Duration-specific running intensities of Australian Football match-play

Lateral End-Range Movement Profile and Shot Effectiveness During Grand Slam Tennis Match-Play

End-range movements are among the most demanding but least understood in the sport of tennis. Using male Hawk-Eye data from match-play during the 2021-2023 Australian Open tournaments, we evaluated the speed, deceleration, acceleration, and shot quality characteristics of these types of movement in men's Grand Slam tennis. Lateral end-range movements that incorporated a change of direction (CoD) were identified for analysis using k-means (end-range) and random forest (CoD) machine learning models. Peak speed, average deceleration into the CoD, average reacceleration out of the CoD, and the quality of the shot played were computed. Players were grouped based on their ATP rankings (top 10, top 50, and outside top 50) to examine the influence of ranking on movement profiles and shot effectiveness. Our data showed that end-range movements profiles of top 10 and top 50 players were characterized by higher peak speed (d = 0.3-0.88), deceleration intensity (d = 0.25-0.63), and acceleration intensity (d = 0.06-0.51) when compared to players outside the top 50 (p < 0.05). Top 10 players also demonstrated greater peak speeds (d = 0.59) and acceleration intensities (d = 0.45) compared to top 50 players (p < 0.05). There was a nonlinear inverse relationship between peak speed and shot quality, such that, as peak speed increased, shot quality decreased-notwithstanding that top 10 players were more likely to hit high-quality shots at higher peak speeds. These results quantify the discrete kinematic characteristics of the sport's most challenging movement sequence and reveal, for the first time, that higher ranked players may possess superior movement potential on court.

A framework for player movement analysis in team sports

Player movement is a fundamental component of evaluating performance in most team sports. Movement can be evaluated across multiple scales, referring to the function of anatomical structures through various planes of motion or an individual regulating their field position based on the movement of opposition players. Developments in commercially available tracking systems have afforded end users the ability to investigate the spatiotemporal features of movement in fine detail. These advancements, in conjunction with overlaid contextual information, have provided insights into the strategies adopted by players in relation to their movement. Understanding movement beyond its semantic value allows practitioners to make informed decisions surrounding performance evaluation and training design. This investigation proposes a framework to guide the analysis of player movement within team sports environments. The framework describes how operational standards for assessing movement can be designed in reference to theory and a set training philosophy. Such practice allows for the spatial and temporal complexities within team sports to be described and could potentially lead to better-applied outcomes through greater interdisciplinary collaboration and an improved holistic understanding of movement. To inform its development, this study evaluates the current research and identifies several open questions to guide future investigations.

Contextual factors associated with running demands in elite Australian football: a scoping review

OBJECTIVES

To identify and summarise the contextual factors associated with running demands in elite male Australian football (AF) gameplay that have been reported in the literature.

DESIGN

Scoping review.

METHODS

A contextual factor in sporting gameplay is a variable associated with the interpretation of results, yet is not the primary objective of gameplay. Systematic literature searches were performed in four databases to identify what contextual factors associated with running demands in elite male AF have been reported: Scopus, SPORTDiscus, Ovid Medline and CINAHL, for terms constructed around Australian football AND running demands AND contextual factors. The present scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), and narrative synthesis was conducted.

RESULTS AND CONCLUSION

A total of 36 unique articles were identified by the systematic literature search, which included 20 unique contextual factors. The most studied contextual factors were position (n = 13), time in game (n = 9), phases of play (n = 8), rotations (n = 7) and player rank (n = 6). Multiple contextual factors, such as playing position, aerobic fitness, rotations, time within a game, stoppages, and season phase appear to correlate with running demands in elite male AF. Many identified contextual factors have very limited published evidence and thus additional studies would help draw stronger conclusions.

Match Running Performance in Australian Football Is Related to Muscle Fiber Typology

PURPOSE

To examine the association between muscle fiber typology and match running performance in professional Australian football (AF) athletes.

METHODS

An observational time-motion analysis was performed on 23 professional AF athletes during 224 games throughout the 2020 competitive season. Athletes were categorized by position as hybrid, small, or tall. Athlete running performance was measured using Global Navigation Satellite System devices. Mean total match running performance and maximal mean intensity values were calculated for moving mean durations between 1 and 10 minutes for speed (in meters per minute), high-speed-running distance (HSR, >4.17 m·s-1), and acceleration (in meters per second squared), while intercept and slopes were calculated using power law. Carnosine content was quantified by proton magnetic resonance spectroscopy in the gastrocnemius and soleus and expressed as a carnosine aggregate z score (CAZ score) to estimate muscle fiber typology. Mixed linear models were used to determine the association between CAZ score and running performance.

RESULTS

The mean (range) CAZ score was -0.60 (-1.89 to 1.25), indicating that most athletes possessed a greater estimated proportion of type I muscle fibers. A greater estimated proportion of type I fibers (ie, lower CAZ score) was associated with a larger accumulation of HSR (>4.17 m·s-1) and an increased ability to maintain HSR as the peak period duration increased.

CONCLUSION

AF athletes with a greater estimated proportion of type I muscle fibers were associated with a greater capacity to accumulate distance running at high speeds, as well as a greater capacity to maintain higher output of HSR running during peak periods as duration increases.

Factors Affecting Physical and Technical Performance in Australian Football

ABSTRACT

Wing, C, Hart, NH, Ma'ayah, F, and Nosaka, K. Factors affecting physical and technical performance in Australian football. J Strength Cond Res 37(9): 1844-1851, 2023-This study assessed player (i.e., lower-body strength and power and aerobic fitness) and environmental (e.g., venue) factors and their effects on the physical (e.g., distance) and technical (e.g., kicks) demands of Australian football (AF). Relative distance, high-speed running (HSR), and acceleration efforts for 19 matches by 33 players in a West AF League team were analyzed from global positioning system data split into periods of successful offense and defense and maximum ball in play (BiP) periods, as well as technical actions. Lower-body strength and power, and aerobic fitness were evaluated using a one-repetition trap-bar deadlift, countermovement jump, 2-km time trial, and Yo-Yo intermittent fitness test, respectively. In matches played at home, distance (p < 0.001, ES = 0.39) and HSR (p < 0.001, ES = 0.34) were significantly reduced during successful defense. In addition, tackle rate was significantly increased (p = 0.003, ES = 0.16) during successful defense when playing at home. Trap-bar deadlift relative to mass significantly increased relative distance (p = 0.004, ES = 0.51) and HSR (p = 0.029, ES = 0.40) in successful offense. In successful defense, superior time trial performance significantly increased relative distance (p < 0.001, ES = 0.58), HSR (p < 0.001, ES = 0.59), and acceleration efforts (p = 0.017, ES = 0.44), while relative distance (p < 0.001, ES = 0.62) and HSR (p = 0.004, ES = 0.52) were also increased during maximum BiP periods. The results demonstrate that player factors have the largest effect on the physical and technical performance of AF players.

