The effects of game and training loads on perceptual responses of muscle soreness in Australian football

The Effect of Caffeine Supplementation on Female Volleyball Players' Performance and Wellness during a Regular Training Week

BACKGROUND

caffeine is an ergogenic aid that still needs to be investigated in women's sports performance.

METHODS

Eight semi-professional women's volleyball players (height = 1.63 ± 0.08 m; weight = 66.67 ± 4.74 kg) voluntarily participated in this study. A randomized crossover design was implemented where players underwent caffeine and placebo conditions. In the caffeine condition, participants consumed 5 mg/kg of caffeine based on their body weight before acute training. The evaluations were performed over two weeks of training. In both conditions, the countermovement jump, repeated jumps for 15 s, and handgrip tests were performed. The change of direction was assessed using the 505 test. Well-being was also assessed with a wellness questionnaire. A repeated measures ANOVA and correlation analysis were performed.

RESULTS

The repeated measures ANOVA revealed a main effect of supplementation (F (1.7) = 8.41, p = 0.02, η2 = 0.54) across the training week on physical performance. Additionally, there was a positive effect on perceived fatigue (F (1.7) = 7.29, p = 0.03, η2 = 0.51).

CONCLUSIONS

Caffeine improved performance and fatigue parameters over one week of training. Further research is needed on women, focusing on physical performance and wellbeing, especially during intense periods.

Are non-starters accumulating enough load compared with starters? Examining load, wellness, and training/match ratios of a European professional soccer team

BACKGROUND

The aims of the study were to: (i) compare accumulated load and wellness between starters and non-starters of a European professional soccer team; (ii) analyze the relationships between wellness and load measures and; (iii) compare training/match ratio (TMr) of external and internal load between starters and non-starters.

METHODS

Ten players were considered starters while seven were classified as non-starters over a 16-week period in which six training sessions and match day (MD) were considered in each weekly micro-cycle. The following measures were used: wellness (fatigue, quality of sleep, muscle soreness, stress, and mood); load (rated of perceived exertion (RPE), session-RPE (s-RPE), high-speed running (HSR), sprinting, accelerations (ACC) and decelerations (DEC)). Accumulated wellness/load were calculated by summing all training and match sessions, while TMr was calculated by dividing accumulated training load by match data for all load measures and each player. Mann-Whitney U test was used for wellness variables, while independent T-test was used for the remaining variables to compare groups. Moreover, relationships among variables were explored using the Spearman's Rho correlation coefficient.

RESULTS

The main results showed that non-starters presented higher significant values for fatigue (p < 0.019; g = 0.24) and lower significant values for duration (p < 0.006; ES = 1.81) and s-RPE (p < 0.001; ES = 2.69) when compared to starters. Moreover, positive and very large correlation was found between quality of sleep and RPE, while negative and very large correlation were found between stress and deceleration, and mood and deceleration (all, p < 0.05). Finally, non-starters presented higher values in all TMr than starters, namely, RPE (p = 0.001; g = 1.96), s-RPE (p = 0.002; g = 1.77), HSR (p = 0.001; g = 2.02), sprinting (p = 0.002; g = 4.23), accelerations (p = 0.001; g = 2.72), decelerations (p < 0.001; g = 3.44), and duration (p = 0.003; g = 2.27).

CONCLUSIONS

In conclusion, this study showed that non-starters produced higher TMr in all examined variables despite the lower match and training durations when compared with starters, suggesting that physical load was adjusted appropriately. Additionally, higher RPE was associated with improved sleep while higher number of decelerations were associated with decreased wellness, namely, stress and mood for non-starters.

Relationships between training load, peak height velocity, muscle soreness and fatigue status in elite-level young soccer players: a competition season study

BACKGROUND

This study aimed to compare training load parameters, delayed onset muscle soreness (DOMS), and fatigue status between season periods (1^st and 2^nd halves) in U14 soccer players and to analyze the relationships between training load parameters based on season periods (1^st and 2^nd halves) with peak height velocity (PHV), DOMS, and fatigue status in under-14 (U14) young elite soccer players. Additionally, it was intended to analyze if fatigue, DOMS and PHV could explain training load parameters across the season.

METHODS

Twenty U14 players that competed in the national league participated in this study. The players were monitored during the whole season (26 weeks), and evaluations were carried out at the end of the in-season. Anthropometric and body composition parameters and the maturity offset of each player were utilized to compute each player's age at PHV. Players reported their levels of DOMS and fatigue status using Hooper index questionnaires. The internal load was monitored using the rating of perceived exertion (RPE). Acute weekly internal load (AW), chronic weekly internal load (CW), acute: chronic workload ratio (ACWR), training monotony (TM), and training strain (TS) were also obtained.

