechanical load and detect inter limb asymmetries during match-play at the source of impact and loading, and is therefore likely to be better than current torso based methods. The results of this study may assist in preparing athletes for match-play, and in preventing injury.

Quantification of Movement Characteristics in Women's English Premier Elite Domestic Rugby Union

This study aims were to determine the positional physical requirements of English domestic women’s rugby union match-play. Global positioning system data (Catapult Minimax S4) were collected at 10 Hz of 129 competitive player games from the Tyrrells Premier15 league. Players were classified according to broad (Forwards, Backs) and specific positions (front-, second-, back-row, scrum-half, inside-, and outside-backs). Total distances, maximum speed, and player loads were calculated. Mean total distance was 4982 m and was similar between the Forwards and Backs, with second-row players covering the most (5297 m) and outside-backs the least (4701 m). Inside- and outside-backs covered a significantly greater distance at high speed running (134 m; 178 m) and sprinting (74 m; 92 m) speeds, respectively, whereas the second- and back-row covered greater distances jogging (1966 m; 1976 m) and the front-row spent the greatest overall distance walking (2613 m). Outside-backs reached greater maximum speed than all other positions (24.9 km.h-1). The mean player load was highest in the back-row (562 AU) and second-row (555 AU) and these were higher than the outside-backs (476 AU). These findings indicate that the demands placed on female rugby players are position specific and differ from male players. Additionally, the data are the first obtained from the 10 Hz GPS and from within English domestic women’s rugby, thus adding to the overall limited data available on women’s rugby union.

Comparison between Two Different Device Models 18 Hz GPS Used for Time-Motion Analyses in Ecological Testing of Football

Background: The aim of this study was to compare the validity of two different GPS device models used for time–motion analyses in ecological testing of football. Methods: Ten healthy male players from a Spanish university football team participated in this study. The team sport simulation circuit (TSCC) used was based on previous research examining the validity and interunit reliability of different GPS systems. Participants were required to complete eight laps of the TSSC, resulting in a total distance of 1320 m. The GPS units used for the current study were the 18 Hz StatsSport Apex Pro and 18 Hz RealTrack WIMU Pro. Participants were required to wear either of the two GPS units during the test. To establish the construct validity of GPS as a measure of V_max, timing lights were used as a gold standard. Results: The results clearly suggest that it is not possible to use the same 18 Hz GPS model or interchange it. The measurement can be considered precise when the noise is at least equal to or lower than the smallest worthwhile change. In this case, all standard deviation in measurement error was higher than the smallest worthwhile change. This is due to an inconsistency in the data processing of each trademark. Conclusions: It is important to prevent a club using different GPS trademarks at the same time, since it is not possible to compare in any case any type of result obtained between different trademarks.

Movement patterns of players in the Australian Women's Rugby League team during international competition

OBJECTIVES

To describe the movement patterns of the Australian Women's Rugby League team during international competition.

DESIGN

Retrospective observational study.

METHODS

Global Positioning Systems technology recorded the movements of players from the Australian Women's Rugby League team (n=31) during seven international rugby league matches. A subgroup of players (n=18) that played at least 80min in a match were categorized into three positional groups: forwards (n=7), backs (n=7) and halves (n=4), and analysed for external outputs that were classified into multiple speed zones. Mean speed (mmin^-1) and mean speed when travelling >12kmh^-1 (MS₁₂; mmin^-1) were calculated for each 10% interval of playing time of both groups to assess changes in match intensity.

RESULTS

Total distance travelled was greater in the first half (3332.9m compared to 3249.0m), along with distances travelled at speeds >15kmh^-1 (p<0.05), whereas players travelled further at speeds <6kmh^-1 in the second half (p=0.005). Backs travelled further at speeds <6kmh^-1 (p=0.002) and >15kmh^-1 (p=0.007) compared to forwards. Mean speed significantly reduced across the first and second halves (p<0.05), while MS₁₂ reduced by ∼40% in the first half of the match (i.e. first ∼5min compared to the last ∼5min).

CONCLUSION

These results provide coaches with sport-specific activity profiles of female rugby league players that can be used to individualise training prescription. Given that match-intensity deteriorated across the first and second halves, programs may be targeted at improving endurance and supramaximal exercise tolerance in order for female players to withstand high match-demands of international competition.