Position-Specific Running and Technical Demands During Male Elite-Junior and Elite-Senior Australian Rules Football Match-Play

ABSTRACT

Jennings, J, Štaka, Z, Wundersitz, DW, Sullivan, CJ, Cousins, SD, Čustović, E, and Kingsley, MI. Position-specific running and technical demands during male elite-junior and elite-senior Australian rules football match-play. J Strength Cond Res 37(7): 1449-1455, 2023-The aim of this study was to compare position-specific running and technical demands of elite-junior and elite-senior Australian rules football match-play to better inform practice and assist transition between the levels. Global positioning system and technical involvement data were collated from 12 Victorian U18 male NAB League ( n = 553) and 18 Australian Football League ( n = 702) teams competing in their respective 2019 seasons. Players were grouped by position as nomadic, fixed, or ruck, and data subsets were used for specific analyses. Relative total distance ( p = 0.635, trivial effect), high-speed running (HSR) distance ( p = 0.433, trivial effect), acceleration efforts ( p = 0.830, trivial effect), deceleration efforts ( p = 0.983, trivial effect), and efforts at >150 m·min -1 ( p = 0.229, trivial effect) and >200 m·min -1 ( p = 0.962, trivial effect) did not differ between elite-junior and elite-senior match-play. Elite juniors covered less total and HSR distance during peak periods (5 seconds-10 minutes) of demand ( p ≤ 0.022, small-moderate effects). Within both leagues, nomadic players had the greatest running demands followed by fixed position and then rucks. Relative disposals ( p = 0.330, trivial effect) and possessions ( p = 0.084, trivial effect) were comparable between the leagues. During peak periods (10 seconds to 2 minutes), elite juniors had less technical involvements than elite seniors ( p ≤ 0.001, small effects). Although relative running demands and positional differences were comparable between the leagues, elite juniors perform less running, HSR, and technical involvements during peak periods when compared with elite seniors. Therefore, coaching staff in elite-senior clubs should maintain intensity while progressively increasing the volume of training that recently drafted players undertake when they have transitioned from elite-junior leagues.

Replicating Maximum Periods of Play in Australian Football Matches Through Position-Specific Drills

ABSTRACT

Wing, C, Hart, NH, Ma'ayah, F, and Nosaka, K. Replicating maximum periods of play in Australian football matches through position-specific drills. J Strength Cond Res XX(X): 000-000, 2022-This study evaluated whether a position-specific drill replicates the running intensities of maximum ball in play (BiP) phases in competitive matches of Australian football (AF). Match data were collected on 32 AF players across 3 seasons (2019, 2020, 2021), with training session data collected from the same players across the 2021 season. Three position-specific training drills were created for defense, offense, and combination (defense and offense combined). Running intensities were compared between maximum BiP periods (e.g., periods with the highest metric per minute) from competitive matches and position-specific training drills, as well as between the 3 position-specific training drills using linear mixed models. The significance level was set at p < 0.05. Measures of distance (offense: 44.4 m·minute-1, defense: 83.5 m·minute-1, combination: 50.4 m·minute-1), high-speed running (offense: 76.7 m·minute-1, defense: 134.6 m·minute-1, combination: 89.6 m·minute-1), very high-speed running (offense: 26.7 m·minute-1, defense: 56.2 m·minute-1, combination: 55.0 m·minute-1), and high-intensity efforts (offense: 2.3 efforts·minute-1, defense: 3.0 efforts·minute-1, combination: 2.8 efforts·minute-1), relative to time were greater (p < 0.001) in all 3 position-specific training drills compared with BiP phases. All measured metrics were significantly (p < 0.001) greater in the defense drill compared with the offense drill, whereas distance, high-speed running, PlayerLoad, and accelerations were significantly (p < 0.001) greater when compared with the combination drill. These demonstrate that position-specific training drills that we created replicated or exceeded the running intensities recorded during matches based on maximum BiP periods. Position-specific training drills seem to be an attractive addition to AF players training regimens because it concurrently provides training for physical and technical actions (e.g., handballs).

Phases of Match-Play in Professional Australian Football: Positional Demands and Match-Related Fatigue

This study examined the influence of player position and match quarter on activity profiles during the phases of play in Australian Football. Global positioning satellite data was collected for one season from an Australian Football League team for nomadic, key position and ruck players (age: 24.8 ± 4.2 years, body mass: 88.3 ± 8.7 kg, height: 1.88 ± 0.8 m). Separate linear mixed models and effect sizes were used to analyse differences between positions and game quarter within each phase of play for values of distance, speed and metabolic power indices. There were clear differences between positions for low-speed running, high-speed running, total distance and average speed. Nomadic players generally recorded the highest match running outputs, followed by key position players and ruckmen. Within each position, offence and defence involved the highest intensities, followed by contested play and then stoppage periods. Across the four quarters, there were small to large reductions in average speed, high-speed running, high power and energy expenditure during offence, defence and contested play, but not during stoppages. Accordingly, conditioning staff should consider the intermittent intensities of the phases of match-play for each position to optimally prepare players for competition. Reductions in match intensities were evident during active periods of play providing implications for real-time monitoring to optimise the timing of rotations.

The Maximal Intensity Period: Rationalising its Use in Team Sports Practice

Quantifying the highest intensity of competition (the maximal intensity period [MIP]) for varying durations in team sports has been used to identify training targets to inform the preparation of players. However, its usefulness has recently been questioned since it may still underestimate the training intensity required to produce specific physiological adaptations. Within this conceptual review, we aimed to: (i) describe the methods used to determine the MIP; (ii) compare the data obtained using MIP or whole-match analysis, considering the influence of different contextual factors; (iii) rationalise the use of the MIP in team sports practice and (iv) provide limitations and future directions in the area. Different methods are used to determine the MIP, with MIP values far greater than those derived from averaging across the whole match, although they could be affected by contextual factors that should be considered in practice. Additionally, while the MIP might be utilised during sport-specific drills, it is inappropriate to inform the intensity of interval-based, repeated sprint and linear speed training modes. Lastly, MIP does not consider any variable of internal load, a major limitation when informing training practice. In conclusion, practitioners should be aware of the potential use or misuse of the MIP.

Assessment of Physical, Technical, and Tactical Analysis in the Australian Football League: A Systematic Review

Background

Elite Australian Football (AF) match-play requires proficiency in physical, technical, and tactical elements. However, when analysing player movement practitioners commonly exclude technical and tactical considerations, failing to recognise the multifactorial nature of AF match-play and providing little context into the movement requirements of the players.

Objectives

This systematic review aimed to identify the physical, technical, and tactical requirements of the Australian Football League (AFL) and to highlight the importance of integrating data from multiple sources when analysing player output.

Methods

A systematic search of electronic databases (CINAHL, PubMed, Scopus, SPORTDiscus, and Web of Science) was conducted from January 2009 to June 2022. Keywords relating to physical, technical, and tactical match requirements were used.

