Knowledge of bout duration influences pacing strategies during small-sided games.

This investigation examines pacing during intermittent team sports. Sixteen junior Rugby League players participated in eight different small-sided offside touch games. All games were 24 min, but bout durations differed in continuous (1 × 24 min) or repeated (2 × 12, 3 × 8, 4 × 6, 6 × 4, 8 × 3, 12 × 2 or 24 × 1 min) formats. Repeat bouts were interspersed by 2 min of passive rest, and participants were informed of the bout duration immediately prior to the game. Heart rates, ratings of perceived exertion and data gathered from global positioning system devices were used to investigate the pacing strategies employed within each game. No significant (P > 0.05) between-game differences were observed in total distance; however, during the 1-min bouts, high-speed movement was significantly (P < 0.05) increased, during the first and second quarters of the 24 × 1-min game compared to all other formats (effect size range: 0.75 ± 0.61-1.38 ± 0.47). Furthermore, the rate of decline in high-speed movement over-time was greatest during the 24 × 1-min game with large differences observed between the first and third quarters (effect size: 0.90 ± 0.58). Greater moderate-speed (effect size range: 0.62 ± 0.63-1.56 ± 0.40) and less low-speed (effect size range: 0.69 ± 0.62-1.54 ± 0.40) distances were also observed during the 1-min bouts, yet heart rates were higher during the continuous 1 × 24-min game. Pacing strategies during intermittent activities are influenced by the number and duration of exercise bouts. Practitioners should consider within-game bout durations when prescribing game-based activities to improve aerobic capacity.

The effect of a familiarisation period on subsequent strength gain.

Untrained subjects can display diverse strength gain following an identical period of resistance exercise. In this investigation, 28 untrained males completed 16-weeks of resistance exercise, comprising 4-weeks familiarisation, and 12-weeks of heavy-load (80-85%) activity. High and low responders were identified by the Δ1RM (Δ one repetition maximum) observed following familiarisation (25.1 ± 1.4%, 9.5 ± 1.4%, P < 0.0001) and differences in electromyographic root mean square amplitude (ΔEMG(RMS) 29.5 ± 8.3%, 2.4 ± 6.0%, P = 0.0140), and habitual and occupational activity patterns were observed between these respective groups. The strength gain (P < 0.0001) observed within high (29.6 ± 1.7%) and low (31.4 ± 2.7%) responding groups was similar during the heavy-load phase, yet ΔEMG(RMS) increased (P = 0.0048) only in low responders (31.5 ± 9.3%). Retrospectively, differences (P < 0.0001) in baseline 1RM strength of high- (19.7 ± 0.9 kg) and low-responding (15.6 ± 0.7 kg) groups were identified, and a strong negative correlation with Δ1RM after 16-weeks (r (2 )= -0.85) was observed. As such, baseline 1RM strength provided a strong predicative measure of strength adaptation. The ΔEMG(RMS) suggests strength variability within high and low responders may be attributed to neural adaptation. However, differences in habitual endurance and occupational physical activity suggests one should consider screening not only recent resistance training, but also other modes of physical activity during participant recruitment.