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

ABSTRACT: Jennings, J, Staka, Z, Wundersitz, DW, Sullivan, CJ, Cousins, SD, Custovic, 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.

Applications of hyperspectral imaging in plant phenotyping.

Our ability to interrogate and manipulate the genome far exceeds our capacity to measure the effects of genetic changes on plant traits. Much effort has been made recently by the plant science research community to address this imbalance. The responses of plants to environmental conditions can now be defined using a variety of imaging approaches. Hyperspectral imaging (HSI) has emerged as a promising approach to measure traits using a wide range of wavebands simultaneously in 3D to capture information in lab, glasshouse, or field settings. HSI has been applied to define abiotic, biotic, and quality traits for optimisation of crop management.

Criterion Validity of a MARG Sensor to Assess Countermovement Jump Performance in Elite Basketballers.

ABSTRACT: Staunton, CA, Stanger, JJ, Wundersitz, DW, Gordon, BA, Custovic, E, and Kingsley, MI. Criterion validity of a MARG sensor to assess countermovement jump performance in elite basketballers. J Strength Cond Res 35(3): 797-803, 2021-This study assessed the criterion validity of a magnetic, angular rate, and gravity (MARG) sensor to measure countermovement jump (CMJ) performance metrics, including CMJ kinetics before take-off, in elite basketballers. Fifty-four basketballers performed 2 CMJs on a force platform with data simultaneously recorded by a MARG sensor located centrally on the player's back. Vertical accelerations recorded from the MARG sensor were expressed relative to the direction of gravity. Jumps were analyzed by a blinded assessor and the best jump according to the force platform was used for comparison. Pearson correlation coefficients (r) and mean bias with 95% ratio limits of agreement (95% RLOA) were calculated between the MARG sensor and the force platform for jumps performed with correct technique (n = 44). The mean bias for all CMJ metrics was less than 3%. Ninety-five percent RLOA between MARG- and force platform-derived flight time and jump height were 1 ± 7% and 1 ± 15%, respectively. For CMJ performance metrics before takeoff, impulse displayed less random error (95% RLOA: 1 ± 13%) when compared with mean concentric power and time to maximum force displayed (95% RLOA: 0 ± 29% and 1 ± 34%, respectively). Correlations between MARG and force platform were significant for all CMJ metrics and ranged from large for jump height (r = 0.65) to nearly perfect for mean concentric power (r = 0.95). Strong relationships, low mean bias, and low random error between MARG and force platform suggest that MARG sensors can provide a practical and inexpensive tool to measure impulse and flight time-derived CMJ performance metrics.

The Effect of Match Schedule on Accelerometry-Derived Exercise Dose during Training Sessions throughout a Competitive Basketball Season.

Accelerometry-derived exercise dose (intensity × duration) was assessed throughout a competitive basketball season. Nine elite basketballers wore accelerometers during a Yo-Yo intermittent recovery test (Yo-Yo-IR1) and during three two-week blocks of training that represented phases of the season defined as easy, medium, and hard based on difficulty of match schedule. Exercise dose was determined using accumulated impulse (accelerometry-derived average net force × duration). Relative exercise intensity was quantified using linear relationships between average net force and oxygen consumption during the Yo-Yo-IR1. Time spent in different intensity zones was computed. Influences of match schedule difficulty and playing position were evaluated. Exercise dose reduced for recovery and pre-match tapering sessions during the medium match schedule. Exercise dose did not vary during the hard match schedule. Exercise dose was not different between playing positions. The majority of activity during training was spent performing sedentary behaviour or very light intensity activity (64.3 ± 6.1%). Front-court players performed a greater proportion of very light intensity activity (mean difference: 6.8 ± 2.8%), whereas back-court players performed more supramaximal intensity activity (mean difference: 4.5 ± 1.0%). No positional differences existed in the proportion of time in all other intensity zones. Objective evaluation of exercise dose might allow coaches to better prescribe and monitor the demands of basketball training.

Sleep patterns and match performance in elite Australian basketball athletes.

OBJECTIVES: To assess sleep patterns and associations between sleep and match performance in elite Australian female basketball players. DESIGN: Prospective cohort study. METHODS: Seventeen elite female basketball players were monitored across two consecutive in-season competitions (30 weeks). Total sleep time and sleep efficiency were determined using triaxial accelerometers for Baseline, Pre-match, Match-day and Post-match timings. Match performance was determined using the basketball efficiency statistic (EFF). The effects of match schedule (Regular versus Double-Header; Home versus Away) and sleep on EFF were assessed. RESULTS: The Double-Header condition changed the pattern of sleep when compared with the Regular condition (F(3,48)=3.763, P=0.017), where total sleep time Post-match was 11% less for Double-Header (mean±SD; 7.2±1.4h) compared with Regular (8.0±1.3h; P=0.007). Total sleep time for Double-Header was greater Pre-match (8.2±1.7h) compared with Baseline (7.1±1.6h; P=0.022) and Match-day (7.3±1.5h; P=0.007). Small correlations existed between sleep metrics at Pre-match and EFF for pooled data (r=-0.39 to -0.22; P≥0.238). Relationships between total sleep time and EFF ranged from moderate negative to large positive correlations for individual players (r=-0.37 to 0.62) and reached significance for one player (r=0.60; P=0.025). CONCLUSIONS: Match schedule can affect the sleep patterns of elite female basketball players. A large degree of inter-individual variability existed in the relationship between sleep and match performance; nevertheless, sleep monitoring might assist in the optimisation of performance for some athletes.