Results

Forty-eight studies met the inclusion criteria. In isolation, physical requirements were the most analysed construct within the AFL (n = 17), followed by technical (n = 9) and then tactical (n = 6). Thirteen studies integrated physical and technical elements, one study integrated technical and tactical elements, one study integrated physical and tactical elements, and one study integrated all three elements. Movement analysis centred around average ‘whole’ match requirements, whereas technical and tactical match analyses focused on key performance indicators of match performance.

Conclusion

While the physical requirements of the AFL have been well documented, there is little understanding of how player technical output and various team tactics influence player movement requirements. Knowledge of how the elements of AF match-play interact with one another could enhance our understanding of match performance and provide a greater resource for training prescription.

Impact of Sudden Rule Changes on Player Injuries and Performance: Insights from Australian Football

This study investigated the effects of reduced quarter time due to COVID-19 pandemic rule changes, on running performance and injuries in Australian Football. Microsensor data for eight matches performed by the same 17 players were compared between the 2019 (standard) and 2020 (COVID-19) seasons using linear and generalised mixed models. Injury rates were assessed in 34 players across the full 2019 season, and 32 players across the full 2020 season. The total distance (ES = 1.28 [0.55 to 2.02]), high-speed (>18 km/h) (ES = 0.44 [-0.24 to 1.12]) and very highspeed (>24 km/h) (ES = 0.27 [-0.41 to 0.94]) distances, PlayerLoad™ (ES = 0.96 [0.25 to 1.67]), high-intensity efforts (ES = 0.48 [-0.20 to 1.16]), and accelerations (ES = 0.33 [-0.34 to 1.01]) were smaller (p ≤ 0.01) for the 2020 than the 2019 season. Expressed relative to playing time, distance (ES=-0.38 [-1.06 to 0.30]), PlayerLoad™ (ES = -0.27 [-0.94 to 0.41]), and acceleration efforts (ES = -0.50 [-1.18 to 0.18]) were greater (p < 0.05) for the 2020 than the 2019 season. No significant differences in maximum ball-in-play periods nor the difference between the 1^st and 4^th quarters were evident. Injury rates remained similar between 2019 (3.36 per game) and 2020 (3.55 per game). However, the proportion of injuries that led to lost time (missed games) was greater for the 2020 (38%) than 2019 season (24%). The changes in the rules had a profound impact on player performance and increased the likelihood of time loss injuries.

Techniques to derive and clean acceleration and deceleration data of athlete tracking technologies in team sports: A scoping review

The application of acceleration and deceleration data as a measure of an athlete's physical performance is common practice in team sports. Acceleration and deceleration are monitored with athlete tracking technologies during training and games to quantify training load, prevent injury and enhance performance. However, inconsistencies exist throughout the literature in the reported methodological procedures used to quantify acceleration and deceleration. The object of this review was to systematically map and provide a summary of the methodological procedures being used on acceleration and deceleration data obtained from athlete tracking technologies in team sports and describe the applications of the data. Systematic searches of multiple databases were undertaken. To be included, studies must have investigated full body acceleration and/or deceleration data of athlete tracking technologies. The search identified 276 eligible studies. Most studies (60%) did not provide information on how the data was derived and what sequence of steps were taken to clean the data. Acceleration and deceleration data were commonly applied to quantify and describe movement demands using effort metrics. This scoping review identified research gaps in the methodological procedures and deriving and cleaning techniques that warrant future research focussing on their effect on acceleration and deceleration data.

Classified metabolic power-based measures in professional football players: comparison between playing positions and match period

OBJECTIVE

The aim of this study was (i) provide reference data of metabolic power-based measures during professional football matches; and to (ii) analyze the between-position and between-halves differences of power-based measures during professional football matches.

METHODS

Forty-six professional male players from two Turkish Super League teams were observed during two seasons, and 58 matches were analyzed. Total distance, equivalent distance, Low Power (LP), Intermediate Power (IP), High Power (HP), Elevated Power (EP), Max Power (MP) and power metabolic measures Pmet at different match moments were considered.

RESULTS

Significant between-position differences were observed for IP (p: 0.000; d: 0.284), HP (p ≤ 0.001; d = 0.45), EP (p ≤ 0.001; d = 0.44), and for MP (p ≤ 0.001; d = 0.56), with the central defenders (CD) showing the lower values, and the central midfielders (CM) showing the higher values for the overall measures.

CONCLUSION

Power-based measures are dependent on playing positions. While the CD have lower Pmet values when compared to all positions, the CM have the greatest values. Training and recovery strategies must be ensured for CM players, especially those who have greater match participation.

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.

Physical and technical demands of Australian football: an analysis of maximum ball in play periods

BACKGROUND

This study compares ball in play (BiP) analyses and both whole game (WG) and quarter averaged data for physical and technical demands of sub-elite Australian football (AF) players competing in the West Australian Football League across playing positions.

METHODS

Microsensor data were collected from 33 male AF players in one club over 19 games of the 2019 season. BiP time periods and technical performance data (e.g., kicks) were acquired from the Champion Data timeline of statistics, and time matched to the microsensor data. Linear mixed modelling was utilised to establish differences between maximum BiP periods and averaged data.

RESULTS

The analyses indicated significant differences (p < 0.0001) between maximum BiP and WG data for all metrics and all playing position (half-line, key position, and midfielders). The percentage difference was greatest for very high-speed running (171-178%), accelerations (136-142%), high-intensity efforts (128-139%), and high-speed running (134-147%) compared to PlayerLoad™ (50-56%) and total running distance (56-59%). No significant (p > 0.05) differences were evident for maximum BiP periods when they were compared between playing positions (i.e., half line vs key position vs midfield). Significant (p < 0.0001) differences were also noted between maximum BiP phases and averaged data across all 4 quarters, for each microsensor metric, and all playing positions. Technical actions (e.g., kicks and handballs) were observed in 21-48% of maximum BiP phases, depending on playing positions and microsensor metric assessed, with kicks and handballs constituting > 50% of all actions performed.

CONCLUSIONS

These results show the BiP analysis method provides a more accurate assessment of the physical demands and technical actions performed by AF players, which are underestimated when using averaged data. The data presented in this study may be used to inform the design and monitoring of representative practice, ensuring that athletes are prepared for both the physical and technical demands of the most demanding passages of play.

Tracking Systems in Team Sports: A Narrative Review of Applications of the Data and Sport Specific Analysis

Seeking to obtain a competitive advantage and manage the risk of injury, team sport organisations are investing in tracking systems that can quantify training and competition characteristics. It is expected that such information can support objective decision-making for the prescription and manipulation of training load. This narrative review aims to summarise, and critically evaluate, different tracking systems and their use within team sports. The selection of systems should be dependent upon the context of the sport and needs careful consideration by practitioners. The selection of metrics requires a critical process to be able to describe, plan, monitor and evaluate training and competition characteristics of each sport. An emerging consideration for tracking systems data is the selection of suitable time analysis, such as temporal durations, peak demands or time series segmentation, whose best use depends on the temporal characteristics of the sport. Finally, examples of characteristics and the application of tracking data across seven popular team sports are presented. Practitioners working in specific team sports are advised to follow a critical thinking process, with a healthy dose of scepticism and awareness of appropriate theoretical frameworks, where possible, when creating new or selecting an existing metric to profile team sport athletes.