RESULTS

The main results showed that TM was higher in the 2^nd half, while CW, AW and DOMS were higher in the 1^st half of the season. Moreover, the main correlations showed a positive correlation between PHV and TS (2^nd half of the season) and between fatigue and TM (1^st half of the season).

CONCLUSION

In conclusion, variations in well-being status and PHV cannot explain the variations in internal training loads in elite U14 soccer players. In addition, internal training load indices during the first half of the competitive season can promote a fundamental base for progression loads during the second period of the competitive season.

Athlete monitoring practices in elite sport in the United Kingdom

Athlete monitoring systems (AMS) aid performance optimisation and support illness/injury prevention. Nonetheless, limited information exists on how AMS are employed across elite sports in the United Kingdom. This study explored how athlete monitoring (AM) data, in particular athlete self-report measures, were collected, analysed and disseminated within elite sports. Thirty elite sports practitioners representing 599 athletes responded to a survey on their AM methodologies. The majority, 83%, (n = 25) utilised an AMS, and a further 84% (n = 21) stated the collection of their AMS data was underpinned by a scientific rationale. Athlete self-report measures (ASRM) were the most commonly employed tool, with muscle soreness, sleep and energy levels amongst the most frequently collected measures. The ubiquitous use of custom single-item ASRM resulted in considerable variability in the questionnaires employed, thus potentially impacting questionnaire validity. Feedback processes were largely felt to be ineffective, with 44% (n = 11) respondents indicating that athletes did not receive sufficient feedback. Some respondents indicated that AMS data was never discussed with athletes and/or coaches. Overall, significant disparities exist in the use of athlete monitoring systems between research and elite sports practice, and the athlete, coach and practitioner experience of monitoring risks being poor if these disparities are not addressed.

Association between Training Load and Well-Being Measures in Young Soccer Players during a Season

This study aimed to analyze the correlations among weekly (w) acute workload (wAW), chronic workload (wCW), acute/chronic workload ratio (wACWR), training monotony (wTM), training strain (wTS), sleep quality (wSleep), delayed onset muscle soreness (wDOMS), fatigue (wFatigue), stress (wStress), and Hooper index (wHI) in pre-, early, mid-, and end-of-season. Twenty-one elite soccer players (age: 16.1 ± 0.2 years) were monitored weekly on training load and well-being for 36 weeks. Higher variability in wAW (39.2%), wFatigue (84.4%), wStress (174.3%), and wHI (76.3%) at the end-of-season were reported. At mid-season, higher variations in wSleep (59.8%), TM (57.6%), and TS (111.1%) were observed. Moderate to very large correlations wAW with wDOMS (r = 0.617, p = 0.007), wFatigue, wStress, and wHI were presented. Similarly, wCW reported a meaningful large association with wDOMS (r = 0.526, p < 0.001); moderate to very large associations with wFatigue (r = 0.649, p = 0.005), wStress, and wHI. Moreover, wTM presented a large correlation with wSleep (r = 0.515, p < 0.001); and a negatively small association with wStress (r = −0.426, p = 0.003). wTS showed a small to large correlation with wSleep (r = 0.400, p = 0.005) and wHI; also, a large correlation with wDOMS (r = 0.556, p = 0.028) and a moderate correlation with wFatigue (r = 0.343, p = 0.017). Wellness status may be considered a useful tool to provide determinant elite players’ information to coaches and to identify important variations in training responses.