Activity Profile of Elite Netball Umpires During Match Play

Spencer, KN, Paget, N, Farley, ORL, and Kilding, AE. Activity profile of elite netball umpires during match play. J Strength Cond Res 34(10): 2832-2839, 2020-The study aimed to determine activity profiles of officials in elite netball. Physical demands of Load·min (au) representing accumulated accelerations by triaxial accelerometers during matches and exercise-to-rest ratio were measured using global positioning systems (Catapult, MinimaxX S4). Physiological demands were quantified by estimated equivalent distance and heart rate (HR) (MeanHR, percentage HRpeak, and HRzones) and movement variables (frequency, mean time, and percentage of total time) were coded using Sportscode Elite (Version 10, Hudl, Lincoln, Nebraska). Differences were analyzed by periods (Q1-Q4). Load·min (au) (M = 407 ± 66) significantly varied with time (F [3, 55] = 3.42, p = 0.02) and the highest percentage of exercise-to-rest performed in Q1 (21 ± 5%). Estimated equivalent distance (3,839 ± 614 m) varied significantly with time (F [3, 56] = 3.18, p = 0.03), the umpires spent longest duration of time (35%) in HRzone 3 (75-85% of HRpeak). Mean HR significantly decreased with time (p < 0.01; Q1 [157 ± 13], quarter 2 [156 ± 12], and Q4 [153 ± 14]). Umpires spent 77% in rest-recovery ratio movements and 23% of time exercise-to-rest ratio. In summary, netball umpiring is characterized by intermittent, short, high-intensity activity (sprinting, sidestepping, and turn to change direction), with increasing periods of rest-recovery (walking and standing).

The Demands of Professional Rugby League Match-Play: a Meta-analysis

Background

Rugby league is a collision sport, where players are expected to be physically competent in a range of areas, including aerobic fitness, strength, speed and power. Several studies have attempted to characterise the physical demands of rugby league match-play, but these studies often have relatively small sample sizes based on one or two clubs, which makes generalisation of the findings difficult. Therefore, the aim of this review was to synthesise studies that investigated the physical demands of professional rugby league match-play.

Methods

SPORTDiscus, CINAHL, MEDLINE (EBSCO) and Embase (EBSCO) databases were systematically searched from inception until October 2018. Articles were included if they (1) recruited professional rugby league athletes aged ≥ 18 years and (2) provided at least one match-play relevant variable (including playing time, total and relative distance, repeat high-intensity efforts (RHIE), efforts per RHIE, accelerations and decelerations, total and relative collisions). Meta-analyses were used to provide pooled estimates ± 95% confidence intervals.

Results

A total of 30 studies were included. Pooled estimates indicated that, compared to adjustables and backs, forwards have less playing time (− 17.2 ± 5.6 and − 25.6 ± 5.8 min, respectively), cover less ‘slow-speed’ (− 2230 ± 735 and − 1348 ± 655 m, respectively) and ‘high-speed’ distance (− 139 ± 108 and − 229 ± 101 m, respectively), but complete more relative RHIEs (+ 0.05 ± 0.05 and + 0.08 ± 0.04 per minute, respectively), and total (+ 12.0 ± 8.1 and + 12.8 ± 7.2 collisions, respectively) and relative collisions (+ 0.32 ± 0.22 and + 0.41 ± 0.22 collisions per minute, respectively). Notably, when the distance was expressed relative to playing time, forwards were not different from adjustables and backs in slow-speed (P ≥ 0.295) and high-speed (P ≥ 0.889) relative distance. The adjustables and backs subgroups were similar in most variables, except playing time (shorter for adjustables, − 8.5 ± 6.2 min), slow-speed distance (greater for adjustables, + 882 ± 763 m) and total relative distance (greater for adjustables, + 11.3 ± 5.2 m·min⁻¹). There were no significant differences between positional groups for efforts per RHIE, accelerations and decelerations (P ≥ 0.745).

Conclusions

These results indicate the unique physical demands of each playing position and should be considered by strength and conditioning and tactical coaches when planning for professional rugby league performance.

Protocol Registration

https://osf.io/83tq2/

Electronic supplementary material

The online version of this article (10.1186/s40798-019-0197-9) contains supplementary material, which is available to authorized users.