Possession chain factors influence movement demands in elite Australian football match-play

Contemporary analysis of physical activity in Australian Football (AF) is typically presented as a total measure and independent of game context, which is not representative of how the game is played and/or assessed by coaches. This study examines the activity profile of individual possession chains and determines the influence that field position, initial chain state, and possession phase have on these activity characteristics in men's AF.Global positioning system data were attained from 35 players in 13 matches across the 2019 Australian Football League season. Matches were coded into different possession phases, initial field location of the ball, and initial chain state. Mixed models were built to observe the influence of field position and initial chain state for each possession phase.Less TD and HSR distance were covered during attacking chains in the forward 50 and attacking midfield, while defensive chains covered less TD and HSR in the defensive 50 and defensive midfield (p < 0.001). Significant main effects for possession phase and initial chain state were observed for TD and HSR. TD and HSR were higher during attacking chains, while chains beginning from a stoppage were lower than intercept and kick-ins (p < 0.001).Overall, the most intense moments of the game appear similar across all possession phases when field location is accounted for and that transitioning the ball quickly from the defensive end of the field results in greater physical activity. These findings can be used for prescription and monitoring of training drills specific to AF requirements.

Running Performance of Male Versus Female Players in Australian Football Matches: A Systematic Review

BACKGROUND

Australian Football is a fast paced, intermittent sport, played by both male and female populations. The aim of this systematic review was to compare male and female Australian Football players, competing at elite and sub-elite levels, for running performance during Australian Football matches based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

METHODS

Medline, SPORTDiscus, and Web of Science searches, using search terms inclusive of Australian Football, movement demands and microsensor technology, returned 2535 potential manuscripts, of which 33 were included in the final analyses.

RESULTS

Results indicated that male athletes performed approximately twice the total running distances of their female counterparts, which was likely due to the differences in quarter length (male elite = 20 min, female elite = 15 min (plus time-on). When expressed relative to playing time, the differences between males and females somewhat diminished. However, high-speed running distances covered at velocities > 14.4 km·h-1 (> 4 m·s-1) were substantially greater (≥ 50%) for male than female players. Male and female players recorded similar running intensities during peak periods of play of shorter duration (e.g., around 1 min), but when the analysis window was lengthened, females showed a greater decrement in running performance.

CONCLUSION

These results suggest that male players should be exposed to greater training volumes, whereas training intensities should be reasonably comparable across male and female athletes.

Physical testing characteristics better explain draft outcome than in-game movement profile in junior elite Australian rules football players

OBJECTIVES

The aim of this study was to investigate the extent to which Australian Football League (AFL) draft outcome is associated with physical performance and/or in-game movement profile.

DESIGN

Observational cohort design.

METHODS

Physical testing results and in-game global positioning system (GPS) data were collated from Victorian-based, draft-eligible participants in the under 18 boys NAB League competition (n = 450; age = 17.1 ± 0.3 y). Players were grouped by position as nomadic, fixed-position or fixed&ruck.

RESULTS

Individually, variables that best distinguish drafted and non-drafted players were: estimated V̇O2 max (all-position, nomadic, fixed&ruck: d = 0.60, 0.64, 0.53), standing vertical jump (d = 0.57, 0.58, 0.53), running vertical jump (d = 0.52, 0.51, 0.56), AFL agility (d = 0.49, 0.44, 0.67) and 20-m speed (all-position, nomadic: d = 0.50, 0.61). Factor analysis prior to binary logistic regression assessed the probability of factors influencing position-specific draft outcome. AFL agility (all-position, fixed&ruck: OR = 4.58, 15.86), anthropometry (all-position, nomadic, fixed, fixed&ruck: OR = 2.55, 2.06, 11.41, 7.99), and jumping (all-position, nomadic, fixed&ruck: OR = 1.75, 1.69, 2.68) were the factors most associated with positive draft outcome. More game involvement (fixed&ruck: OR = 2.22), sprinting (all-position, fixed&ruck: OR = 1.45, 2.06) and less non-sprinting activities (all-position, nomadic: OR = 0.64, 0.61) were associated with positive draft outcome. The fixed&ruck model was the best performing (χ2(115) = 30.59, p < 0.001, AUC = 84.7%).

CONCLUSIONS

Physical testing-related factors were most likely to influence draft outcome, where larger and more agile players were desirable draft picks. In-game movement profile had some bearing on draft outcome in all positional groups with the exception of fixed.

A GNSS-based method to define athlete manoeuvrability in field-based team sports

This study presented a method of quantifying the manoeuvrability of two field-based team sport athletes and investigated its relationship with running velocity during competition. Across a season, 10 Hz Global navigation satellite system (GNSS) devices were worn during matches by 62 athletes (Australian Football League [AFL]; n = 36, 17 matches, National Rugby League [NRL]; n = 26, 21 matches). To quantify manoeuvrability, tortuosity was calculated from the X and Y coordinates from match GNSS files (converted from latitude and longitude). Tortuosity was calculated as 100 x natural logarithm of the chord distance (distance travelled between X and Y coordinates), divided by the straight-line distance. The maximal tortuosity was then quantified for each 0.5 m∙s-1 speed increment, ranging from 0 to the highest value for each game file. A quadratic model was fitted for each match file, controlling for the curvilinear relationship between tortuosity and velocity. A comparison of the quadratic coefficients between sports, and within sport between positions was investigated using linear mixed models. Resulting standard deviations (SDs) and mean differences were then assessed to establish standardized effect sizes (ES) and 90% confidence intervals (CI). A curvilinear relationship exists between maximal tortuosity and running speed, reflecting that as speed increases, athletes' ability to deviate from a linear path is compromised (i.e., run in a more linear path). Compared to AFL, NRL had a greater negative quadratic coefficient (a) (ES = 0.70; 0.47 to 0.93) for the 5 second analysis, meaning that as speed increased, NRL athletes' manoeuvrability reduced at a faster rate than when compared to AFL. There were no positional differences within each sport. GNSS derived information can be used to provide a measure of manoeuvrability tortuosity during NRL and AFL matches. The curvilinear relationship between tortuosity and speed demonstrated that as speed increased, manoeuvrability was compromised.