Influence of Perceptions of Sleep on Well-Being in Youth Athletes

ABSTRACT

Sawczuk, T, Jones, B, Scantlebury, S, and Till, K. Influence of perceptions of sleep on well-being in youth athletes. J Strength Cond Res 35(4): 1066-1073, 2021-To date, most research considering well-being questionnaires has only considered the training stress imposed on the athlete, without evaluating the questionnaire's relationship with a measure of recovery (e.g., sleep). This study aimed to assess the influence of sleep duration (Sduration), sleep quality (Squality), and sleep index (Sindex; Sduration × Squality) on well-being in youth athletes, while accounting for the known training stressors of training load and exposure to match play. Forty-eight youth athletes (age 17.3 ± 0.5 years) completed a daily questionnaire including well-being (DWBno-sleep; fatigue, muscle soreness, stress, and mood) measures, Perceived Recovery Status Scale (PRS), the previous day's training loads, Sduration, and Squality every day for 13 weeks. Linear mixed models assessed the impact of Sduration, Squality, and Sindex on DWBno-sleep, its individual subscales, and PRS. Sduration had a small effect on DWBno-sleep (d = 0.31; ±0.09), fatigue (d = 0.42; ±0.11), and PRS (d = 0.25; ±0.09). Squality had a small effect on DWBno-sleep (d = 0.47; ±0.08), fatigue (d = 0.53; ±0.11), stress (d = 0.35; ±0.07), mood (d = 0.41; ±0.09), and PRS (d = 0.37; ±0.08). Sindex had a small effect on DWBno-sleep (d = 0.44; ±0.08), fatigue (d = 0.55; ±0.11), stress (d = 0.29; ±0.07), mood (d = 0.37; ±0.09), and PRS (d = 0.36; ±0.09). The results indicate that an athlete's perceptions of sleep are associated with deviations in well-being measures and should be used as an input to the monitoring process rather than as part of the outcome well-being score. The sleep index is suggested as a potential input because it provides information on both the duration and quality of the sleep experienced.

The Use of Upper-Body Intermittent Sequential Pneumatic Compression Arm Sleeves on Recovery From Exercise in Wheelchair Athletes

OBJECTIVE

The aim of the current study was to investigate the efficacy of an upper-body intermittent sequential pneumatic compression device on recovery after wheelchair team sport activity.

DESIGN

Eleven well-trained wheelchair basketball and rugby athletes (male, 8; female, 3; mean ± SD age = 33 ± 10 yrs) performed a series of performance measures pre-exercise, postexercise, and postrecovery (grip strength, pressure-to-pain threshold, medicine ball throw, wheelchair sprints, repeated sprints). Subjective muscle soreness and fatigue measurements were taken at the same time points as performance tests, with an additional 24-hr postrecovery measure. Participants completed two recovery trials, separated by 1 wk, of either passive recovery (control) or 20 mins of wearing recovery arm sleeves (intermittent sequential pneumatic compression) applied to both arms.

RESULTS

No statistically significant differences were found between trials for any of the performance or perceptual measures (P > 0.05). However, effect size analysis revealed a moderate decrease (d = -0.67) from postexercise to postrecovery for muscle fatigue in favor of intermittent sequential pneumatic compression. A large decrease (d = -0.96) in muscle soreness was also found after exercise to 24 hrs after recovery in favor of intermittent sequential pneumatic compression over control.

CONCLUSIONS

Intermittent sequential pneumatic compression may provide some benefit for perceptual recovery measures immediately after and 24 hrs after a high-intensity wheelchair activity with negligible effects on performance recovery.

Player Wellness (Soreness and Stress) and Injury in Elite Junior Australian Football Players Over 1 Season

Purpose: To investigate the association between player wellness and injury in elite junior Australian football players over 1 competitive season. Methods: Prospective cohort study. Elite junior Australian football players (N = 196, average age = 17.7 y, range = 16–18 y) were recruited in the under-18 state league competition in Victoria, Australia. They recorded their wellness (sleep, fatigue, soreness, stress, and mood) according to a 5-point Likert scale 3 times weekly, with injuries (missed match/training session) entered into an online sport-injury surveillance system. A logistic generalized estimating equation was used to examine the association (expressed as odds ratio [OR]) between wellness and injury (yes/no). Results: Soreness was associated with injury at each time point across the week, with the strongest association evident for soreness reported 6 d postmatch (OR = 1.30; 95% confidence interval [CI], 1.17–1.44; P < .001). Stress and injury were associated with injury for average stress values across the week, as well as specifically on day 1 postmatch (OR = 1.10; 95% CI, 1.01–1.21; P = .038). Mood reported in the middle of the week (3 d postmatch) was associated with injury (OR = 0.87; 95% CI, 0.78–0.97; P = .014), as was fatigue (OR = 1.10; 95% CI, 1.00–1.22; P = .044). Conclusions: This study demonstrates key associations between wellness and injury in elite junior Australian football, specifically soreness, stress, fatigue, and mood. Monitoring strategies help identify injury-risk profiles, which can help decision makers (coaches or medical staff) intervene when relevant to reduce injury risk.

Managing Load to Optimize Well-Being and Recovery During Short-Term Match Congestion in Elite Basketball

In elite basketball, players are exposed to intensified competition periods when participating in both national and international competitions. How coaches manage training between matches and in reference to match scheduling for a full season is not yet known.

