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.

Applying common filtering processes to Global Navigation Satellite System-derived acceleration during team sport locomotion.

This study aimed to observe whether there were substantial differences in acceleration during team-sport locomotion between GNSS manufacturers. Speed and acceleration were obtained from 7 professional rugby league athletes via 2 GNSS manufacturers (GPSports EVO, 10 Hz and STATSports Apex, 10 Hz) worn together during the same training sessions (n = 13). Raw GNSS data were exported from respective proprietary software and a 1 Hz, 4th-order Butterworth filter applied, with differences in speed and acceleration calculated between manufacturers. To determine the difference in acceleration and speed, a root mean square deviation (RMSD) was used. Linear mixed models were used and no substantial differences were found between manufacturers in raw and filtered speed variables. RMSD for average acceleration (m · s-2) decreased from raw (RMSD: 1.77 ± 0.37 m · s-2) to those seen at the filtered (RMSD: 0.27 ± 0.23 m · s-2) and twice filtered (0.24 ± 0.23 m · s-2) variables. Raw average acceleration (m · s-2) was substantially higher in Apex compared to EVO (Difference (Diff); CI: -0.82; -0.84 to -0.80). Following application of the common filter there was no substantial difference between GNSS models for average acceleration (Diff; CI: -0.04; -0.04 to -0.04). Acceleration variables derived from each manufacturer's proprietary software were substantially different.

Quantifying the Movement Characteristics of Australian Football League Women's Competition.

ABSTRACT: Thornton, HR, Armstrong, CR, Gamble, T, Rigby, A, Johnston, RD, and Duthie, GM. Quantifying the movement characteristics of Australian Football League Women's competition. J Strength Cond Res 36(12): 3415-3421, 2022-The purpose is to provide an overview of the externally measured movement characteristics of Australian Football League Women's (AFLW) competition, and the variability in this between matches. A range of movement variables were measured from 28 athletes who wore 10-Hz global positioning system devices during games and were summarized according to positional groups. The variance in each athlete's match loads for each round were expressed using standardized scores ( z -scores), and the change compared with the first game played was calculated and expressed as a standard deviation. Furthermore, using the raw export, moving means (1-10 minutes) of speed (m·min -1 ) and acceleration (m·s -2 ) were calculated. Following log transformation of the maximal means, intercept and slopes were calculated. Linear mixed models identified differences between positional groups for match loads, and intercept and slopes. Effects were described using standardized effect sizes (ESs) and magnitude-based decisions. There were no substantial and unclear differences between positional groups for match loads (ES range; ±confidence limits = 0.10-0.80; ±0.30-4.30) and for intercept and slopes (ES range; 0.04-0.44; ±0.52-2.11). Large within-athlete variation in match demands between rounds was observed ( z -score up to -1.8 SD for distance), and the maximal means for speed and acceleration demonstrate the extensive physical demands of AFLW competition. These data describe the intense and variable physical demands of AFLW competition, and further provide novel information regarding the maximal mean intensities and intercept and slopes, which should assist practitioners in planning and prescribing training in preparation for competition.

Using Small-Sided Games in Field Hockey: Can They Be Used to Reach Match Intensity?

ABSTRACT: Duthie, GM, Thomas, EJ, Bahnisch, J, Thornton, HR, and Ball, K. Using small-sided games in field hockey: Can they be used to reach match intensity? J Strength Cond Res 36(2): 498-502, 2022-Small-sided games (SSGs) are commonly used in field hockey to replicate or overload physical and tactical competition demands; however, little evidence is available regarding if specific SSG formats achieve this. This research investigated how speed and acceleration differed between 5-minute SSG formats (2v2, 3v3, and 4v4) and also compared with competition. Elite male field hockey athletes (n = 10) participated in the SSGs with standard rules, on pitches of 30 × 20, 35 × 25, and 40 × 30 m, respectively (∼150 m2 per athlete excluding goal keepers). Global Positioning System devices measured speed (m·min-1) and acceleration (m·s-2). Differences between mean speed and acceleration during SSGs and 5-minute maximal mean values from competition (calculated using moving averages) were quantified using linear mixed models and described using standardized effect sizes (ES) and 90% confidence intervals. Between SSG formats, there were nonsubstantial differences for mean speed and acceleration (ES range -0.4 to 0.8). Compared with competition, mean speed was substantially lower for all SSG formats (ES range -1.4 to -1.8), whereas mean acceleration was higher (ES range 3.9-4.8). The SSG formats examined had a lower mean speed and higher mean acceleration than the maximal mean observed in competition. Therefore, these SSGs are an effective training drill for the development and overload of acceleration. However, manipulating SSG constraints to expose athletes to the maximal mean competition speed is required.