Comparison of Preseason and In-Season Practice and Game Loads in National Collegiate Athletic Association Division I Football Players

Wellman, AD, Coad, SC, Flynn, PJ, Siam, TK, and McLellan, CP. A Comparison of preseason and in-season practice and game loads in NCAA Division I football players. J Strength Cond Res 33(4): 1020-1027, 2019-The aim of this study was to quantify the individual practice and game loads throughout the National Collegiate Athletic Association (NCAA) Division I football season to determine whether significant differences exist between the practice loads associated with the preseason training camp and those undertaken during the in-season period. Thirty-one NCAA Division I football players were monitored using the global positioning system and triaxial accelerometer (IA) (MinimaxX S5; Catapult Innovations, Melbourne, Australia) during 22 preseason practices, 36 in-season practices, and 12 competitions. The season was divided into 4 distinct phases for data analysis: preseason week 1 (preseason 1), preseason week 2 (preseason 2), preseason week 3 (preseason 3), and 12 in-season weeks. Individual IA data sets represented players from every offensive and defensive position group Wide Receiver (WR: n = 5), Offensive Line (OL: n = 4), Running Back (RB: n = 4), Quarterback (QB: n = 2), Tight End (TE: n = 3), Defensive Line (DL: n = 4), Linebacker (LB: n = 4), Defensive Back (DB: n = 5). Data were set at the practice level, where an observation for each player's maximum player load (PLMax) or mean player load (PLMean) from each training camp phase was referenced against each player's respective PL from each game, Tuesday, Wednesday, or Thursday practice session. Notable results included significantly (p ≤ 0.05) greater PLMax values attributed to preseason 1 compared with PL resulting from all in-season practices, and significantly (p ≤ 0.05) higher cumulative PL reported for preseason 1, 2, and 3 compared with every in-season week. Data from this study augment our understanding of the practice demands experienced by NCAA Division I college football players, and provide scope for the improvement of preseason practice design and physical conditioning strategies for coaches seeking to optimize performance.

The Use of Microtechnology to Quantify the Peak Match Demands of the Football Codes: A Systematic Review

BACKGROUND

Quantifying the peak match demands within the football codes is useful for the appropriate prescription of external training load. Wearable microtechnology devices can be used to identify the peak match demands, although various methodologies exist at present.

OBJECTIVES

This systematic review aimed to identify the methodologies and microtechnology-derived variables used to determine the peak match demands, and to summarise current data on the peak match demands in the football codes.

METHODS

A systematic search of electronic databases was performed from earliest record to May 2018; keywords relating to microtechnology, peak match demands and football codes were used.

RESULTS

Twenty-seven studies met the eligibility criteria. Six football codes were reported: rugby league (n = 7), rugby union (n = 5), rugby sevens (n = 4), soccer (n = 6), Australian Football (n = 2) and Gaelic Football (n = 3). Three methodologies were identified: moving averages, segmental and 'ball in play'. The moving averages is the most commonly used (63%) and superior method, identifying higher peak demands than other methods. The most commonly used variables were relative distance covered (63%) and external load in specified speed zones (57%).

CONCLUSION

This systematic review has identified moving averages to be the most appropriate method for identifying the peak match demands in the football codes. Practitioners and researchers should choose the most relevant duration-specific period and microtechnology-derived variable for their specific needs. The code specific peak match demands revealed can be used for the prescription of conditioning drills and training intensity.

Energetic Demands of Interchange and Full-Match Rugby League Players

Cummins, CJ, Gray, AJ, Shorter, KA, Halaki, M, and Orr, R. Energetic demands of interchange and full-match rugby league players. J Strength Cond Res 32(12): 3456-3464, 2018-The purpose of this study was to describe and compare the metabolic demands of rugby league for interchange and full-match players in relation to positional groups. Eighteen elite rugby league players were recruited. A time-motion model was used to estimate the energy expenditure and metabolic demands of rugby league match-play using Global Positioning System (GPS) technology. This approach uses players' GPS velocity-time curves to examine running velocity. Players were categorized into positional groups (outside backs, adjustables, wide-running, and hit-up forwards) and then further categorized into full-match or interchange players. Compared with their full-match counterparts, interchange wide-running forwards expended greater energy (43.1 ± 6.1 vs. 28.6 ± 7.5 kJ·kg, p ≤ 0.001, effect size [ES] = -2.38) and produced a higher anaerobic index (p = 0.016, ES = 0.56) and mean power (7.4%, p = 0.003, ES = 0.66) per match. Full-match adjustables expended 94.8% more energy (p ≤ 0.001, ES = -2.3) and performed more moderate accelerations (10.1%, p = 0.014, ES = -0.57) and decelerations (7.6%, p = 0.017, ES = -0.8), than their interchange counterparts. Outside backs did not interchange and hit-up forwards rarely (n = 2) played an entire match. Differing metabolic demands were identified for interchange and full-match players across positional groups, suggesting position-specific conditioning drills are required to model the energetic demands of match-play.

