Physical Preparation Factors That Influence Technical and Physical Match Performance in Professional Australian Football.

OBJECTIVES: To examine the collective influence of a range of physical preparation elements on selected performance measures during Australian football match play. DESIGN: Prospective and longitudinal. METHODS: Data were collected from 34 professional Australian football players from the same club during the 2016 Australian Football League competition season. Match activity profiles and acute (7-d) and chronic (3-wk) training loads were collected using global positioning system devices. Training response was measured by well-being questionnaires completed prior to the main training session each week. Maximal aerobic running speed (MAS) was estimated by a 2-km time trial conducted during preseason. Coach ratings were collected from the senior coach and 4 assistants after each match on a 5-point Likert scale. Player ratings were obtained from a commercial statistics provider. Fifteen matches were analyzed. Linear mixed models were constructed to examine the collective influence of training-related factors on 4 performance measures. RESULTS: Muscle soreness had a small positive effect (ES: 0.12) on Champion Data rating points. Three-week average high-speed running distance had a small negative effect (ES: 0.14) on coach ratings. MAS had large to moderate positive effects (ES: 0.55 to 0.47) on relative total and high-speed running distances. Acute total and chronic average total running distance had small positive (ES: 0.13) and negative (ES: 0.14) effects on relative total and high-speed running distance performed during matches, respectively. CONCLUSIONS: MAS should be developed to enhance players' running performance during competition. Monitoring of physical preparation data may assist in reducing injury and illness and increasing player availability but not enhance football performance.

The effect of low- vs high-cadence interval training on the freely chosen cadence and performance in endurance-trained cyclists.

The aim of this study was to determine the effects of high- and low-cadence interval training on the freely chosen cadence (FCC) and performance in endurance-trained cyclists. Sixteen male endurance-trained cyclists completed a series of submaximal rides at 60% maximal power (Wmax) at cadences of 50, 70, 90, and 110 r·min(-1), and their FCC to determine their preferred cadence, gross efficiency (GE), rating of perceived exertion, and crank torque profile. Performance was measured via a 15-min time trial, which was preloaded with a cycle at 60% Wmax. Following the testing, the participants were randomly assigned to a high-cadence (HC) (20% above FCC) or a low-cadence (LC) (20% below FCC) group for 18 interval-based training sessions over 6 weeks. The HC group increased their FCC from 92 to 101 r·min(-1) after the intervention (p = 0.01), whereas the LC group remained unchanged (93 r·min(-1)). GE increased from 22.7% to 23.6% in the HC group at 90 r·min(-1) (p = 0.05), from 20.0% to 20.9% at 110 r·min(-1) (p = 0.05), and from 22.8% to 23.2% at their FCC. Both groups significantly increased their total distance and average power output following training, with the LC group recording a superior performance measure. There were minimal changes to the crank torque profile in both groups following training. This study demonstrated that the FCC can be altered with HC interval training and that the determinants of the optimal cycling cadence are multifactorial and not completely understood. Furthermore, LC interval training may significantly improve time-trial results of short duration as a result of an increase in strength development or possible neuromuscular adaptations.

Factors associated with the selection of the freely chosen cadence in non-cyclists.

The purpose of this study was to examine both the freely chosen cadence (FCC) and the physical variables associated with cadence selection in non-cyclists. Eighteen participants pedalled at 40, 50, and 60% of their maximal power output (determined by a maximal oxygen uptake test, W (max)), whilst cadence (50, 65, 80, 95, 110 rpm, and FCC) was manipulated. Gross efficiency, was used to analyse the most economical cadence whilst central and peripheral ratings of perceived exertion (RPE) were used to measure the most comfortable cadence and the cadence whereby muscle strain was minimised. Peak (T (peak)), mean crank torque (T (mean)) and the crank torque profile were analysed at 150 and 200 W at cadences of 50, 65, 80, 95, and 110 rpm in order to determine the mechanical load. FCC was found to be approximately 80 rpm at all workloads and was significantly higher than the most economical cadence (50 rpm). At 60% W (max), RPE peripheral was minimised at 80 rpm which coincided with the FCC. Both T (peak) and T (mean) decreased as cadence increased and, conversely, increased as power output increased. An analysis of the crank torque profile showed that the crank angle at both the top (DP(top)) and the bottom (DP(bot)) dead point of the crank cycle at 80 rpm occurred later in the cycling revolution when compared to 50 rpm. The findings suggested that the FCC in non-cyclists was more closely related to variables that minimise muscle strain and mechanical load than those associated with minimising metabolic economy.