The physiological consequences of acceleration during shuttle running

Speed Effects on the Accuracy of Heart Rate as Oxygen-Uptake Indicator in Short-Distance Shuttle Running

Purpose: Despite the accuracy of heart rate (HR) as an indicator of the aerobic engagement has been evaluated in several intermittent on-court activities, its validity as an oxygen uptake (V ˙ O 2 ) indicator during shuttle running over short paths remains uncertain. Moreover, it is unclear whether speed may affect such validity. This study evaluated the HR ability in estimating the V ˙ O 2 during 5-m shuttle running at different speeds. Methods: V ˙ O 2 and HR of 12 physically active young men were recorded during an incremental forward running (FW) protocol and a 5-m shuttle test at 50%, 60%, and 75% of maximal aerobic speed (MAS). Slope and intercept of the relationship between HR and V ˙ O 2 (HR/V ˙ O 2 ) were individually determined, in both protocols. The HR measured during the shuttle test was used in the FW HR/V ˙ O 2 to estimate V ˙ O 2 at each shuttle speed. A paired Student's t-test compared slopes and intercepts of the two HR/V ˙ O 2 . A two-way RM-ANOVA and an equality test examined, respectively, the differences and the equality between measured and estimated V ˙ O 2 . Lastly, a Bland-Altman plot described the accuracy and precision of the estimated V ˙ O 2 at each shuttle intensity. Results: Slopes and intercepts of the HR/V ˙ O 2 appeared not different between FW and shuttle running. At 50%MAS, HR underestimated the V ˙ O 2 (~7%), whereas returned accurate values at the two higher velocities, although with high variability (±18%). Conclusions: When using HR as V ˙ O 2 indicator during shuttle running over short paths, a separated analysis of the HR validity as V ˙ O 2 indicator is recommended especially when administering different exercise intensities.

Physical Impact of a Typical Training Session with Different Volumes on the Day Preceding a Match in Academy Soccer Players

French academies almost all implement reactivity drills and small-sided games (SSG) the day preceding a match (MD-1). The present study aimed to determine the physical impact of different training durations on MD-1 on the subsequent matchday performance (MD). Eleven elite U19 academy soccer players conducted three typical training sessions lasting 45 min (TS45), 60 min (TS60) and 75 min (TS75) on MD-1. During TS60, warm-up, reactivity and SSG were 10, 15 and 24 min, respectively, plus coaches' feedback or water breaks. Durations of all training components decreased by 25% for TS45 and increased by 25% for TS75. Tests were conducted on MD-4 (CONTROL) and MD before the match (TEST). Tests consisted of a counter movement jump (CMJ), 20 m sprint, Illinois agility test (IAT) and Hooper questionnaire. CONTROL values were similar over the three experimental conditions. TEST on MD revealed greater CMJ for TS45 (42.7 ± 5.1 cm) compared to TS60 (40.5 ± 5.5 cm, p = 0.032) and TS75 (40.9 ± 5.7 cm, p = 0.037). 20 m time was lower for TS45 (3.07 ± 0.10 s, p < 0.001) and TS60 (3.13 ± 0.10 s, p = 0.017) compared to TS75 (3.20 ± 0.10 s). IAT time was lower on TS45 (14.82 ± 0.49 s) compared to TS60 (15.43 ± 0.29 s, p < 0.001) and TS75 (15.24 ± 0.33 s, p = 0.006). Furthermore, the Hooper index was lower at TEST for TS45 (7.64 ± 1.50) compared to TS60 (11.00 ± 3.49, p = 0.016) and TS75 (9.73 ± 2.41, p = 0.016), indicating a better readiness level. We concluded that, as training session duration increases, performance decreases on MD. A 45 min training session including reactivity and SSG exercises is therefore recommended on MD-1.