The Distribution of Match Activities Relative to the Maximal Mean Intensities in Professional Rugby League and Australian Football.

ABSTRACT: Johnston, RD, Thornton, HR, Wade, JA, Devlin, P, and Duthie, GM. The distribution of match activities relative to the maximal mean intensities in professional rugby league and Australian football. J Strength Cond Res 36(5): 1360-1366, 2022-This study determined the distribution of distance, impulse, and accelerometer load accumulated at intensities relative to the maximal mean 1-minute peak intensity within professional rugby league and Australian football. Within 26 rugby league (n = 24 athletes) and 18 Australian football (n = 38 athletes) games, athletes wore global navigation satellite system devices (n = 608 match files). One-minute maximal mean values were calculated for each athlete per game for speed (m·minP-1P), accelerometer load (AU·minP-1P), and acceleration (m·sP-2P). Volumes for each parameter were calculated by multiplying by time, specifying total distance, accelerometer load, and impulse. The distribution of intensity of which these variables were performed relative to the maximal mean was calculated, with percentages ranging from 0-110%, separated into 10% thresholds. Linear mixed models determined whether the distribution of activities within each threshold varied, and positional differences. Effects were described using standardized effect sizes (ESs), and magnitude-based decisions. Across both sports, the distribution of activity (%) largely reduced the closer to the maximal mean 1-minute peak and was highest at ∼60% of the maximal mean peak. When compared with Australian football, a higher percentage of total distance was accumulated at higher intensities (70-80% and 100-110%) for rugby league (ES range = 0.82-0.87), with similar, yet larger differences for accelerometer load >80% (0.78-1.07) and impulse >60% (1.00-2.26). These findings provide information of the volume of activities performed relative to the mean maximal 1-minute peak period, which may assist in the prescription of training.

Uphill sprinting load- and force-velocity profiling: Assessment and potential applications.

This study aimed to quantify the validity and reliability of load-velocity (LV) relationship of hill sprinting using a range of different hill gradients and to describe the effect of hill gradient on sprint performance. Twenty-four collegiate-level athletes performed a series of maximal sprints on either flat terrain or hills of gradients 5.2, 8.8 and 17.6%. Velocity-time curves were recorded using a radar device. LV relationships were established using the maximal velocity achieved in each sprinting condition, whilst force-velocity-power (FVP) profiles were established using only the flat terrain sprint. LV profiles were shown to be valid (R2 = 0.99) and reliable (TE < 4.4%). For every 1-degree increase in slope, subjects' velocity decreased by 1.7 ± 0.1% on average. All the slopes used represented low resistance relative to the entire LV spectrum (<25% velocity loss). Subjects who exhibited greater horizontal force output at higher velocities on flat terrain were most affected by the gradient of the hill. Hills of gradients up to 17.6% do not provide sufficient resistance to optimize power development. However, such hills could be used to develop late-stage technical ability, due to the prolonged horizontally oriented body position that occurs as subjects attempt to overcome the acceleration due to gravity.

The Quantification of Acceleration Events in Elite Team Sport: a Systematic Review.