Anthropometric and Physical Qualities of Elite Male Youth Rugby League Players

Rugby league is a collision team sport played at junior and senior levels worldwide, whereby players require highly developed anthropometric and physical qualities (i.e. speed, change-of-direction speed, aerobic capacity, muscular strength and power). Within junior levels, professional clubs and national governing bodies implement talent identification and development programmes to support the development of youth (i.e. 13-20 years) rugby league players into professional athletes. This review presents and critically appraises the anthropometric and physical qualities of elite male youth rugby league players aged between 13 and 20 years, by age category, playing standard and playing position. Height, body mass, body composition, linear speed, change-of-direction speed, aerobic capacity, muscular strength and power characteristics are presented and demonstrate that qualities develop with age and differentiate between playing standard and playing position. This highlights the importance of anthropometric and physical qualities for the identification and development of youth rugby league players. However, factors such as maturity status, variability in development, longitudinal monitoring and career attainment should be considered to help understand, identify and develop the physical qualities of youth players. Further extensive research is required into the anthropometric and physical qualities of youth rugby league players, specifically considering national standardised testing batteries, links between physical qualities and match performance, together with intervention studies, to inform the physical development of youth rugby league players for talent identification and development purposes.

Match Demands of Senior and Junior Players During International Rugby League

Dempsey, GM, Gibson, NV, Sykes, D, Pryjmachuk, BC, and Turner, AP. Match demands of senior and junior players during International Rugby League. J Strength Cond Res 32(6): 1678-1684, 2018-This study aims to quantify and compare the positional game demands of international junior and senior rugby league competition for the first time. Global positioning system (GPS) and video analysis were used to track 118 elite male rugby league players (57 seniors aged 28.7 ± 4.4 years; 61 juniors aged 17.2 ± 0.5 years) over 10 international matches (6 senior; 4 junior) characterized as either forwards (n = 67) or backs (n = 51). There were significant increases in the offensive carries (0.18 cf. 0.09 n·min; r = 0.56) and defensive tackles (0.36 cf. 0.23 n·min; r = 0.3) between senior and junior players, and forwards and backs (0.16 cf. 0.09; r = 0.34 and 0.41 cf. 0.14; r = 0.52), respectively. Running demands were significantly greater in backs than forwards (independent of playing level) for total distance (6,962 ± 1,263 m cf. 4,879 ± 1,824 m; r = 0.55), individualized high-speed distances (310 ± 158 m cf. 250 ± 171 m; r = 0.2), high-intensity accelerations (28.7 ± 12.1 m·s cf. 21.9 ± 11.7 m·s; r = 0.27), and decelerations (57.2 ± 18.3 m·s cf. 43.0 ± 17.8 m·s; r = 0.38). Positional differences were eliminated when reported relative to minutes played. From a practical perspective, although running demands relative to time on the pitch may prepare junior players for senior competition, it is not representative of the increased body mass and contact frequency within the senior game. Coaches should therefore reflect these differences within their physical preparation programs to prepare junior athletes accordingly for progression to the senior level.

Differences in Speed and Power Capacities Between Female National College Team and National Olympic Team Handball Athletes

The aim of this study was to compare and examine differences in several neuromuscular assessments between female national Olympic team (Rio-2016) and national college team handball players (2015-Gwangju Summer Universiade). Twenty-eight elite female handball players of the national Brazilian Olympic (n = 12) and college (n = 16) teams participated in this study. The Olympic and college athletes performed the following speed-power tests assessing mean propulsive power (MPP) in loaded jump squat (JS) and bench press (BP) exercises, unloaded squat and countermovement jumps (SJ and CMJ), sprint performance over 5-, 10-, and 20-m, and change of direction ability in a standard Zig-zag test and a T-Test. The differences between Olympic and college team performances in all variables were analyzed using the magnitude-based inference. The Olympic group presented likely higher performances in the SJ, CMJ, and MPP JS and very likely higher performances in the MPP BP and T-Test than the college group. The differences in the linear sprint velocity in 5-, 10-, and 20-m tests as well as in the Zig-zag test were all rated as unclear. These findings may have substantial implications for the development of effective strength-power training and testing strategies in elite handball. In addition, coaches and researchers can use these data to create efficient talent identification programs for youth handball players.

