Utilising one minute and four minute recovery when employing the resistance training contrast method does not negatively affect subsequent jump performance in the presence of concurrent training.

BACKGROUND: Little is known about contrast training and post-activation performance enhancement (PAPE) in a same day concurrent training model. The aim of the current study was to examine the use of two short duration (1-min and 4-min) recovery periods on drop jump performance in same day concurrently trained athletes. METHODS: Ten professional Australian Rules footballers (age, 20.6 ± 1.9 yr; height, 184.8 ± 6.9 cm; body mass, 85.8 ± 8.4 kg) completed two resistance training sessions with different PAPE recovery durations; 1-min and 4-min, 1 h following a field-based endurance session. Baseline (pre) drop jumps were compared to post-test maximal drop jumps, performed after each set of three squats (where each participant was encouraged to lift as heavy as they could), to determine changes between 1-min and 4-min recovery periods. Data were analysed by fitting a mixed model (significance was set at P ≤ 0.05). Corrected Hedges' g standardised effect sizes ±95% confidence limits were calculated using group means ± SDs. RESULTS: There were no significant differences between baseline and experimental sets 1, 2 and 3 for reactive strength index (RSI), flight time, and total and relative impulse for either recovery duration. However, for contact time, 1-min baseline was significantly different from set 2 (mean difference; 95% CI [0.029; 0.000-0.057 s], P = 0.047, ES; 95% CI [-0.27; -1.20 to 0.66]). For RSI and flight time, 1-min was significantly higher than 4-min (RSI: 0.367; 0.091 to 0.642, P = 0.010, ES; 95% CI [0.52; -0.37 to 1.42]; flight time: 0.033; 0.003 to 0.063 s, P = 0.027, ES; 95% CI [0.86; -0.06 to 1.78]). DISCUSSION: Short recovery periods of 1-min may be a time-efficient form of prescribing strength-power exercise in contrast loading schemes. Longer recovery periods do not appear to benefit immediate, subsequent performance.

The Effects of Endurance-Based Skills-Specific Running Loads on Same-Day Resistance-Training Performance in Professional Australian Rules Football Players.

Little is known about the effect of preceding endurance-exercise bouts on subsequent resistance-training (RT) performance in team-sport players. PURPOSE: To examine the effect of prior skills/endurance training and different recovery time periods on subsequent same-day RT performance in professional Australian football players. METHODS: Sport-specific endurance-running loads (duration [in minutes], total distance [in meters], mean speed [in meters per minute], high-speed running >15 km·h-1, and relative high-speed running [>75% and >85% of maximal velocity]) were obtained for 46 professional Australian football players for each training session across an entire competitive season. RT was prescribed in 3 weekly mesocycles with tonnage (in kilograms) lifted recorded as RT performance. Endurance and RT sessions were interspersed by different recovery durations: ∼20 min and 1, 2, and 3 h. Fixed- and mixed-effect linear models assessed the influence of skills/endurance-running loads on RT performance. Models also accounted for season period (preseason vs in-season) and recovery duration between concurrent training bouts. RESULTS: An increase in high-speed running and distance covered >75% and >85% of maximal velocity had the greatest reductions on RT performance. In-season total distance covered displayed greater negative effects on subsequent RT performance compared with preseason, while ∼20-min recovery between skills/endurance and RT was associated with greater reductions in RT performance, compared with 1-, 2-, and 3-h recovery. CONCLUSIONS: Sport-specific endurance-running loads negatively affect subsequent same-day RT performance, and this effect is greater in-season and with shorter recovery durations between bouts.

Greater Association of Relative Thresholds Than Absolute Thresholds With Noncontact Lower-Body Injury in Professional Australian Rules Footballers: Implications for Sprint Monitoring.

Sprint capacity is an important attribute for team-sport athletes, yet the most appropriate method to analyze it is unclear. PURPOSE: To examine the relationship between sprint workloads using relative versus absolute thresholds and lower-body soft-tissue and bone-stress injury incidence in professional Australian rules football. METHODS: Fifty-three professional Australian rules football athletes' noncontact soft-tissue and bone-stress lower-body injuries (N = 62) were recorded, and sprint workloads were quantified over ∼18 months using the global positioning system. Sprint volume (m) and exposures (n) were determined using 2 methods: absolute (>24.9 km·h-1) and relative (≥75%, ≥80%, ≥85%, ≥90%, ≥95% of maximal velocity). Relationships between threshold methods and injury incidence were assessed using logistic generalized additive models. Incidence rate ratios and model performances' area under the curve were reported. RESULTS: Mean (SD) maximal velocity for the group was 31.5 (1.4), range 28.6 to 34.9 km·h-1. In comparing relative and absolute thresholds, 75% maximal velocity equated to ~1.5 km·h-1 below the absolute speed threshold, while 80% and 85% maximal velocity were 0.1 and 1.7 km·h-1 above the absolute speed threshold, respectively. Model area under the curve ranged from 0.48 to 0.61. Very low and very high cumulative sprint loads ≥80% across a 4-week period, when measured relatively, resulted in higher incidence rate ratios (2.54-3.29), than absolute thresholds (1.18-1.58). DISCUSSION: Monitoring sprinting volume relative to an athlete's maximal velocity should be incorporated into athlete monitoring systems. Specifically, quantifying the distance covered at >80% maximal velocity will ensure greater accuracy in determining sprint workloads and associated injury risk.

