ABSTRACT
PURPOSE: This crossover trial compared the effects of varying feedback approaches on sprint performance, motivation, and affective mood states in female athletes. METHODS: Eligibility criteria were being competitive female athletes, where participants completed sprint tests in 4 randomized feedback conditions on grass, including augmented feedback (sprint time; AUG-FB), technical feedback (cues; TECH-FB), a competition-driven drill (CDD) sprinting against an opponent, and a control condition (no feedback; CON). Participants completed a 20-m sprint (maximum sprint), 30-m curved agility sprint, and a repeated sprint ability test, with sprint times, motivation level, and mood states recorded. The participants were blinded from the number of trials during the repeated sprint ability test. RESULTS: About 12 rugby league players completed all feedback conditions. The maximum sprint times were faster for AUG-FB (3.54 [0.16] s) and CDD (3.54 [0.16] s) compared with TECH-FB (3.64 [0.16] s), while there were no differences compared with CON (3.58 [0.17] s). The curved agility sprint times were faster for AUG-FB (5.42 [0.20] s) compared with TECH-FB (5.61 [0.21] s) and CON (5.57 [0.24] s), although CDD (5.38 [0.26] s) produced faster sprint times than TECH-FB. Effort and value were higher with AUG-FB (6.31 [0.68]; 6.53 [0.05]) compared with CON (5.99 [0.60]; 4.75 [2.07]), while CON exhibited lower enjoyment ratings (4.68 [0.95]) compared with other feedback conditions (AUG-FB: 5.54 [0.72]; CDD: 5.56 [0.67]; TECH-FB: 5.60 [0.56]). CONCLUSIONS: Providing AUG-FB prior to sprint tasks enhances more immediate performance outcomes than TECH-FB. AUG-FB also benefited athlete enjoyment, task effort, and coaching value. Female athletes should receive AUG-FB in testing and training environments, to improve immediate physical performance and motivation.
Subject(s)
Athletic Performance , Football , Running , Humans , Female , Cross-Over Studies , Motivation , AthletesABSTRACT
In professional team sports, like Rugby League, performance analysis has become an integral part of operational practices. This has helped practitioners gain deeper insight into phenomena like team and athlete behaviour and understanding how such behaviour may be influenced by various contextual factors. This information can then be used by coaches to design representative practice tasks, inform game principles and opposition strategies, and even support team recruitment practices. At the elite level, the constant evolution of sports technology (both hardware and software) has enabled greater access to information, making the role of the performance analyst even more valuable. However, this increase in information can create challenges regarding which variables to use to help guide decision-making, and how to present it in ways that can be utilised by coaches and other support staff. While there are published works exploring aspects of performance analysis in team sports like Rugby League, there is yet to be a perspective that explores the various operational uses of performance analysis in Rugby League, the addition of which could help guide the practices of emerging performance analysts in elite organisations like the Australian National Rugby League and the European Super League. Thus, this narrative review-with accompanying case examples-explores the various ways performance analysis can help address pertinent operational questions commonly encountered when working in high-performance sport.
ABSTRACT
The current study explored the effects of short haul air travel within the same country on elite Australian rugby league (RL) players (n=12) during two away and two home games of elite competition. Physiological tests of handgrip strength and leg power were assessed along with psychological tests and perceptions of leg soreness and tiredness on the day before the game (Time 1 and Time 2) and on game day (Time 3). Game statistics of tackles and metres gained were assessed for the games analysed. Significant differences were found for daily analyses of life demands for athletes (DALDA) worse than normal responses at Time 2 (2.50 ± 3.23 vs. 3.50 ± 3.93; P=0.04), Karolinska Sleepiness Scale (KSS) at Time 2 (2.88 ± 1.51 vs. 3.71 ± 1.37; P=0.011) and leg tiredness at Time 3 (3.38 ± 1.66 vs. 2.35 ± 1.70; P=0.004) between home and away games. The analysis of game statistics identified that more metres were gained during home games (83.6 ± 49.1 vs. 63.0 ± 30.1; P=0.02) and more tackles made while playing away (18.4 ± 9.2 vs. 14.3 ± 6.7; P=0.016). The results suggest that short haul air travel without crossing time zones results in symptoms of travel fatigue but does not appear to negatively impact on elite RL players ability to perform strength and power tasks. Different game tactics (attacking vs. defensive) occurred between home and away games however, it is unclear whether travel fatigue or a home advantage (HA) is associated with this finding.