The peak duration-specific locomotor demands and concurrent collision frequencies of European Super League rugby

Understanding the most demanding passages of European Super League competition can optimise training prescription. We established positional and match half differences in peak relative distances (m·min^-1) across durations, and the number of collisions, high-speed- and very-high-speed-distance completed in the peak 10 min period. Moving-averages (10 s, 30 s, 1 min, 5 min, 10 min) of instantaneous speed (m·s^-1) were calculated from 25 professional rugby league players during 25 matches via microtechnology. Maximal m·min^-1 was taken for each duration for each half. Concurrently, collisions (n), high-speed- (5 to 7 m·s^-1; m) and very-high-speed-distance (> 7 m·s^-1; m) were coded during each peak 10 min. Mixed-effects models determined differences between positions and halves. Aside from peak 10 s, trivial differences were observed in peak m·min^-1 between positions or halves across durations. During peak 10 min periods, adjustables, full- and outside-backs ran more at high-speed and very-high-speed whilst middle- and edge-forwards completed more collisions. Peak m·min^-1 is similar between positional groups across a range of durations and are maintained between halves of the match. Practitioners should consider that whilst the overall peak locomotor "intensity" is similar, how they achieve this differs between positions with forwards also exposed to additional collision bouts.

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.

Postmatch recovery of physical performance and biochemical markers in team ball sports: a systematic review

Background

Insufficient postmatch recovery in elite players may cause an increased risk of injuries, illnesses and non-functional over-reaching.

Objective

To evaluate postmatch recovery time courses of physical performance and biochemical markers in team ball sport players.

Study design

Systematic review.

Data sources

PubMed and Web of Science.

Eligibility criteria for selecting studies

This systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Critical Review Form for Quantitative Studies was used to evaluate quality. Studies were included if they met the following criteria: (1) original research evaluated players’ physical recovery postmatch; (2) team/intermittent sports; and (3) at least two postmeasurements were compared with baseline values.

Results

Twenty-eight studies were eligible. Mean methodological quality was 11.2±1.11. Most used performance tests and biochemical markers were the countermovement jump test, sprint tests and creatine kinase (CK), cortisol (C) and testosterone (T), respectively.

Summary/conclusions

The current evidence demonstrates that underlying mechanisms of muscle recovery are still in progress while performance recovery is already reached. CK recovery time courses are up to ≥72 hours. Soccer and rugby players need more time to recover for sprint performance, CK and C in comparison to other team ball sports. There are more high-quality studies needed regarding recovery in various team sports and recovery strategies on an individual level should be evaluated.

Clinical relevance

Ongoing insufficient recovery can be prevented by the use of the presented recovery time courses as specific practical recovery guidelines.

The Work-Rate of Elite Hurling Match-Play

Collins, DK, McRobert, A, Morton, JP, O'Sullivan, D, and Doran, DA. The work-rate of elite hurling match-play. J Strength Cond Res 32(3): 805-811, 2018-This study describes the global work-rate of elite hurling match-play and the influence which positional difference has on work-rate is considered. The movement of ninety-four players was recorded using global positioning system, sampling at 4 Hz in a total of 12 games. Data were classified according to the positional line on the field and period of the match. The total and high-speed distance of match-play was 7,617 ± 1,219 m (95% confidence interval [CI], 7,367-7,866) and 1,134 ± 358 m (95% CI, 1,060-1,206), respectively. The maximum speed attained was 29.8 ± 2.3 km·h with a mean speed of 6.1 ± 1 km·h. The second {271 ± 107 m (p = 0.001; effect size [ES] = 0.25)}, third (278 ± 118 m [p = 0.001; ES = 0.21]), and fourth quarter (255 ± 108 m [p = 0.001; ES = 0.31]) high-speed running distance differed significantly from that of the first quarter (330 ± 120 m). There was a significant difference in total (p = 0.001; ES = 0.01-0.85), high-speed running (p = 0.001; ES = 0.21-0.76), and sprint (p = 0.013; ES = 0.01-0.39) distance across the positions, with midfielders undertaking the highest volume of work, followed by the half-forward and half-back lines and finally the full-forward and full-back lines. A decrease in high-speed running distance seems to occur through out the game and in particular at the latter stages of each half. Distinct positional work profiles are evident. The present finding provide a context on which training which replicates the work-rate of match-play may be formulated, thus helping to improve the physical preparation of elite players.