Effects of congested match periods on acceleration and deceleration profiles in professional soccer

The aim of the present study was to analyse the influence of congested periods of matches on the acceleration (Acc) and deceleration (Dec) profiles of elite soccer players. Twenty-three elite male professional soccer players participated in the study across 31 official matches. Assessed periods included: (i) congested periods (three to four days between games), and (ii) non-congested periods (more than four days between games). Physical activity during matches was recorded during games using a 10Hz global positioning system device, coupled with a 100 Hz accelerometer, and was analysed according to the periods. Maximal Acc- (73.2 ± 20.3 vs. 84.918.5 m), high Acc- (244.0 ± 49.5 vs. 267.0 ± 37.8 m), maximal Dec- (139.0 ± 44.8 vs. 152.039.3 m) and the total decelerating- distance (5132 ± 690 vs. 5245 ± 552 m) were lower in congested than in non-congested periods (p < 0.05, effect size 0.31–0.70). Neither a main effect of playing position nor a period*playing position interaction on Acc and Dec were observed (p > 0.05). It was concluded that Acc and Dec match activities were significantly affected during congested periods compared to non-congested highlighting a possible fatigue accumulation being responsible for the observed decrement in physical activity. Monitoring Acc and Dec metrics throughout particular periods of congested fixtures amongst professional soccer teams is advised and may be a way to assess physical and fatigue status.

Physiological characteristics and acute fatigue associated with position-specific speed endurance soccer drills: production vs maintenance training

Objective: The study aimed to compare the physiological characteristics and acute fatigue associated with position-specific speed endurance production (SEP) and maintenance (SEM) soccer drills.Methods: Twenty male soccer players performed a position specific drill consisting of 8 exercise bouts each lasting ~30 s interspersed by 150 s (SEP) and 60 s (SEM) of passive recovery. A selection of players (n = 10) completed neuromuscular assessments pre and post drill.Results: Players covered greater high speed (12%), very high speed (49%) and sprint (218%) running distances in SEP (P < 0.05, ES: 0.51-0.80). SEP resulted in greater peak (7%) and average (10%) running speeds (P < 0.01, ES: 0.70-0.93). Mean and peak heart rate responses were greater in SEM (4-10%, P < 0.01, ES: 0.97-1.84) whilst blood lactate concentrations were higher following SEP (6%, P < 0.05, ES: 0.42). Reductions in vertical countermovement jump height were more pronounced immediately after SEP (2%, P < 0.05, ES: 0.36) but 24 h post SEM (4%, P < 0.05, ES: 0.52). Horizontal countermovement jump performance was reduced immediately post SEP and SEM (3-5%, P < 0.01, ES: 0.22-0.38) and 24 h post SEM (4%, ES: 0.32).Conclusion: The data demonstrate that position-specific SEP and SEM drills overload different physiological indices and induce small impairments in some neuromuscular measures.

Quantifying Accelerations and Decelerations in Elite Women Soccer Players during Regular In-Season Training as an Index of Training Load

Accelerations (ACC) and decelerations (DEC) are important and frequent actions in soccer. We aimed to investigate whether ACC and DEC were good indicators of the variation of training loads in elite women soccer players. Changes in the training load were monitored during two different selected weeks (considered a “low week” and a “heavy week”) during the in-season. Twelve elite soccer women playing in the French first division wore a 10-Hz Global Positioning System unit recording total distance, distance within speed ranges, sprint number, ACC, DEC, and a heart rate monitor during six soccer training sessions and rated their perceived exertion (RPE). They answered the Hooper questionnaire (sleep, stress, fatigue, DOMS) to get an insight of their subjective fitness level at the start (Hooper S) and at the end of each week (Hooper E). A countermovement jump (CMJ) was also performed once a week. During the heavy week, the training load was significantly greater than the low week when considering number of ACC >2 m·s⁻² (28.2 ± 11.9 vs. 56.1 ± 10.1, p < 0.001) and number of DEC < −2 m·s⁻² (31.5 ± 13.4 vs. 60.9 ± 14.4, p < 0.001). The mean heart rate percentage (HR%) (p < 0.05), RPE (p < 0.001), and Hooper E (p < 0.001) were significantly greater during the heavy week. ACC and DEC showed significant correlations with most outcomes: HR%, total distance, distance per min, sprint number, Hooper index of Hooper E, DOMS E, Fatigue E, RPE, and session RPE. We concluded that, for elite women soccer players, quantifying ACC and DEC alongside other indicators seemed to be essential for a more complete training load monitoring. Indeed, it could lead to a better understanding of the reasons why athletes get fatigued and give insight into neuromuscular, rather than only energetic, fatigue.