BACKGROUND: Wearable tracking devices are commonly utilised to quantify the external acceleration load of team sport athletes during training and competition. The ability to accelerate is an important attribute for athletes in many team sports. However, there are many different acceleration metrics that exist in team sport research. This review aimed to provide researchers and practitioners with a clear reporting framework on acceleration variables by outlining the different metrics and calculation processes that have been adopted to quantify acceleration loads in team sport research. METHODS: A systematic review of three electronic databases (CINAHL, MEDLINE, SPORTDiscus), was performed to identify peer-reviewed studies that published external acceleration load in elite team sports during training and/or competition. Articles published between January 2010 and April 2020 were identified using Boolean search phrases in relation to team sports (population), acceleration/deceleration (comparators), and competition and/or training (outcome). The included studies were required to present external acceleration and/or deceleration load (of any magnitude) from able-bodied athletes (mean age ≥ 18 years) via wearable technologies. RESULTS: A total of 124 research articles qualified for inclusion. In total, 113/124 studies utilised GPS/GNSS technology to outline the external acceleration load of athletes. Count-based metrics of acceleration were predominant of all metrics in this review (72%). There was a lack of information surrounding the calculation process of acceleration with 13% of studies specifying the filter used in the processing of athlete data, whilst 32% outlined the minimum effort duration (MED). Markers of GPS/GNSS data quality, including horizontal dilution of precision (HDOP) and the average number of satellites connected, were outlined in 24% and 27% of studies respectively. CONCLUSIONS: Team sport research has predominantly quantified external acceleration load in training and competition with count-based metrics. Despite the influence of data filtering processes and MEDs upon acceleration, this information is largely omitted from team sport research. Future research that outlines acceleration load should present filtering processes, MEDs, HDOP, and the number of connected satellites. For GPS/GNSS systems, satellite planning tools should document evidence of available satellites for data collection to analyse tracking device performance. The development of a consistent acceleration filtering method should be established to promote consistency in the research of external athlete acceleration loads.

Quantifying Mean Peak Running Intensities in Elite Field Hockey.

ABSTRACT: Delves, RIM, Bahnisch, J, Ball, K, and Duthie, GM. Quantifying mean peak running intensities in elite field hockey. J Strength Cond Res 35(9): 2604-2610, 2021-To replicate match demands in training, field hockey (FH) coaches typically prescribe intensities based on whole-match data. Such data may underestimate peak competition periods, potentially underpreparing athletes for competition. This study then aimed to quantify maximal mean running intensities during elite FH competition to facilitate enhanced training prescription. Ten-Hertz Global Positioning System data were collected from 17 male and 11 female FH athletes who competed in the 2016 and 2017 Australian Hockey League tournaments. Maximal mean values for speed, acceleration, and metabolic power (Pmet) were calculated over a 1- to 10-minute moving average by position. Summary match statistics were also analyzed. Linear mixed models were constructed to determine the effect of position on moving average and summary variables. Pairwise comparisons between groups were made using magnitude-based inferences. In female competition, speed and Pmet intensities were greater in midfielders, whereas defenders were lowest in acceleration demands over the 10-minute window and in corresponding intercepts. In male competition, acceleration was greater in defenders during the 10-minute window and in subsequent intercepts compared with midfielders, whereas defenders were lowest in speed intercepts. In comparison with previously reported summary match variables, intensities from the 1-minute moving average interval were 50-65% greater in male competition and 30-50% greater in female competition. The 10-minute moving average framework has identified FH running intensities that are greater than previously reported whole-match averages. This information enhances the understanding of the demands of FH, assisting practitioners to prepare their athletes for the most demanding instances of play.

Relationship Between Physical Performance Testing Results and Peak Running Intensity During Professional Rugby League Match Play.

Duthie, GM, Thornton, HR, Delaney, JA, McMahon, JT, and Benton, DT. Relationship between physical performance testing results and peak running intensity during professional rugby league match play. J Strength Cond Res 34(12): 3506-3513, 2020-The purpose of this study was to examine the relationship between individual athletes' physical characteristics and both the peak running intensities and the decline in peak running intensities during competition. Twenty-two professional rugby league athletes (age; 24.1 ± 4.0 years, body mass; 101.4 ± 9.5 kg) underwent a series of physical testing procedures. Peak running intensity was determined using a moving average technique, applied to the speed (m·min), acceleration/deceleration (m·s), and metabolic power (W·kg) during competition, across 10 different durations. The power law relationship was then established, yielding an intercept and slope for the movement variables. Mixed linear models were then used to determine the relationship between physical characteristics and intercept and slope values. There were large, positive relationships between a player's maximal speed and both peak running speeds (effect size = 0.56, 90% confidence interval: 0.20-0.78) and metabolic power (0.57, 0.21-0.79) during competition. By contrast, there were large, negative associations between maximal speed and the rate of decline in running speed (-0.60, -0.81 to -0.27) and metabolic power (-0.65, -0.83 to -0.32) during competition. Similarly, there were negative associations between relative squat strength and the rate of decline in running speed (moderate: -0.41, -0.69 to -0.04) and metabolic power (large: -0.53, -0.77 to -0.17) during competition. The findings of this study demonstrate that a players running intensity during competition is underpinned by the individual athletes physiological qualities. Athletes demonstrating higher maximal speeds in testing were able to maintain higher running intensities over short durations but had a greater decrease in running intensity as duration increased.