Quantification of Accelerometer Derived Impacts Associated With Competitive Games in National Collegiate Athletic Association Division I College Football Players

Wellman, AD, Coad, SC, Goulet, GC, and McLellan, CP. Quantification of accelerometer derived impacts associated with competitive games in National Collegiate Athletic Association division I college football players. J Strength Cond Res 31(2): 330-338, 2017-The aims of the present study were to (a) examine positional impact profiles of National Collegiate Athletic Association (NCAA) division I college football players using global positioning system (GPS) and integrated accelerometry (IA) technology and (b) determine if positional differences in impact profiles during competition exist within offensive and defensive teams. Thirty-three NCAA division I Football Bowl Subdivision players were monitored using GPS and IA (GPSports) during 12 regular season games throughout the 2014 season. Individual player data sets (n = 294) were divided into offensive and defensive teams, and positional subgroups. The intensity, number, and distribution of impact forces experienced by players during competition were recorded. Positional differences were found for the distribution of impacts within offensive and defensive teams. Wide receivers sustained more very light and light to moderate (5-6.5 G force) impacts than other position groups, whereas the running backs were involved in more severe (>10 G force) impacts than all offensive position groups, with the exception of the quarterbacks (p ≤ 0.05). The defensive back and linebacker groups were subject to more very light (5.0-6.0 G force) impacts, and the defensive tackle group sustained more heavy and very heavy (7.1-10 G force) impacts than other defensive positions (p ≤ 0.05). Data from the present study provide novel quantification of positional impact profiles related to the physical demands of college football games and highlight the need for position-specific monitoring and training in the preparation for the impact loads experienced during NCAA division I football competition.

Application of Global Positioning System and Microsensor Technology in Competitive Rugby League Match-Play: A Systematic Review and Meta-analysis

BACKGROUND

The use of global positioning system (GPS) devices with the inclusion of microsenor technology in rugby league enables measurement of player activity profiles to understand the demands of match-play and optimise on-field performance.

OBJECTIVE

The aim of this review was to systematically review the use of GPS and microsensor technology to quantify player activity profiles in match-play, and conduct a meta-analysis of relevant movement variables in order to present the contemporary and emerging themes within rugby league.

METHODS

A systematic search of electronic databases (MEDLINE, SPORTDiscus, CINAHL, Web of Science, Scopus, ScienceDirect, EMBASE, and Google Scholar) from the earliest record to February 2015 was conducted. Permutations of key words included GPS, microtechnology, activity profiles, match demands (movement or physical demands), and rugby league. A meta-analysis was conducted to provide a pooled mean and confidence intervals on comparable data from at least three studies.

RESULTS

Twenty-seven studies met the eligibility criteria and included 1270 male participants. The studies reported on GPS use in elite competition (n = 16) with limited representation of other competition standards: sub-elite (n = 6), amateur (n = 1) and junior (n = 3). All studies reported on movement variables (distance, relative distance, speed and accelerations), with studies analysing movement at high speed (n = 18, 66.7%), evaluating collision or impact variables (n = 15, 55.6%) and determining the metabolic energy (n = 2, 7.4%) associated with rugby league match-play. Activity profiles of varying positions, positional groups and levels of rugby league competition were described. Meta-analysis indicated that the total distance covered by backs and adjustables were both greater than forward positions, but adjustables covered greater relative distance than forwards and backs. Speed zones were typically categorised into six speed zones ranging from 0 to 36 km·h(-1), or into low- and high-intensity movement. Vast inconsistencies were apparent across studies in categorising movement at high speed, posing difficulties for comparison. Meta-analysis indicated that, although the number of repeated high-intensity effort (RHIE) bouts in elite players were similar to sub-elite (and both greater than juniors), the number of efforts per RHIE were significantly greater in elite than sub-elite players. Differential pacing strategies were adopted according to player selection (whole-match vs. interchange), time period within match-play and match outcome, in order to maintain high-intensity performance or to challenge for a win. Sizeable inconsistencies were also identified in the definitions of reported collisions (classified as mild, moderate and heavy) and impacts (six zone categories provided by manufacturer), making comparisons across studies difficult. Collision profiles were different between competition standard and position where elite players and forwards sustained more moderate- and high-intensity collisions than sub-elite players and backs, respectively. The recent inclusion of GPS-derived metabolic indices to activity profiles has also accentuated the distinctive workloads of positional groups during match-play where adjustables demonstrate the highest energy expenditure and metabolic power.