PURPOSE

First, to compare load during short-term match congestion (ie, ≥2-match weeks) with regular competition (ie, 1-match weeks) in elite male professional basketball players. Second, to determine changes in well-being, recovery, neuromuscular performance, and injuries and illnesses between short-term match congestion and regular competition.

METHODS

Sixteen basketball players (age 24.8 [2.0] y, height 195.8 [7.5] cm, weight 94.8 [14.0] kg, body fat 11.9% [5.0%], VO2max 51.9 [5.3] mL·kg-1·min-1) were monitored during a full season. Session rating of perceived exertion (s-RPE) was obtained, and load was calculated (s-RPE × duration) for each training session or match. Perceived well-being (fatigue, sleep quality, general muscle soreness, stress levels, and mood) and total quality of recovery were assessed each training day. Countermovement jump height was measured, and a list of injuries and illnesses was collected weekly using the adapted Oslo Sports Trauma Research Center Questionnaire on Health Problems.

RESULTS

Total load (training sessions and matches; P < .001) and training load (P < .001) were significantly lower for ≥2-match weeks. Significantly higher well-being (P = .01) and less fatigue (P = .001) were found during ≥2-match weeks compared with 1-match weeks.

CONCLUSION

Total load and training load were lower during short-term match congestion compared with regular competition. Furthermore, better well-being and less fatigue were demonstrated within short-term match congestion. This might indicate that coaches tend to overcompensate training load in intensified competition.

No Influence of Prematch Subjective Wellness Ratings on External Load During Elite Australian Football Match Play

PURPOSE

To determine whether there is an association between external match load and contextual factors on subjective wellness in the days before and after Australian Rules football match play.

METHODS

A total of 34 elite male Australian football players completed a subjective wellness questionnaire in the days leading into the match (-3, -2, and -1 d), the day of (match day), and the days after each match (+3, +2, and +1 d). Players subjectively rated each item (mood, energy, stress, leg heaviness, muscle soreness, sleep quality, hours slept, and total wellness [a sum of the total response score]) on a visual analog scale ranging from 1 to 10, with 1 representing the negative end of the continuum. External load during competitive matches was quantified using accelerometer-derived PlayerLoad, and running activity was quantified using global positioning system technology across 2 competitive seasons. The relationships between perceptions of wellness (within-individual z score), external match load, and contextual factors (match result, match location, and between-matches recovery duration) were analyzed using linear mixed models.

RESULTS

Mixed-effect linear models revealed trivial effects of match-day wellness z score on subsequent external match load metrics. Match result (win) and PlayerLoad in the anteroposterior vector (au·min-1) were associated with an increased (estimate ± SE: 0.30 ± 0.13 z score) and reduced subjective wellness (-0.15 ± 0.06 z score), respectively.

CONCLUSION

The results of this study suggest that prematch perceived wellness does not relate to external match load in elite Australian football players. The between-matches microcycle length appears to be sufficient to restore perceived wellness to values that do not affect the subsequent external match loads.

The Reliability of Neuromuscular and Perceptual Measures Used to Profile Recovery, and the Time-Course of such Responses following Academy Rugby League Match-Play

In professional academy rugby league (RL) players, this two-part study examined; A) the within- and between-day reliability of isometric mid-thigh pulls (IMTP), countermovement jumps (CMJ), and a wellness questionnaire (n = 11), and B) profiled the responses with acceptable reliability (no between-trial differences and between-day coefficient of variation (CV) ≤10% and intraclass correlation coefficient (ICC) ≥0.8) for 120 h (baseline: -3, +24, +48, +72, +96, +120 h) following RL match-play (n = 10). In part A, force at 200, and 250 ms, and peak force (PF) demonstrated acceptable within- (CV%: 3.67-8.41%, ICC: 0.89-0.93) and between-day (CV%: 4.34-8.62%, ICC: 0.87-0.92) reliability for IMTP. Most CMJ variables demonstrated acceptable within-day reliability (CV%: 3.03-7.34%, ICC: 0.82-0.98), but only six (i.e., flight-time, PF, peak power (PP), relative PP, velocity at take-off (VTO), jump-height (JH)) showed acceptable between-day reliability (CV%: 2.56-6.79%, ICC: 0.83-0.91). Only total wellness demonstrated acceptable between-day reliability (CV%: 7.05%, ICC: 0.90) from the questionnaire. In part B, reductions of 4.75% and 9.23% (vs. baseline; 2.54 m∙s-1; 0.33 m) occurred at +24 h for CMJ VTO, and JH, respectively. Acceptable reliability was observed in some, but not all, variables and the magnitude and time-course of post-match responses were test and variable specific. Practitioners should therefore be mindful of the influence that the choice of recovery monitoring tool may have upon the practical interpretation of the data.