There Is Little Difference in the Peak Movement Demands of Professional and Semi-Professional Rugby League Competition.

Previous research has quantified the peak movement demands of elite rugby league match-play, but the peak accelerometer load or the semi-professional peak demands remain unknown. The aim of this research was to determine the peak movement demands of professional and semi-professional rugby league competition. Wearable microtechnology devices tracked the physical activity profiles of players during 26 professional (n = 351 files) and 22 semi-professional (n = 267 files) matches. Following each match, data were exported in raw form to extract the peak 1- to 10-min periods for speed, average acceleration, and accelerometer load of each player, using a rolling average method. To determine the difference between playing levels (professional vs. semi-professional) and position (forwards vs. backs), linear mixed models were used. The intercept and the slope were calculated based on the power law relationship to provide the peak, and rate of decay, of each dependent variable. Cohen's effect size (ES) statistic was used to determine the magnitude of differences between positions and playing level. There was little difference between playing standards, with only small differences in running speed, with a greater intercept and slope for the professional forwards compared with semi-professional forwards (intercept ES: 0.37; 90%CL: 0.19 to 0.55; slope ES: 0.35; 0.15 to 0.55). For positional comparisons (forwards vs. backs), there was no difference in running speeds at the professional level, but there was substantially greater running speed for backs compared to forwards in semi-professional competition, with small to moderate differences (ES range: 0.60-0.39). Both professional and semi-professional forwards showed small to moderately higher accelerometer load compared to backs, which increased with period duration (ES range: 0.22-0.79). Similarly, acceleration demands were greater for forwards compared to backs across both playing standards, with moderate to large differences (ES range: 0.52-0.96). Overall, the results of this study show that there is a small difference in the peak running speed for forwards in professional competition, but otherwise there are no meaningful differences in movement demands of professional and semi-professional rugby league match-play. Forwards display greater acceleration and accelerometer load across a number of rolling average durations compared to backs.

The Validity of a Global Navigation Satellite System for Quantifying Small-Area Team-Sport Movements.

Delaney, JA, Wileman, TM, Perry, NJ, Thornton, HR, Moresi, MP, and Duthie, GM. The validity of a global navigation satellite system for quantifying small-area team-sport movements. J Strength Cond Res 33(6): 1463-1466, 2019-The recent development of global navigation satellite systems (GNSS) has improved the availability and signal strength of surrounding satellites compared with traditional global positioning systems, although their ability to quantify rapid changes in speed may still be limited. This study aimed to evaluate the validity of GNSS to quantify the mean speed (m·s) and acceleration (m·s) of movements typical to team sports. One participant completed 9 periods of 4 minutes of activity, separated by 2-minute rest periods, which involved walking, jogging, and running in a variety of directions and patterns, aimed to simulate a team-sport movement profile. Speed and acceleration were quantified from a 10-Hz GNSS unit and compared with a 10-camera, 3-dimensional motion capture system (VICON), from which the movement of both the participant's center of mass (COM) and the location of the GNSS unit (e.g., C7 vertebrae) were calculated. Practical estimates of speed were associated with small differences from both the criterion COM (effect size; ±90% confidence limits = 0.19-0.25; ± ∼0.21) and criterion C7 (0.14-0.22; ± ∼0.13). The corresponding estimates of acceleration derived from raw data were classified as small (0.16-0.22; ± ∼0.15) and small to moderate (0.25-0.35; ± ∼0.24) for the COM and C7, respectively. Software-exported acceleration values exhibited very large mean bias compared with both criterion measures (-3.81 to -3.77; ± ∼0.24). This study demonstrates that 10-Hz GNSS possess acceptable validity for assessing the average demands of movements typical of team-sports training and competition, although caution is recommended when using software-exported measures of acceleration.

Developing Athlete Monitoring Systems in Team Sports: Data Analysis and Visualization.