HIIT Models in Addition to Training Load and Heart Rate Variability Are Related With Physiological and Performance Adaptations After 10-Weeks of Training in Young Futsal Players

INTRODUCTION

The present study aimed to investigate the effects of two high-intensity interval training (HIIT) shuttle-run-based models, over 10 weeks on aerobic, anaerobic, and neuromuscular parameters, and the association of the training load and heart rate variability (HRV) with the change in the measures in young futsal players.

METHODS

Eleven young male futsal players (age: 18.5 ± 1.1 years; body mass: 70.5 ± 5.7 kg) participated in this study. This pre-post study design was performed during a typical 10 weeks training period. HIIT sessions were conducted at 86% (HIIT86; n = 6) and 100% (HIIT100; n = 5) of peak speed of the FIET. Additionally, friendly and official matches, technical-tactical and strength-power training sessions were performed. Before and after the training period, all players performed the FIET, treadmill incremental, repeated sprint ability (RSA), sprint 15-m, and vertical jump tests (CMJ and SJ), and the HRV was measured. Training load (TL) was monitored using the session rating of perceived effort. Data analysis was carried out using Bayesian inference methods.

RESULTS

The HIIT86 model showed clear improvements for the peak oxygen uptake (VO2peak), peak speed in the treadmill incremental test, first and second ventilatory thresholds, RSA best and mean times, CMJ, and SJ. The HIIT100 model presented distinct advances in VO2peak, peak speed in the treadmill incremental test, RSA mean time, and CMJ. Between HIIT models comparisons showed more favorable probabilities of improvement for HIIT86 than HIIT100 model in all parameters. TL data and HIIT models strongly explained the changes in the RSA mean and best times (R 2 = 0.71 and 0.87, respectively), as well as HRV changes, and HIIT models explained positively VO2peak changes (R 2 = 0.72). All other changes in the parameters were low to moderately explained.

CONCLUSION

The HIIT86 proved to be more effective for improving aerobic, RSA, and neuromuscular parameters than HIIT100 during a typical 10-week futsal training period. So, strength and conditioning specialists prescribing shuttle-run intermittent exercises at submaximal intensities can manage the individual acceleration load imposed on athlete increasing or decreasing either the set duration or the frequency of change of direction during HIIT programming.

Application of Individualized Speed Zones to Quantify External Training Load in Professional Soccer

This study aimed to examine the interchangeability of two external training load (ETL) monitoring methods: arbitrary vs. individualized speed zones. Thirteen male outfield players from a professional soccer team were monitored during training sessions using 10-Hz GPS units over an 8-week competitive period (n = 302 observations). Low-speed activities (LSA), moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary speed zones as <14.4, 14.4–19.8, 19.8–25.1 and ≥25.2 km·h-1, and using individualized speed zones based on a combination of maximal aerobic speed (MAS, derived from the Yo-yo Intermittent recovery test level 1), maximal sprinting speed (MSS, derived from the maximal speed reached during training) and anaerobic speed reserve (ASR) as <80% MAS, 80–100% MAS, 100% MAS or 29% ASR and ≥30% ASR. Distance covered in both arbitrary and individualized methods was almost certainly correlated in all speed zones (p < 0.01; r = 0.67-0.78). However, significant differences between methods were observed in all speed zones (p < 0.01). LSA was almost certainly higher when using the arbitrary method than when using the individualized method (p < 0.01; ES = 5.47 [5.18; 5.76], respectively). Conversely, MSR, HSR and sprinting speed were higher in the individualized method than in the arbitrary method (p < 0.01; ES = 5.10 [4.82; 5.37], 0.86 [0.72; 1.00] and 1.22 [1.08; 1.37], respectively). Arbitrary and individualized methods for ETL quantification based on speed zones showed similar sensitivity in depicting player locomotor demands. However, since these methods significantly differ at absolute level (based on measurement bias), arbitrary and individualized speed zones should not be used interchangeably.