CONCLUSIONS

This review and the results of the meta-analysis have demonstrated that positional groups have varied kinematic and metabolic demands. During match play, forwards sustain the greatest number of collisions and RHIE bouts, outside backs participate in more high-speed running and cover the greatest distance, and adjustables work at high intensity covering the greatest relative distance with the highest metabolic cost. Therefore, specific training for each positional group should address their match requirements. In addition, sub-elite players exhibit lower intensity of play compared with elite players, as indicated by lower relative distance and less number of efforts per RHIE bout despite similarities in total distance covered and number of RHIE bouts. To prepare them for elite-level play, their training should incorporate higher intensity drills in which greater relative distance and number of efforts per RHIE bout are performed. Furthermore, the lack of consistency in the definition of speed zones, high-intensity movement, collisions and impacts, underscores the difficulties encountered in meaningful comparisons of player activity profiles between studies. Consensus of these definitions would facilitate direct comparisons within rugby league.

Movement Demands of Elite Under-20s and Senior International Rugby Union Players

This study compared the movement demands of elite international Under-20 age grade (U20s) and senior international rugby union players during competitive tournament match play. Forty elite professional players from an U20 and 27 elite professional senior players from international performance squads were monitored using 10Hz global positioning systems (GPS) during 15 (U20s) and 8 (senior) international tournament matches during the 2014 and 2015 seasons. Data on distances, velocities, accelerations, decelerations, high metabolic load (HML) distance and efforts, and number of sprints were derived. Data files from players who played over 60 min (n = 258) were separated firstly into Forwards and Backs, and more specifically into six positional groups; FR-Front Row (prop & hooker), SR-Second Row, BR-Back Row (Flankers & No.8), HB-Half Backs (scrum half & outside half), MF-Midfield (centres), B3 -Back Three (wings & full back) for match analysis. Linear mixed models revealed significant differences between U20 and senior teams in both the forwards and backs. In the forwards the seniors covered greater HML distance (736.4 ± 280.3 vs 701.3 ± 198.7m, p = 0.01) and severe decelerations (2.38 ± 2.2 vs 2.28 ± 1.65, p = 0.05) compared to the U20s, but performed less relative HSR (3.1 ± 1.6 vs 3.2 ± 1.5, p < 0.01), moderate (19.4 ± 10.5 vs 23.6 ± 10.5, p = 0.01) and high accelerations (2.2 ± 1.9 vs 4.3 ± 2.7, p < 0.01) and sprint•min-1 (0.11 ± 0.06 vs 0.11 ± 0.05, p < 0.01). Senior backs covered a greater relative distance (73.3 ± 8.1 vs 69.1 ± 7.6 m•min-1, p < 0.01), greater High Metabolic Load (HML) distance (1138.0 ± 233.5 vs 1060.4 ± 218.1m, p < 0.01), HML efforts (112.7 ± 22.2 vs 98.8 ± 21.7, p < 0.01) and heavy decelerations (9.9 ± 4.3 vs 9.5 ± 4.4, p = 0.04) than the U20s backs. However, the U20s backs performed more relative HSR (7.3 ± 2.1 vs 7.2 ± 2.1, p <0.01) and sprint•min-1 (0.26 ± 0.07 vs 0.25 ± 0.07, p < 0.01). Further investigation highlighted differences between the 6 positional groups of the teams. The positional groups that differed the most on the variables measured were the FR and MF groups, with the U20s FR having higher outputs on HSR, moderate & high accelerations, moderate, high & severe decelerations, HML distance, HML efforts, and sprints•min-1. For the MF group the senior players produced greater values for relative distance covered, HSR, moderate decelerations, HML distance and sprint•min-1. The BR position group was most similar with the only differences seen on heavy accelerations (U20s higher) and moderate decelerations (seniors higher). Findings demonstrate that U20s internationals appear to be an adequate 'stepping stone' for preparing players for movement characteristics found senior International rugby, however, the current study highlight for the first time that certain positional groups may require more time to be able to match the movement demands required at a higher playing level than others. Conditioning staff must also bear in mind that the U20s players whilst maintaining or improving match movement capabilities may require to gain substantial mass in some positions to match their senior counterparts.