In professional team sports, the collection and analysis of athlete-monitoring data are common practice, with the aim of assessing fatigue and subsequent adaptation responses, examining performance potential, and minimizing the risk of injury and/or illness. Athlete-monitoring systems should be underpinned by appropriate data analysis and interpretation, to enable the rapid reporting of simple and scientifically valid feedback. Using the correct scientific and statistical approaches can improve the confidence of decisions made from athlete-monitoring data. However, little research has discussed and proposed an outline of the process involved in the planning, development, analysis, and interpretation of athlete-monitoring systems. This review discusses a range of methods often employed to analyze athlete-monitoring data to facilitate and inform decision-making processes. There is a wide range of analytical methods and tools that practitioners may employ in athlete-monitoring systems, as well as several factors that should be considered when collecting these data, methods of determining meaningful changes, and various data-visualization approaches. Underpinning a successful athlete-monitoring system is the ability of practitioners to communicate and present important information to coaches, ultimately resulting in enhanced athletic performance.

Interunit Reliability and Effect of Data-Processing Methods of Global Positioning Systems.

PURPOSE: To establish the interunit reliability of a range of global positioning system (GPS)-derived movement indicators, to determine the variation between manufacturers, and to investigate the difference between software-derived and raw data. METHODS: A range of movement variables were obtained from 27 GPS units from 3 manufacturers (GPSports EVO, 10 Hz, n = 10; STATSports Apex, 10 Hz, n = 10; and Catapult S5, 10 Hz, n = 7) that measured the same team-sport simulation session while positioned on a sled. The interunit reliability was determined using the coefficient of variation (%) and 90% confidence limits, whereas between-manufacturers comparisons and comparisons of software versus raw processed data were established using standardized effect sizes and 90% confidence limits. RESULTS: The interunit reliability for both software and raw processed data ranged from good to poor (coefficient of variation = 0.2%; ±1.5% to 78.2%; ±1.5%), with distance, speed, and maximal speed exhibiting the best reliability. There were substantial differences between manufacturers, particularly for threshold-based acceleration and deceleration variables (effect sizes; ±90% confidence limits: -2.0; ±0.1 to 1.9; ±0.1), and there were substantial differences between data-processing methods for a range of movement indicators. CONCLUSIONS: The interunit reliability of most movement indicators was deemed as good regardless of processing method, suggesting that practitioners can have confidence within systems. Standardized data-processing methods are recommended, due to the large differences between data outputs from various manufacturer-derived software.

Running Intensities in Elite Youth Soccer by Age and Position.

Duthie, GM, Thornton, HR, Delaney, JA, Connolly, DR, and Serpiello, FR. Running intensities in elite youth soccer by age and position. J Strength Cond Res 32(10): 2918-2924, 2018-The purpose of this investigation was to examine differences between the peak running speed, acceleration, and metabolic power of elite youth soccer across a range of age levels by position. Ninety-six elite junior soccer players were assessed between 2015 and 2017. Ninety-six elite junior soccer players (at time of match: age, 15.8 ± 0.9 years; body mass, 69.1 ± 8.0 kg) were assessed during 61 games within the 2015, 2016, and 2017 season, for a total of 441 individual match observations (4.8 ± 3.3 matches per player, range 1-13). Participants were classified by age group: under 15 (U15, n = 121, 14.7 ± 0.3 years), under 16 (U16, n = 176, 15.8 ± 0.3 years), or under 17 (U17, n = 144, 16.7 ± 0.4 years), and according to their playing position: Attacker (ATT), Defender (DEF), Mid-Fielder (MID), or Wide (WIDE). Participants wore global positioning system units during each match, where speed (m·min), acceleration/deceleration (m·s), and metabolic power (Pmet) were established. A 1- to 10-minute moving average was applied to establish the intercept (c) and slope (n) of running intensity variables as a power law y = cx relationship. Linear mixed models were used to examine differences in the intercept and slope between age group and player position. There were no substantial differences in peak (intercept) or decline (slope) in running intensity between playing levels. Several differences were observed in the peak running speeds (m·min), particularly peak running speeds of ATT and DEF being substantially lower than the MID. Despite variability between positions, we suggest that the magnitude of these differences would not warrant the prescription of different running intensities across positions at the elite junior level. These findings describe the peak running intensities of elite junior soccer, useful in the monitoring and prescription of training to ensure that players are prepared for the most demanding periods of competition.