The Quantification of Within-Week Session Intensity, Duration, and Intensity Distribution Across a Season in Australian Football Using the Session Rating of Perceived Exertion Method.

CONTEXT: Team-sport training requires the daily manipulation of intensity, duration, and frequency, with preseason training focusing on meeting the demands of in-season competition and training on maintaining fitness. PURPOSE: To provide information about daily training in Australian football (AF), this study aimed to quantify session intensity, duration, and intensity distribution across different stages of an entire season. METHODS: Intensity (session ratings of perceived exertion; CR-10 scale) and duration were collected from 45 professional male AF players for every training session and game. Each session's rating of perceived exertion was categorized into a corresponding intensity zone, low (<4.0 arbitrary units), moderate (≥4.0 and <7.0), and high (≥7.0), to categorize session intensity. Linear mixed models were constructed to estimate session duration, intensity, and distribution between the 3 preseason and 4 in-season periods. Effects were assessed using linear mixed models and magnitude-based inferences. RESULTS: The distribution of the mean session intensity across the season was 29% low intensity, 57% moderate intensity, and 14% high intensity. While 96% of games were high intensity, 44% and 49% of skills training sessions were low intensity and moderate intensity, respectively. Running had the highest proportion of high-intensity training sessions (27%). Preseason displayed higher training-session intensity (effect size [ES] = 0.29-0.91) and duration (ES = 0.33-1.44), while in-season game intensity (ES = 0.31-0.51) and duration (ES = 0.51-0.82) were higher. CONCLUSIONS: By using a cost-effective monitoring tool, this study provides information about the intensity, duration, and intensity distribution of all training types across different phases of a season, thus allowing a greater understanding of the training and competition demands of Australian footballers.

Quantification of Training Load During Return to Play After Upper- and Lower-Body Injury in Australian Rules Football.

CONTEXT: Training volume, intensity, and distribution are important factors during periods of return to play. PURPOSE: To quantify the effect of injury on training load (TL) before and after return to play (RTP) in professional Australian Rules football. METHODS: Perceived training load (RPE-TL) for 44 players was obtained for all indoor and outdoor training sessions, while field-based training was monitored via GPS (total distance, high-speed running, mean speed). When a player sustained a competition time-loss injury, weekly TL was quantified for 3 wk before and after RTP. General linear mixed models, with inference about magnitudes standardized by between-players SDs, were used to quantify effects of lower- and upper-body injury on TL compared with the team. RESULTS: While total RPE-TL was similar to the team 2 wk before RTP, training distribution was different, whereby skills RPE-TL was likely and most likely lower for upper- and lower-body injury, respectively, and most likely replaced with small to very large increases in running and other conditioning load. Weekly total distance and high-speed running were most likely moderately to largely reduced for lower- and upper-body injury until after RTP, at which point total RPE-TL, training distribution, total distance, and high-speed running were similar to the team. Mean speed of field-based training was similar before and after RTP compared with the team. CONCLUSIONS: Despite injured athletes' obtaining comparable TLs to uninjured players, training distribution is different until after RTP, indicating the importance of monitoring all types of training that athletes complete.

Quantification of Training and Competition Load Across a Season in an Elite Australian Football Club.

PURPOSE: Load monitoring in Australian football (AF) has been widely adopted, yet team-sport periodization strategies are relatively unknown. The authors aimed to quantify training and competition load across a season in an elite AF team, using rating of perceived exertion (RPE) and GPS tracking. METHODS: Weekly totals for RPE and GPS loads (including accelerometer data; PlayerLoad) were obtained for 44 players across a full season for each training modality and for competition. General linear mixed models compared mean weekly load between 3 preseason and 4 in-season blocks. Effects were assessed with inferences about magnitudes standardized with between-players SD. RESULTS: Total RPE load was most likely greater during preseason, where the majority of load was obtained via skills and conditioning. There was a large reduction in RPE load in the last preseason block. During in-season, half the total load came from games and the remaining half from training, predominantly skills and upper-body weights. Total distance, high-intensity running, and PlayerLoad showed large to very large reductions from preseason to in-season, whereas changes in mean speed were trivial across all blocks. All these effects were clear at the 99% level. CONCLUSIONS: These data provide useful information about targeted periods of loading and unloading across different stages of a season. The study also provides a framework for further investigation of training periodization in AF teams.