Positional Differences in Peak- and Accumulated- Training Load Relative to Match Load in Elite Football

Quantification of training and match load is an important method to personalize the training stimulus' prescription to players according to their match demands. The present study used time-motion analysis and triaxial-accelerometer to quantify and compare: a) The most demanding passages of play in training sessions and matches (5-min peaks); b) and the accumulated load of typical microcycles and official matches, by playing position. Players performance data in 15 official home matches and 11 in-season microcycles were collected for analysis. Players were divided into four different playing positions: Centre-backs, wing-backs, centre midfielders, and centre forwards. The results show that match demands were overperformed for acceleration counts (acc_counts) (131%-166%) and deceleration counts (dec_counts) (108%-134%), by all positions. However, relative to match values, training values for sprint distance (sprint_dist) and high-intensity run distance (HIR_dist) were considerably lower (36%-61% and 57%-71%) than for accelerations and decelerations. The most pronounced difference on the 5-min peaks was observed in sprints (sprint_peak), with wing-backs achieving during the microcycle only 64% of the sprint_peak in matches, while centre backs, centre midfielders, and centre forwards levelled and overperformed the match values (107%, 100%, and 107%, respectively). Differences observed across playing positions in matches and microcycles underline the lack of position specificity of common training drills/sessions adopted by coaches in elite football.

Relationship between External Load and Perceptual Responses to Training in Professional Football: Effects of Quantification Method

We examined the within-player correlation between external training load (ETL) and perceptual responses to training in a professional male football team (n = 13 outfield players) over an eight-week competitive period. ETL was collected using 10-Hz GPS, whereas perceptual responses were accessed through rating of perceived exertion (RPE) questionnaires. Moderate-speed running (MSR), high-speed running (HSR) and sprinting were defined using arbitrary (fixed) and individualised speed zones (based on maximal aerobic speed and maximal sprinting speed). When ETL was expressed as actual distance covered within the training session, perceptual responses were moderately correlated to MSR and HSR quantified using the arbitrary method (p < 0.05; r = 0.53 to 0.59). However, the magnitude of correlations tended to increase when the individualised method was used (p < 0.05; r = 0.58 to 0.67). Distance covered by sprinting was moderately correlated to perceptual responses only when the individualised method was used (p < 0.05; 0.55 [0.05; 0.83] and 0.53 [0.02; 0.82]). Perceptual responses were largely correlated to the sum of distance covered within all three speed running zones, irrespective of the quantification method (p < 0.05; r = 0.58 to 0.68). When ETL was expressed as percentage of total distance covered within the training session, no significant correlations were observed (p > 0.05). Perceptual responses to training load seem to be better associated with ETL, when the latter is adjusted to individual fitness capacities. Moreover, reporting ETL as actual values of distance covered within the training session instead of percentual values inform better about players’ perceptual responses to training load.