Gradual vs. Maximal Acceleration: Their Influence on the Prescription of Maximal Speed Sprinting in Team Sport Athletes.

The primary purpose of this study was to determine if a difference existed between peak speed attained when performing a sprint with maximal acceleration versus from a gradual build-up. Additionally, this investigation sought to compare the actual peak speed achieved when instructed to reach 75% and 90% of maximum speed. Field sport athletes (n = 21) performed sprints over 60 m under the experimental conditions, and the peak speed was assessed with a radar gun. The gradual build-up to maximum speed (8.30 ± 0.40 m∙s-1) produced the greater peak speed (effect size = 0.3, small) than the maximum acceleration run (8.18 ± 0.40 m∙s-1), and the majority of participants (62%) followed this pattern. For the sub-maximum runs, the actual mean percentage of maximum speed reached was 78 ± 6% for the 75% prescribed run and 89 ± 5% for the 90% prescription. The errors in attaining the prescribed peak speeds were large (~15%) for certain individuals, especially for the 75% trial. Sprint training for maximum speed should be performed with a gradual build-up of speed rather than a maximum acceleration. For sub-maximum interval training, the ability to attain the prescribed target peak speed can be challenging for field sport athletes, and therefore where possible, feedback on peak speeds reached should be provided after each repetition.

The Occurrence of Repeated High Acceleration Ability (RHAA) in Elite Youth Football.

The aim of the present study was to investigate the occurrence of Repeated High-Acceleration Ability (RHAA) bouts in elite youth football games using 10-Hz GPS devices and two relative thresholds derived from players' actual maximal acceleration. Thirty-six outfield soccer players (age 14.9±0.6 years) participated in the study. Players wore 10-Hz GPS units during 41 official games. High accelerations were defined as efforts commencing above a threshold corresponding to 70% (T70%) or 80% (T80%) of the average 5-m acceleration obtained during a 40-m sprint test; RHAA bouts were defined as ≥3 efforts with ≤45 s recovery between efforts. Results were analysed via generalised linear mixed model and magnitude-based inferential statistics. On average, 8.0±4.6 and 5.1±3.5 bouts were detected in an entire game using T70% and T80%, respectively. When all positions were analysed together, there was a very-likely small difference in the number of RHAA bouts between first and second half for T70% and T80%, respectively. RHAA bouts occur frequently in elite youth football, with small differences between halves and between playing positions within the first or second half in most variables assessed.

Differences Between Relative and Absolute Speed and Metabolic Thresholds in Rugby League.

PURPOSE: To compare relative and absolute speed and metabolic thresholds for quantifying match output in elite rugby league. METHODS: Twenty-six professional players competing in the National Rugby League were monitored with global positioning systems (GPS) across a rugby-league season. Absolute speed (moderate-intensity running [MIRTh > 3.6 m/s] and high-intensity running [HIRTh > 5.2 m/s]) and metabolic (>20 W/kg) thresholds were compared with individualized ventilatory (first [VT1IFT] and second [VT2IFT]) thresholds estimated from the 30-15 Intermittent Fitness Test (30-15IFT), as well as the metabolic threshold associated with VT2IFT (HPmetVT2), to examine difference in match-play demands. RESULTS: VT2IFT mean values represent 146%, 138%, 167%, and 144% increases in the HIR dose across adjustables, edge forwards, middle forwards, and outside backs, respectively. Distance covered above VT2IFT was almost certainly greater (ES range = 0.79-1.03) than absolute thresholds across all positions. Trivial to small differences were observed between VT1IFT and MIRTh, while small to moderate differences were reported between HPmetVT2 and HPmetTh. CONCLUSIONS: These results reveal that the speed at which players begin to run at higher intensities depends on individual capacities and attributes. As such, using absolute HIR speed thresholds underestimates the physical HIR load. Moreover, absolute MIR and high metabolic thresholds may over- or underestimate the work undertaken above these thresholds depending on the respective fitness of the individual. Therefore, using relative thresholds enables better prescription and monitoring of external training loads based on measured individual physical capacities.

Effects of Preseason Training on the Sleep Characteristics of Professional Rugby League Players.