Peak Movement and Technical Demands of Professional Australian Football Competition

ABSTRACT

Johnston, RD, Murray, NB, Austin, DJ, and Duthie, G. Peak movement and technical demands of professional Australian football competition. J Strength Cond Res 35(10): 2818-2823, 2021-The aim of this study was to determine the average peak movement and technical demands of professional Australian football (AF) across a number of period durations using an observational cohort design. This information will be able to guide duration-specific intensities for training drills. Microtechnology and technical performance data were recorded across 22 games of the 2017 AF League season. The peak 1-, 3-, 5-, 7-, and 10-minute rolling periods were determined from each game for each player for each frequency of skill involvements. Average speed (m·min-1) and accelerometer load (PlayerLoad; PL·min-1) were used as measures of physical output, and any disposal of the football or tackle was used as a technical involvement. Linear mixed models and Cohen's effect size (ES) statistic were used to determine the impact technical involvements had on movement profiles. There were substantial reductions in average speed across each duration as the number of technical involvements increased, other than for the 10-minute period. The reductions in speed were greatest during the 1-minute period for 1 (ES = -0.59 ± 0.13), 2 (ES = -1.96 ± 0.17), and 3 (ES = -2.39 ± 0.27) involvements. Similarly, less pronounced reductions were seen for accelerometer load, other than during the 7- and 10-minute periods where there were small to moderate increases in load for periods with technical involvements. Players may have to perform as many as 3 technical involvements a minute while covering 150-160 m·min-1. This information provides coaches with the peak speed, accelerometer load, and technical demands of competition. There are reductions in movement profiles as the number of technical involvements increases.

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.

Anaerobic Speed/Power Reserve and Sport Performance: Scientific Basis, Current Applications and Future Directions

Many individual and team sport events require extended periods of exercise above the speed or power associated with maximal oxygen uptake (i.e., maximal aerobic speed/power, MAS/MAP). In the absence of valid and reliable measures of anaerobic metabolism, the anaerobic speed/power reserve (ASR/APR) concept, defined as the difference between an athlete's MAS/MAP and their maximal sprinting speed (MSS)/peak power (MPP), advances our understanding of athlete tolerance to high speed/power efforts in this range. When exercising at speeds above MAS/MAP, what likely matters most, irrespective of athlete profile or locomotor mode, is the proportion of the ASR/APR used, rather than the more commonly used reference to percent MAS/MAP. The locomotor construct of ASR/APR offers numerous underexplored opportunities. In particular, how differences in underlying athlete profiles (e.g., fiber typology) impact the training response for different 'speed', 'endurance' or 'hybrid' profiles is now emerging. Such an individualized approach to athlete training may be necessary to avoid 'maladaptive' or 'non-responses'. As a starting point for coaches and practitioners, we recommend upfront locomotor profiling to guide training content at both the macro (understanding athlete profile variability and training model selection, e.g., annual periodization) and micro levels (weekly daily planning of individual workouts, e.g., short vs long intervals vs repeated sprint training and recovery time between workouts). More specifically, we argue that high-intensity interval training formats should be tailored to the locomotor profile accordingly. New focus and appreciation for the ASR/APR is required to individualize training appropriately so as to maximize athlete preparation for elite competition.

Peak Running Intensities in Field Hockey - A Positional Analysis

The aim of this study was to investigate the positional mean peak running periods during a field hockey match using a moving average method. The secondary aim was to investigate how the peak periods changed between quarters and playing positions. The moving average method was used to analyse the data because of the nature of field hockey, which has natural fluctuations of high and low intensity periods of play. The time periods included periods from 1 to 10 minutes. The level of significance for results was set at p ≤ 0.05. The study found that forwards had a peak running intensity of 194 ± 24.2 m·min^-1, midfielders 189 ± 11.9 m·min^-1, and defenders 182.6 ± 17.9 m·min^-1. These results showed that forwards had the highest maximum running speed, with defenders having the lowest one (p = 0.0025). Additionally, running output started to plateau after 7/8-min periods for each of the three positions. Forwards did not show any statistically significant changes across the four quarters. Midfielders showed effect sizes ranging from >0.6 to >2.0 (moderate, large and very large) significance when comparing the first three quarters to the fourth one. Defenders showed >0.6 to <2.0 (moderate to large) effect sizes to occur when comparing the first and second quarter to the fourth. There are three main practical implications from the results of this study: 1) the creation of conditioning drills, 2) substitution patterns, and 3) knowledge to be able to plan and train at or above peak match demands.

Evolving peak period, match movement, and performance demands in elite women's Australian football

OBJECTIVES

Given the dearth of research available on the elite women's Australian football (AFLW) competition, this study aimed to observe the position-specific peak movement demands of AFLW players and assess whether any seasonal changes have occurred in movement- or performance-based metrics over the initial three years of competition.

DESIGN

Observational longitudinal design.

METHODS

Data were collected on one team across the initial three seasons of the AFLW competition. Global position system units were used to obtain the movement demands while performance metrics were obtained from an external statistical provider. Peak movement demands were determined using a rolling period analysis of 1-10 min durations. Mixed models were used to assess the influence of season and position on movement- and performance-based metrics.

RESULTS

Peak period high speed running (HSR, >14.4 km/h), but not total distance (TD), differed between playing positions, with midfielders covering the greatest peak period movements (p < 0.01). No seasonal changes were observed for peak periods of TD or HSR for any positions. Various mean running movements observed seasonal changes and positional differences (p < 0.01), albeit with small effect sizes. No performance-based metric differed by position. Seasonal changes were observed for handballs and uncontested possessions only (p < 0.01), with trivial effect sizes.

CONCLUSIONS

The small differences in on-field movement patterns and performance characteristics of AFLW players observed across seasons and between positional groups gives confidence that practitioners can continue to prescribe whole team rather than position-specific movement and technical training. External factors such as modification to competition structure and rules, or a change in team focus, may mask developments in this competition and warrants continued investigation.

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.

A Comparison of Peak Intensity Periods across Male Field Hockey Competitive Standards

This investigation aimed to compare the international level peak intensity period of male field hockey players to those experienced during professional and amateur club hockey match play. Twenty-seven players from an international squad were monitored for all activity relating to field hockey over three seasons. The peak intensity period, of 3 min duration, was extracted from match play files for international and club matches. Club matches were categorised by league standard-professional vs. amateur. The output for the peak intensity period, within positions, was compared using linear mixed models (LMMs) and post hoc pairwise comparisons. Significance levels were set as p < 0.05 and Cohen's d was utilised for effect sizes. Competition level had a main effect on relative total distance (p < 0.05) and significant interaction effects were found between competition level and position (p < 0.05). Midfielders competing in amateur leagues and international match play completed less relative total distance than those who compete in professional leagues (-47.88 m/min, p < 0.05), (-46.06 m/min, p < 0.05) with large effect sizes reported. No other position displayed significant differences for peak periods. Match play in professional leagues provide opportunities for midfielders to experience peak intensity periods of a greater magnitude than international match play.