The Relationship Between Adductor Squeeze Strength, Subjective Markers of Recovery and Training Load in Elite Rugby Players

Tiernan, C, Lyons, M, Comyns, T, Nevill, AM, and Warrington, G. The relationship between adductor squeeze strength, subjective markers of recovery and training load in elite Rugby players. J Strength Cond Res 33(11): 2926-2931, 2019-The adductor squeeze strength test has become a popular training monitoring marker, particularly in team sports. The aim of this study was to investigate the relationship between adductor squeeze strength scores, subjective markers of recovery and training load in elite Rugby Union players, because of limited research in this area. Nineteen elite male Rugby Union players completed daily monitoring markers (adductor squeeze strength and 5 selected subjective markers of recovery), over a 10-week preseason training period. Rate of perceived exertion (RPE) was collected to determine training load (session RPE; RPE × session duration) and to calculate weekly training load. Spearman's correlation was used to analyze the relationship between adductor squeeze strength scores, subjective markers of recovery, and weekly training load. The results found that where adductor squeeze scores decreased, both perceived fatigue levels (r = -0.335; R = 11.2%; p < 0.001) and muscle soreness (r = -0.277; R = 7.7%; p < 0.001) increased. A weak correlation was found between Monday adductor squeeze strength scores and the previous week's training load (r = -0.235; R = 5.5%; p < 0.001) and Friday adductor squeeze strength scores and the same week's training load (r = -0.211; R = 4.5%; p < 0.05). These results show that adductor squeeze strength may provide coaches with a time-efficient, low-cost objective, player monitoring marker. Additionally, the combination of adductor strength squeeze, with subjective markers, perceived fatigue, and muscle soreness, and appropriately planned training load may help coaches to optimize training adaptations by determining a player's training status.

Relationships Between Training Load, Sleep Duration, and Daily Well-Being and Recovery Measures in Youth Athletes

PURPOSE

To assess the relationships between training load, sleep duration, and 3 daily well-being, recovery, and fatigue measures in youth athletes.

METHODS

Fifty-two youth athletes completed 3 maximal countermovement jumps (CMJs), a daily well-being questionnaire (DWB), the perceived recovery status scale (PRS), and provided details on their previous day's training loads (training) and self-reported sleep duration (sleep) on 4 weekdays over a 7-week period. Partial correlations, linear mixed models, and magnitude-based inferences were used to assess the relationships between the predictor variables (training and sleep) and the dependent variables (CMJ, DWB, and PRS).

RESULTS

There was no relationship between CMJ and training (r = -.09; ±.06) or sleep (r = .01; ±.06). The DWB was correlated with sleep (r = .28; ±.05, small), but not training (r = -.05; ±.06). The PRS was correlated with training (r = -.23; ±.05, small), but not sleep (r = .12; ±.06). The DWB was sensitive to low sleep (d = -0.33; ±0.11) relative to moderate; PRS was sensitive to high (d = -0.36; ±0.11) and low (d = 0.29; ±0.17) training relative to moderate.

CONCLUSIONS

The PRS is a simple tool to monitor the training response, but DWB may provide a greater understanding of the athlete's overall well-being. The CMJ was not associated with the training or sleep response in this population.

The influence of training load, exposure to match play and sleep duration on daily wellbeing measures in youth athletes

This study assessed the influence of training load, exposure to match play and sleep duration on two daily wellbeing measures in youth athletes. Forty-eight youth athletes (age 17.3 ± 0.5 years) completed a daily wellbeing questionnaire (DWB), the Perceived Recovery Status scale (PRS), and provided details on the previous day's training loads (TL) and self-reported sleep duration (sleep) every day for 13 weeks (n = 2727). Linear mixed models assessed the effect of TL, exposure to match play and sleep on DWB and PRS. An increase in TL had a most likely small effect on muscle soreness (d = -0.43;± 0.10) and PRS (d = -0.37;± 0.09). Match play had a likely small additive effect on muscle soreness (d = -0.26;± 0.09) and PRS (d = -0.25;± 0.08). An increase in sleep had a most likely moderate effect on sleep quality (d = 0.80;± 0.14); a most likely small effect on DWB (d = 0.45;± 0.09) and fatigue (d = 0.42;± 0.11); and a likely small effect on PRS (d = 0.25;± 0.09). All other effects were trivial or did not reach the pre-determined threshold for practical significance. The influence of sleep on multiple DWB subscales and the PRS suggests that practitioners should consider the recovery of an athlete alongside the training stress imposed when considering deviations in wellbeing measures.