PURPOSE: To investigate the influence of daily and exponentially weighted moving training loads on subsequent nighttime sleep. METHODS: Sleep of 14 professional rugby league athletes competing in the National Rugby League was recorded using wristwatch actigraphy. Physical demands were quantified using GPS technology, including total distance, high-speed distance, acceleration/deceleration load (SumAccDec; AU), and session rating of perceived exertion (AU). Linear mixed models determined effects of acute (daily) and subacute (3- and 7-d) exponentially weighted moving averages (EWMA) on sleep. RESULTS: Higher daily SumAccDec was associated with increased sleep efficiency (effect-size correlation; ES = 0.15; ±0.09) and sleep duration (ES = 0.12; ±0.09). Greater 3-d EWMA SumAccDec was associated with increased sleep efficiency (ES = 0.14; ±0.09) and an earlier bedtime (ES = 0.14; ±0.09). An increase in 7-d EWMA SumAccDec was associated with heightened sleep efficiency (ES = 0.15; ±0.09) and earlier bedtimes (ES = 0.15; ±0.09). CONCLUSIONS: The direction of the associations between training loads and sleep varied, but the strongest relationships showed that higher training loads increased various measures of sleep. Practitioners should be aware of the increased requirement for sleep during intensified training periods, using this information in the planning and implementation of training and individualized recovery modalities.

Importance, Reliability, and Usefulness of Acceleration Measures in Team Sports.

Delaney, JA, Cummins, CJ, Thornton, HR, and Duthie, GM. Importance, reliability and usefulness of acceleration measures in team sports. J Strength Cond Res 32(12): 3494-3502, 2018-The ability to accelerate, decelerate, and change direction efficiently is imperative to successful team sports performance. Traditional intensity-based thresholds for acceleration and deceleration may be inappropriate for time-series data and have been shown to exhibit poor reliability, suggesting other techniques may be preferable. This study assessed movement data from one professional rugby league team throughout 2 full seasons and 1 preseason period. Using both 5 and 10 Hz global positioning systems (GPS) units, a range of acceleration-based variables were evaluated for their interunit reliability, ability to discriminate between positions, and associations with perceived muscle soreness. The reliability of 5 Hz global positioning systems for measuring acceleration and deceleration ranged from good to poor (CV = 3.7-27.1%), with the exception of high-intensity deceleration efforts (CV = 11.1-11.8%), the 10 Hz units exhibited moderate-to-good interunit reliability (CV = 1.2-6.9%). Reliability of average metrics (average acceleration/deceleration, average acceleration, and average deceleration) ranged from good to moderate (CV = 1.2-6.5%). Substantial differences were detected between positions using time spent accelerating and decelerating for all magnitudes, but these differences were less clear when considering the count or distance above acceleration/deceleration thresholds. All average metrics detected substantial differences between positions. All measures were similarly related to perceived muscle soreness, with the exception of high-intensity acceleration and deceleration counts. This study has proposed that averaging the acceleration/deceleration demands over an activity may be a more appropriate method compared with threshold-based methods, because a greater reliability between units, while not sacrificing sensitivity to within-subject and between-subject changes.

Duration-specific running intensities of Australian Football match-play.

OBJECTIVES: To establish the position and duration-specific running demands of Australian Football (AF) competition for the prescription and monitoring of specific training drills. DESIGN: An observational time-motion analysis was performed on 40 professional AF players during 30 games throughout the 2014-15 competitive seasons. METHODS: Player movements were collected and peak values were calculated for moving averages of between 1-10min in duration for relative distance (mmin-1), high-speed relative distance (HSmmin-1), average acceleration/deceleration (ms2) and metabolic power (Pmet). A mixed-model analysis was used to detect positional differences, and differences were described using a magnitude-based network. RESULTS: Relative distance was likely greater for midfielders (MID), and mobile forwards (MF) compared to tall backs (TB) across all moving average durations assessed, with MF peaking at 223±35mmin-1 for a 1-min window. High-speed relative distance was at least likely to be greater for MF compared to all other positions, across all moving average durations (ES=0.27-0.94). Acceleration/deceleration demands were similar across positions. CONCLUSIONS: The present study demonstrated that the peak running intensities of AF are well above previously reported peak intensities when considering the distance-based running requirements of match-play. Whilst the acceleration-based metric was unable to detect large differences between positions, it is important to note their contribution to the overall competition demands. This study presents a useful framework for the prescription and monitoring of drills specific to AF competition requirements.