Evolution of Physical Demands of Australian Football League Matches from 2005 to 2017: A Systematic Review and Meta-Regression

BACKGROUND

There is extensive research investigating the match demands of players in the Australian Football League (AFL).

OBJECTIVE

This systematic literature review and meta-regression sought to analyse the evolution of in-game demands in AFL matches from 2005 to 2017, focusing on the relationship between volume and intensity.

METHODS

A systematic search of Ovid MEDLINE, Embase, Emcare, Scopus, SPORTDiscus, and Cochrane Library databases was conducted. Included studies examined the physical demands of AFL matches utilising global positioning system (GPS) technology. Meta-regression analysed the shift in reported volume (total distance and total match time) and intensity (metres per minute [m.min^-1], sprint duration and acceleration) metrics for overall changes, across quarters and positional groups (forwards, nomadics and defenders) from 2005 to 2017 inclusive and for each year between 2005 and 2007, 2007 and 2010, 2010 and 2012, and 2012 and 2015/2017 breakpoints.

RESULTS

Distance (p = 0.094), m.min^-1 (p = 0.494), match time (p = 0.591), time over 18 km·h^-1 (p = 0.271), and number of accelerations greater than 4 km·h^-1 (p = 0.498) and 10 km·h^-1 (p = 0.335) in 1 s did not change from 2005 to 2017. From 2005 to 2007 volume decreased (- 6.10 min of match time; p = 0.010) and intensity increased (6.8 m.min^-1 increase; p = 0.023). Volume and intensity increased from 2007 to 2010, evidenced by increases in total distance (302 m; p = 0.039), time over 18 km·h^-1 (0.31 min; p = 0.005), and number of accelerations greater than 4 km·h^-1 (41.1; p = 0.004) and 10 km·h^-1 (3.6; p = 0.005) in 1 s. From 2010 to 2012, intensity decreased, evidenced by reductions in metres per minute (- 4.3; p = 0.022), time over 18 km·h^-1 (- 0.93 min; p < 0.001), and number of accelerations greater than 4 km·h^-1 (- 104.4; p < 0.001) and 10 km·h^-1 (- 8.3; p < 0.001) in 1 s, whilst volume stabilised with no changes in distance (p = 0.068) and match time (p = 0.443). From 2012 to 2015/2017 volume remained stable and intensity increased with time over 18 km·h^-1 (0.27 min; p = 0.008) and number of accelerations greater than 4 km·h^-1 (31.6; p = 0.016) in 1 s increasing.

CONCLUSIONS

Changes in volume and intensity of AFL match demands are defined by discrete periods from 2007 to 2010 and 2010 to 2012. The interaction of rule and interpretation changes and coaching strategies play a major role in these evolutionary changes. In turn, modified game styles impact player game demands, training, and selection priorities. Standardisation and uniformity of GPS data reporting is recommended due to inconsistencies in the literature.

Positional Differences in the Most Demanding Scenarios of External Load Variables in Elite Futsal Matches

The aims of this study were to analyze the peak physical demands in elite futsal by quantifying the most demanding scenarios of match play and to identify the differences between playing positions (defenders, wingers, and pivots) and the seasonal trend for five different rolling average time windows (30, 60, 120, 180, and 300 s). The most demanding scenarios of external load from distance, speed, acceleration, and deceleration variables were obtained from 14 elite futsal players using a local positioning system during 15 official matches in the premier Spanish Futsal League (2018-2019 season). The results showed an extremely large effect of the time window for all dependent variables in all positional groups. Another important finding of this study was that, in regard to the seasonal trend, only defenders reported clear moderate-large positive trends for high-speed running (>18 km⋅h-1) efforts, high-acceleration efforts, and high-deceleration efforts. Finally, moderate-large individual differences in player means for all dependent variables and clear differences between games for most dependent variables were found, suggesting how likely contextual factors may exert an influence on how "demanding" the most demanding scenarios are. The findings of this study provide coaches and strength and conditioning coaches further knowledge of the peak physical demands in elite futsal competition. This valuable information may lead to a more precise position-specific training prescription.

Preparing for an Australian Football League Women's League Season

The aims were to investigate the externally measured weekly loads, and the distribution intensity relative to the 1-min maximal mean (MM) intensity of matches. Athletes (n = 28) wore 10 Hz GNSS devices during training and matches. For the descriptive analysis, a range of movement variables were collected, including total distance, high-speed distance, very high-speed distance, acceleration, and acceleration load. Using raw GNSS files, 1-min moving averages were calculated for speed (m·min^-1) and acceleration (m·s^-2), and were multiplied by time, specifying total distance (m), and by body mass to quantify impulse (kN·s^-1). The distribution of distance and impulse accumulated at varied intensities relative to MMs was calculated, with percentages ranging from zero to 110%. Drills were categorized as either; warm-ups, skill drills, games (i.e., small-sided games), conditioning and matches. Linear mixed models determined if the distribution of intensity within each threshold (>50%) varied between drill types and matches, and if the distribution within drill types varied across the season. Effects were described using standardized effect sizes (ES) and 90% confidence limits (CL). Compared to matches, a higher proportion of distance was accumulated at 50% of the MM within warm-ups and conditioning (ES range 0.86-1.14). During matches a higher proportion of distance was accumulated at 60% of MM when compared to warms ups, skill drills and conditioning (0.73-1.87). Similarly, greater proportion of distance was accumulated between 70 and 100% MM in matches compared to skill drills and warm-ups (1.05-3.93). For impulse, matches had a higher proportion between 60 and 80% of the MM compared to conditioning drills (0.91-3.23). There were no other substantial differences in the proportion of impulse between matches and drill types. When comparing phases, during competition there was a higher proportion of distance accumulated at 50% MM than general preparation (1.08). A higher proportion of distance was covered at higher intensities within matches compared to drills. The proportion of impulse was higher between 60 and 80% MM within matches compared to conditioning. Practitioners can therefore ensure athletes are not only exposed to the intensities common within competition, but also the volume accumulated is comparable, which may have positive performance outcomes, but is also extremely important in the return to play process.

Is it enough to use the traditional approach based on average values for basketball physical performance analysis?

Understanding the most demanding scenarios of basketball match-play can optimise training prescription. We established physical demand differences in total distance covered, distance covered at high-speed running, distance covered at high-intensity accelerations and decelerations, number of high-speed running actions and number of high-intensity accelerations comparing the traditional average method with the most demanding scenarios based on 1-minute rolling averages. Physical demand parameters were analysed from 21 elite basketball players according to playing position during a friendly game via local positioning system microtechnology. The results showed that players covered a total distance of 141.3 m·min^-1 (p < 0.001; ES = 7.80) and 25.4 m·min^-1 (p < 0.001; ES = 4.52) at high-speed running using rolling averages, compared to 66.3 and 3.2 m min^-1, respectively, using the traditional average approach. These data represent a very large increase of 113.1% for total distance per minute and 686.4% for high-speed running distance per minute, 252% for the number of high-intensity accelerations and 290.5% for the number of high-intensity decelerations, respectively, demonstrating the relevance of this novel approach. In conclusion, this investigation indicated that the traditional average method underestimates peak physical demands over a 1-minute period during a basketball game. Thus, the average approach should be complemented by analysing the most demanding scenarios in order to have a better understanding of physical demands during basketball competition.