Seasonal player wellness and its longitudinal association with internal training load: study in elite volleyball

BACKGROUND

Monitoring training load is critical to minimize the risk of overreaching, injury or illness. The purpose of this study was to assess the relationships and variance between perceived internal load and wellness status of elite male volleyball.

METHODS

Thirteen elite volleyball players were studied during a full competitive season (nine months, 237 training sessions and 37 official matches). Perceived exertion, muscle soreness, stress, fatigue and sleep quality levels were daily measured using session RPE and the Hopper Questionnaire.

RESULTS

Moderate-to-large correlations were found between weekly training load and perceived status of muscle soreness, fatigue and stress. Stronger correlations were found between weekly training loads than daily training load. Significant greater stress levels in match days than in training were found. No correlations between load and wellness were not found in the last month when players perceived higher levels of stress due to the competition.

CONCLUSIONS

The analysis of the weekly training load had a higher relationship with players' wellness status in preseason and middle of the season. In the last part of the season (final matches for the title), despite of a decrease in perceived load of last month of the season, there was an increase stress and fatigue levels. These results suggest the importance of including the impact on the competition when elite athletes are monitored. The results show the monitoring tools used may help in to characterize the training process of teams and the player's acute and chronic responses.

Wellbeing perception and the impact on external training output among elite soccer players

OBJECTIVES

The objective of the investigation was to observe the impact of player wellbeing on the training output of elite soccer players.

DESIGN

Prospective cohort design.

METHODS

Forty-eight soccer players (age: 25.3±3.1years; height: 183±7cm; mass: 72±7kg) were involved in this single season observational study across two teams. Each morning, pre-training, players completed customised perceived wellbeing questionnaires. Global positioning technology devices were used to measure external load (total distance, total high-speed running distance, high speed running, player load, player load slow, maximal velocity, maximal velocity exposures). Players reported ratings of perceived exertion using the modified Borg CR-10 scale. Integrated training load ratios were also analysed for total distance:RPE, total high speed distance:RPE player load:RPE and player load slow:RPE respectively.

RESULTS

Mixed-effect linear models revealed significant effects of wellbeing Z-score on external and integrated training load measures. A wellbeing Z-score of -1 corresponded to a -18±2m (-3.5±1.1%), 4±1m (-4.9±2.1%,) 0.9±0.1kmh^-1 (-3.1±2.1%), 1±1 (-4.6±2.9%), 25±3AU (-4.9±3.1%) and 11±0.5AU (-8.9±2.9%) reduction in total high speed distance, high speed distance, maximal velocity, maximal velocity exposures, player load and player load slow respectively. A reduction in wellbeing impacted external:internal training load ratios and resulted in -0.49±0.12mmin^-1, -1.20±0.08mmin^-1,-0.02±0.01AUmin^-1 in total distance:RPE, total high speed distance:RPE and player load slow:RPE respectively.

CONCLUSIONS

The results suggest that systematic monitoring of player wellbeing within soccer cohorts can provide coaches with information about the training output that can be expected from individual players during a training session.

Training Monitoring for Resistance Exercise: Theory and Applications

Resistance exercise is difficult to quantify owing to its inherent complexity with numerous training variables contributing to the training dose (type of exercise, load lifted, training volume, inter-set rest periods, and repetition velocity). In addition, the intensity of resistance training is often inadequately determined as the relative load lifted (% 1-repetition maximum), which does not account for the effects of inter-set recovery periods, repetition velocity, or the number of repetitions performed in each set at a given load. Methods to calculate the volume load associated with resistance training, as well as the perceived intensity of individual sets and entire training sessions have been shown to provide useful information regarding the actual training stimulus. In addition, questionnaires to subjectively assess how athletes are coping with the stressors of training and portable technologies to quantify performance variables such as concentric velocity may also be valuable. However, while several methods have been proposed to quantify resistance training, there is not yet a consensus regarding how these methods can be best implemented and integrated to complement each other. Therefore, the purpose of this review is to provide practical information for strength coaches to highlight effective methods to assess resistance training, and how they can be integrated into a comprehensive monitoring program.

Combined Carbohydrate and Protein Ingestion During Australian Rules Football Matches and Training Sessions Does Not Reduce Fatigue or Accelerate Recovery Throughout a Weeklong Junior Tournament

Lee, NA, Fell, JW, Pitchford, NW, Hall, AH, Leveritt, MD, and Kitic, CM. Combined carbohydrate and protein ingestion during Australian rules football matches and training sessions does not reduce fatigue or accelerate recovery throughout a weeklong junior tournament. J Strength Cond Res 32(2): 344-355, 2018-Australian rules football (ARF) is a physically demanding sport that can induce high levels of fatigue. Fatigue may be intensified during periods where multiple matches are played with limited recovery time. Combined carbohydrate and protein (CHO + PRO) intake during physical activity may provide performance and recovery benefits. The aim of this study was to investigate whether CHO + PRO ingestion during ARF matches and training sessions throughout a tournament would enhance performance or recovery in comparison with CHO-only ingestion. Australian rules football players (n = 21) competing in a 7-day national tournament participated in this randomized and double-blinded study. Beverages containing either CHO (n = 10) or CHO + PRO (n = 11) were provided during matches (day 1, day 4, and day 7) and training sessions (day 2 and day 3). Countermovement jumps (CMJs), ratings of muscle soreness, and autonomic function were assessed throughout the tournament. Gastrointestinal tract (GI) discomfort was measured after matches. Countermovement jump peak velocity increased in the CHO + PRO group (p = 0.01) but not in the CHO group. There were no differences in the other CMJ variables. In both groups, muscle soreness increased from days 0 and 1 to day 2 (p ≤ 0.05) but did not remain elevated. R-R intervals (time elapsed between successive peaks in QRS complexes) increased in both groups from day 1 to day 7 (mean difference = 59.85 ms, p < 0.01). Postmatch GI discomfort was not different (p > 0.05) between groups. When daily dietary protein is adequate (>1.8 g·kg·d), the ingestion of CHO + PRO during matches and training sessions throughout a tournament does not reduce muscle soreness nor have clear benefits for neuromuscular recovery or modulate autonomic function in junior ARF athletes, compared with that of CHO alone.

Monitoring of in-season neuromuscular and perceptual fatigue in youth rugby players

The purpose of this study was to examine both short- and long-term neuromuscular and perceptual fatigue in youth rugby players during a seven-week in-season mesocycle. Eleven male youth rugby players (age 16.9 ± 0.8 years) were assessed for countermovement jump (CMJ), reactive strength index (RSI) and leg stiffness to monitor neuromuscular performance, together with a well-being questionnaire to monitor perceptual fatigue. Players trained and competed throughout a seven-week block with test variables measured at baseline and 24 h pre- and post-matches played in weeks 1, 4 and 7. Players trained on average 9.7 ± 1.1 h per week and competed in 10.5 ± 1.9 games over the seven-week block. Pre- to post-match reductions were significant across all games for CMJ, RSI and well-being (all P < 0.05), ranging from likely to almost certain negative reductions. Well-being and RSI demonstrated non-significant (P < 0.05) unclear or inconsistent changes when comparing pre-match scores to baseline. Significant reductions to baseline were observed pre-match for CMJ (weeks 4 and 7) and stiffness (week 7), representing very likely to almost certain negative long-term decrements. CMJ, RSI and well-being were all sensitive to detecting post-match fatigue. Importantly, CMJ and stiffness were sensitive to detecting accumulated fatigue over a seven-week period, whereas RSI and well-being were not. Consequently, either a CMJ or leg stiffness should be monitored to detect long-term, accumulated fatigue in academy rugby players.

High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior Australian Football players assessed using the Functional Movement Screen

OBJECTIVES

The purpose of this study was to describe the prevalence of dysfunctional, asymmetrical, and painful movement in junior Australian Football players using the Functional Movement Screen (FMS).

DESIGN

Cross-sectional study.

METHODS

Elite junior male Australian Football players (n=301) aged 15-18 years completed pre-season FMS testing. The FMS consists of 7 sub-tests: deep squat, hurdle step, in-line lunge, shoulder mobility, active straight leg raise, trunk stability push-up (TSPU) and rotary stability. The shoulder mobility, TSPU, and rotary stability tests were combined with an accompanying clearing test to assess pain. Each sub-test was scored on an ordinal scale from 0 to 3 and summed to give a composite score out of 21. Composite scores ≤14 were operationally defined as indicating dysfunctional movement. Players scoring differently on left and right sides were considered asymmetrical. Players reported whether they missed any games due to injury in the preceding 22 game season.