Quantification of an Elite Futsal Team's Microcycle External Load by Using the Repetition of High and Very High Demanding Scenarios

The main objective of this study was to describe the repetition of external load high-demanding scenarios and very high-demanding scenarios of match play for velocity, distance, and neuromuscular locomotor variables of an elite futsal team. Additionally, we also checked how these high- and very high-demanding scenarios were distributed throughout the microcycle. The most demanding scenario (measured using a rolling average method with a 1-min time window) of match play was measured out of thirteen elite futsal players using a local positioning system in the course of thirteen official matches and six in-season microcycles. A mean of the top three match play observations for each variable and each player were used to determine the most demanding scenario (100%) reference value. Data were reanalyzed to count the number of high-demanding scenarios (80-90% of the individual most demanding scenario) and very high-demanding scenarios (>90% of the individual most demanding scenario). The number of scenarios was analyzed with respect to the number of days prior to the match [match day (MD) minus X] and a bootstrap confidence interval approach was used to assess differences between MD. During a single match, players have to cope with repeated high- and very high-demanding scenarios. Moreover, the training session 2 days prior to the match was the one most similar to the match, surpassing it only in scenarios of locomotor velocity variables, albeit with significantly fewer scenarios of neuromuscular variables. The number of high- and very high-demanding scenarios in the training session prior to the match dropped significantly in comparison with the rest of the microcycle and the match. This new monitoring method may help practitioners to establish an accurate assessment of external load demands in competition and training.

Reliability and Validity of Maximal Mean and Critical Speed and Metabolic Power in Australian Youth Soccer Players

The reliability and validity of maximal mean speed (MMS), maximal mean metabolic power (MMPmet), critical speed (CS) and critical metabolic power (CPmet) were examined throughout the 2016-2017 soccer National Youth League competitions. Global positioning system (GPS) data were collected from 20 sub-elite soccer players during a battery of maximal running tests and four home matches. A symmetric moving average algorithm was applied to the instantaneous velocity data using specific time windows (1, 5, 10, 60, 300 and 600 s) and peak values were identified. Additionally, CS and CP¬met values calculated from match data were compared to CS and CPmet values determined from previously validated field tests to assess the validity of match values. Intra-class correlation (one-way random absolute agreement) scores ranged from 0.577 to 0.902 for speed, and from 0.701 to 0.863 for metabolic power values. Coefficients of variation (CV) ranged from good to moderate for speed (4-6%) and metabolic power (4-8%). Only CS and CPmet values were significantly correlated (r = 0.842; 0.700) and not statistically different (p = 0.066; 0.271) to values obtained in a shuttle-running critical test. While the present findings identified match-derived MMS, MMPmet, CS and CPmet to be reliable, only CS and CPmet derived from match play were validated to a CS field test that required changes in speed and direction rather than continuous running. This suggests that both maximal mean and critical speed and metabolic power analyses could be alternatives to absolute distance and speed in the assessment of match running performance during competitive matches.

Sensitivity, reliability and construct validity of GPS and accelerometers for quantifying peak periods of rugby competition

Training prescription and monitoring of team-sport athletes rely on accurate quantification of player movement. Our aim was to determine the sensitivity, reliability and construct validity of measures derived from a wearable device incorporating Global Positioning System (GPS) and accelerometer technology to quantify the peak periods of rugby competition. Match movement data were collected from 30 elite and 30 sub-elite rugby union players across respective competitive seasons. Accelerometer and GPS measures were analysed using a rolling average to identify peak movement for epochs ranging from 5 to 600 seconds. General linear mixed modelling was used to quantify the effects of playing position and match-half on the peak movement and variabilities within and between players represented reliability of each measure. Mean positional differences and match-half changes were assessed via standardisation and magnitude-based decisions. Sensitivity of measures was quantified via evaluation of ("signal") and typical error of measurement ("noise"). GPS and accelerometer measures had poor sensitivity for quantifying peak movement across all epochs and both levels of rugby union competition (noise 4× to 5× the signal). All measures displayed correspondingly low reliability across most epochs and both levels of competition (ICC<0.50). Construct validity was evident in mean differences between playing positions and match halves that were consistent with expected activity profiles in rugby union. However, it was clear from the pattern of differences across epoch durations and levels of competition that GPS and accelerometer measures provided different information about player movement. The poor sensitivity and low reliability of GPS and accelerometer measures of peak movement imply that rugby union players need to be monitored across many matches to obtain adequate precision for assessing individuals. Although all measures displayed construct validity, accelerometers provided meaningful information additional to that of GPS. We recommend using accelerometers alongside GPS to monitor and prescribe match respresentative training.

Phases of match-play in professional Australian Football: Distribution of physical and technical performance

The current study aimed to describe the distribution of physical and technical performance during the different phases of play in professional Australian Football. The phases of play (offence, defence, contested play, umpire stoppages, set shots and goal resets) were manually coded from video footage for a single team competing in 18 matches in the Australian Football League. Measures of physical performance including total distance (m), average speed (m · min-1), low-speed running (LSR, <14.4 km h-1), high-speed running (HSR, >14.4 km h-1), accelerations (2.78 m · s-2) and decelerations (-2.78 m · s-2) were derived from each phase of play via global positioning system (GPS) devices. Technical skill data including tackles, handballs and kicks were obtained from a commercial statistics provider and derived from each phase of play. Linear mixed-effects models and effect sizes were used to assess and reflect the differences in physical and technical performance between the six phases of play. Activity and recovery cycles, defined as periods where the ball was in or out of play were also described using mean and 95% confidence intervals. The analysis showed that several similarities existed between offence and defence for physical performance metrics. Contested play involved the highest total distance, LSR, accelerations, decelerations and tackles compared to all other phases. Offence and defence involved the highest average speed and HSR running distances. Handballs and kicks were highest during offence, while tackles were highest during contested play, followed by defence. Activity and recovery cycles involved mean durations of ~110 and ~39 s and average speeds of ~160 and ~84 m · min-1, respectively. The integration of video, GPS and technical skill data can be used to investigate specific phases of Australian Football match-play and subsequently guide match analysis and training design.

The Most Demanding Scenarios of Play in Basketball Competition From Elite Under-18 Teams

The main purpose of this study was to describe the most demanding scenarios of match play in basketball through a number of physical demand measures (high-intensity accelerations and decelerations, relative distance covered, and relative distance covered in established speed zones) for four different rolling average time epochs (30, 60, 180, and 300 s) during an official international tournament. A secondary purpose was to identify whether there were significant differences in physical demand measures among playing positions (centers, guards, and forwards) and levels (two best classified teams in the tournament and remaining teams), match scoring (winning, losing, and drawing), and playing periods (match quarter) at the moment of the most demanding scenarios. Data were collected from 94 male under 18 (U18) elite basketball players (age: 17.4 ± 0.7 years; stature: 199.0 ± 11.9 cm; body mass: 87.1 ± 13.1 kg) competing in a Euroleague Basketball Tournament. Measures were compared via a Bayesian inference analysis. The results revealed the presence of position-related differences [Bayesian factor (BF) > 10 (at least strong evidence) and standardized effect size (δ) > 0.6 (at least moderate)] so that centers covered a lower relative distance at speed zone 1 and had lower high-intensity accelerations and decelerations than guards. However, the Bayesian analysis did not demonstrate the existence of significant differences in any physical demand measure in relation to the playing level, match scoring, and playing periods at the moment of the most demanding scenarios. Therefore, this study provides coaches and strength and conditioning specialists with a most demanding scenario reference on physical demands that can be used as an upper limit threshold in the training and rehabilitation monitoring processes.

Interdisciplinary Sport Research Can Better Predict Competition Performance, Identify Individual Differences, and Quantify Task Representation

Sport performance consists of interacting individual, task and environmental constraints, but research has used a monodisciplinary, rather than an interdisciplinary approach to understand performance. This study used Australian football (AF) as the exemplar sport to investigate the value of an interdisciplinary approach to understand sport performance. Through this, it was also possible to quantify individual differences and representative task design. Fifty-nine semi-professional Australian footballers participated. Based upon accessibility, combinations of these players completed physiological (3 × 1 km trial) and perceptual-cognitive-motor (small-sided game, SSG) tests, with coach rating of psychological skill (mental toughness coach, MTC). Univariate monodisciplinary models indicated that all tests predicted disposal efficiency; 3 × 1 km trial (p = 0.047), SSG (p = 0.001), and MTC (p = 0.035), but only the SSG predicted coaches' vote (p = 0.003). A multivariate interdisciplinary model indicated that SSG and MTC tests predicted disposal efficiency with a better model fit than the corresponding univariate model. The interdisciplinary model formulated an equation that could identify individual differences in disposal efficiency. In addition, the interdisciplinary model showed that the higher representative SSG test contributed a greater magnitude to the prediction of competition performance, than the lower representative MTC rating. Overall, this study demonstrates that a more comprehensive understanding of sport performance, individual differences, and representative tasks, can be obtained through an interdisciplinary approach.

The most demanding passages of play in football competition: a comparison between halves

The purpose of this investigation was to determine the differences between halves in the most demanding passages of play in football players according to playing position and duration-specific activity. Global positioning system data were collected from twenty-three football players from a reserve squad of the Spanish La Liga. A total of 265 individual match half data were analysed across the competitive season. Players were categorised based on positional groups: full-back (FB), central defender (CD), midfielder (MF), offensive midfielder (OMF) and forwards (FW). The most demanding passage of match play was analysed using a rolling average method, where maximal values were calculated for five different time durations (1, 3, 5, 10 min and half completed) using distance (m·min-1), high metabolic load distance (HMLD; m·min-1) and average metabolic power (AMP; W·kg-1) as variables of interest. The differences between the first and second half increased as the rolling duration increased, reaching the greatest difference between halves in the complete half (45 min) in all the variables studied (ES = 0.54 ± 0.15, 0.75 ± 0.15 and 0.76 ± 0.15 in distance, HMLD and AMP). The CDs were the players that presented the greatest differences, and it was in the AMP variable where the greatest differences between the first and second half were found. Large decreases in AMP were found for CD (ES = -1.30 ± 0.36) and moderate decreases were found in AMP for FB (ES = -0.84 ± 0.30) and OMF (ES = -0.78 ± 0.37). These results provide insight into the most demanding passages of play to inform training practices for specific football playing positions.

Positional demands for various-sided games with goalkeepers according to the most demanding passages of match play in football

The main aim was to determine the differences between four training games and competitive matches (CM) according to position and compared to the most demanding passages (MDP) of competitive match play. Global Positioning System data were obtained from 21 football players belonging to the reserve squad of a Spanish La Liga club during the 2015/16 season. The training games were small-sided games (SSGs) with 5 and 6 and large-sided games with 9 and 10 outfield players per team. The players were categorized based on positional groups: full back (FB), central defender (CD), midfielder (MF), offensive midfielder (OMF), and forward (FW). The variables recorded were the distance covered (DIS), DIS at high speed (HSR; >19.8 km·h-1), DIS at sprint (SPR; >25.2 km·h-1), high metabolic load distance (HMLD; >25.5 W·kg-1) all in m·min-1, average metabolic power (AMP; W·kg-1) and number of high-intensity accelerations (ACC; >3 m·s-2) and decelerations (DEC; <-3 m·s-2), both in n·min-1. The MDP was analysed using a rolling average method for AMP as a criterion variable, where maximal values were calculated for time windows of 5 and 10 minutes of CM and after that compared with the training game formats. As the SSG format increases, all the rest of the variables increase and the number of cases with significant interposition differences also increases (effect size [ES]: DIS: 0.7-2.2; HSR: 0.7-2.1; SPR: 0.8-1.4; HMLD: 0.9-2.0; AMP: 0.8-1.9; ACC: 0.8-1.7; DEC: 0.5-1.7). The large-sided game 10v10 + 2 goalkeepers over-stimulates sprint values relative to MDP (all: 121.0% of MDP, ES=0.5-1.8). This study provides useful information for coaching staff on the heightened impact of different training game formats on physical load, considering positional differences in relation to the MDP of competitive match play.

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.

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.

Modelling Movement Energetics Using Global Positioning System Devices in Contact Team Sports: Limitations and Solutions

Quantifying the training and competition loads of players in contact team sports can be performed in a variety of ways, including kinematic, perceptual, heart rate or biochemical monitoring methods. Whilst these approaches provide data relevant for team sports practitioners and athletes, their application to a contact team sport setting can sometimes be challenging or illogical. Furthermore, these methods can generate large fragmented datasets, do not provide a single global measure of training load and cannot adequately quantify all key elements of performance in contact team sports. A previous attempt to address these limitations via the estimation of metabolic energy demand (global energy measurement) has been criticised for its inability to fully quantify the energetic costs of team sports, particularly during collisions. This is despite the seemingly unintentional misapplication of the model's principles to settings outside of its intended use. There are other hindrances to the application of such models, which are discussed herein, such as the data-handling procedures of Global Position System manufacturers and the unrealistic expectations of end users. Nevertheless, we propose an alternative energetic approach, based on Global Positioning System-derived data, to improve the assessment of mechanical load in contact team sports. We present a framework for the estimation of mechanical work performed during locomotor and contact events with the capacity to globally quantify the work done during training and matches.