RESULTS

Sixty percent of players (n=182) had composite scores ≤14, 65% of players (n=196) had at least one asymmetrical sub-test, and 38% of players (n=113) had at least one painful sub-test. Forty-two percent of players (n=126) missed at least one game in the previous season due to injury. Previous injury did not influence composite score (p=0.951) or asymmetry (p=0.629). Players reporting an injury during the previous season were more likely to experience pain during FMS testing (odds ratio 1.97, 95% confidence interval 1.23-3.18; p=0.005).

CONCLUSIONS

Junior Australian Football players demonstrate a high prevalence of dysfunctional, asymmetrical, and painful movement during FMS testing.

Injuries and musculoskeletal pain among Norwegian group fitness instructors

OBJECTIVE

To examine the prevalence and factors associated with instruction-related injuries and musculoskeletal pain among group fitness instructors.

DESIGN

Descriptive epidemiology study.

SETTINGS

Online survey.

PARTICIPANTS

Group fitness instructors from three fitness centre companies in Norway (n = 1473). Assessment of independent variables: questions regarding duration of working as a group fitness instructor, weekly instruction and exercise loading and modality, instruction-related injuries, musculoskeletal pain, use of alcohol, tobacco, snuff, menstrual dysfunction and disordered eating (Eating Disorder Inventory, EDI). The respondents were divided into high instruction loading (HIL), ≥5 h/w with instruction; and low instruction loading (LIL), <5 h/w with instruction).

RESULTS

The response rate was 57% (n = 837). Mean total loading (instruction and exercise) was 11.8 h/w and 6.3 h/w in the HIL and LIL groups (p < .001), respectively. The prevalence of acute (9% vs. 6%, p < .05), overuse (38% vs. 24%, p < .001) and both acute and overuse injuries (25% vs. 10%, p < .001) was higher in the HIL than in the LIL group (OR: 3.9, CI: 2.7, 5.5). The most prevalent injury locations were ankle and lower leg. The most frequent location for musculoskeletal pain was the shoulder/neck region. Factors associated with injury were instruction loading (h/w), years working as an instructor and EDI score. A high total EDI score predicted musculoskeletal pain.

CONCLUSION

The high prevalence of injuries and musculoskeletal pain suggests a need for prevention strategies in the fitness industry. There is a need for limits regarding weekly instruction loading, especially for classes with high metabolic and/or mechanical loading.

Different methods of training load quantification and their relationship to injury and illness in elite Australian football

OBJECTIVES

To compare different methods of training load (TL) quantification and their relationship to injury and illness in elite Australian footballers.

DESIGN

Prospective cohort study.

METHODS

Forty-five elite Australian footballers (mean±standard deviation: age=23.4±3.8 years) from one elite club participated in this 15 week pre-season study. TL was quantified every session for each individual using four different methods involving rating of perceived exertion (RPE). Two of these methods enabled the quantification of TL for all exercise modalities whilst two were applicable only to outdoor field activities. One- and two-weekly cumulative TL was investigated against injury and illness data using a logistic regression model where the low TL group was considered as the reference group.

RESULTS

A general trend existed across all TL methods which suggested lower odds of injury and illness in high TL groups. The one-week RPE (all) and one-week RPExDuration (all) methods detected reduced odds of injury in high TL groups compared to low TL groups (p<0.05, OR=0.199-0.202). Similarly, the one-week RPE (field) method identified lower illness odds in the high TL groups (p<0.05, OR=0.083-0.182).

CONCLUSIONS

Higher TL appeared to provide a protective effect against both injury and illness. The inclusion of duration in the quantification of TL via RPE did not improve the ability of RPE to predict change in odds of injury or illness.

Improving the value of fitness testing for football

One of the challenges for sports scientists working in football is to balance the needs for routine fitness testing with daily fatigue and well-being monitoring to best manage the physical preparation of players. In this commentary, the authors examine contemporary issues of fitness testing in football to identify ways of improving the value of routine testing and monitoring. A testing program must be well planned and organized to ensure that the results are useful. Different tests can be employed for younger and older players. A rigorous approach to analysis and interpretation of results is desirable, and database management must address both short- and long-term requirements of players, staff, and programs.