Integrated Framework of Load Monitoring by a Combination of Smartphone Applications, Wearables and Point-of-Care Testing Provides Feedback that Allows Individual Responsive Adjustments to Activities of Daily Living

Athletes schedule their training and recovery in periods, often utilizing a pre-defined strategy. To avoid underperformance and/or compromised health, the external load during training should take into account the individual's physiological and perceptual responses. No single variable provides an adequate basis for planning, but continuous monitoring of a combination of several indicators of internal and external load during training, recovery and off-training as well may allow individual responsive adjustments of a training program in an effective manner. From a practical perspective, including that of coaches, monitoring of potential changes in health and performance should ideally be valid, reliable and sensitive, as well as time-efficient, easily applicable, non-fatiguing and as non-invasive as possible. Accordingly, smartphone applications, wearable sensors and point-of-care testing appear to offer a suitable monitoring framework allowing responsive adjustments to exercise prescription. Here, we outline 24-h monitoring of selected parameters by these technologies that (i) allows responsive adjustments of exercise programs, (ii) enhances performance and/or (iii) reduces the risk for overuse, injury and/or illness.

Directional Change Mediates the Physiological Response to High-Intensity Shuttle Running in Professional Soccer Players

The purpose of this study was to investigate the influence that different frequencies of deceleration and acceleration actions had on the physiological demands in professional soccer players. Thirteen players were monitored via microelectromechanical devices during shuttle running protocols which involved one, three, or seven 180 degree directional changes. Heart rate exertion (HRE) (1.1 ± 0.7) and rating of perceived exertion (RPE) (5 ± 1) were significantly higher for the protocol which included seven directional changes when compared to the protocols which included one (HRE 0.5 ± 0.3, ES = 1.1, RPE 3 ± 0, ES = 2.7) or three (HRE 0.5 ± 0.2, ES = 1.1, RPE 3 ± 1, ES = 1.9) directional changes (p < 0.05). The gravitational force (g-force) as measured through accelerometry (ACC) also showed a similar trend when comparing the seven (8628.2 ± 1630.4 g) to the one (5888.6 ± 1159.1 g, ES = 1.9) or three (6526.9 ± 1257.6 g, ES = 1.4) directional change protocols (p < 0.05). The results of this study suggest that increasing the frequency of decelerations and accelerations at a high intensity running (HIR) speed alters the movement demands and elevates the physiological responses in professional players. This data has implications for the monitoring of physical performance and implementation of training drills.

Energy expenditure, metabolic power and high speed activity during linear and multi-directional running

OBJECTIVES

The purpose of the study was to compare measures of energy expenditure derived from indirect calorimetry and micro-technology, as well as high power and high speed activity during linear and multi-directional running.

DESIGN

Repeated measures.

METHODS

Twelve university standard team sport players completed a linear and multi-directional running condition. Estimated energy expenditure, as well as time at high speed (>14.4kmh^-1) and high power (>20Wkg^-1) were quantified using a 10Hz micro-technology device and compared with energy expenditure derived from indirect calorimetry.

RESULTS

Measured energy expenditure was higher during the multi-directional condition (9.0±2.0 cf. 5.9±1.4kcalmin^-1), whereas estimated energy expenditure was higher during the linear condition (8.7±2.1 cf. 6.5±1.5kcalmin^-1). Whilst measures of energy expenditure were strongly related (r>0.89, p<0.001), metabolic power underestimated energy expenditure by 52% (95% LoA: 20-93%) and 34% (95% LoA: 12-59%) during the multi-directional and linear condition, respectively. Time at high power was 41% (95% LoA: 4-92%) greater than time at high speed during the multi-directional condition, whereas time at high power was 5% (95% LoA: -17-9%) lower than time at high speed during the linear condition.

CONCLUSIONS

Estimated energy expenditure and time at high metabolic power can reflect changes in internal load. However, micro-technology cannot be used to determine the energy cost of intermittent running.

Gold Standard or Fool's Gold? The Efficacy of Displacement Variables as Indicators of Energy Expenditure in Team Sports

Over recent decades, the use of player tracking technology to monitor physical work output has become established practice in many team sports. Early tracking systems were manual in nature, relying on subjective assessments and arbitrary classifications of movement intensity. Poor spatial and temporal resolution meant that only gross displacement measures could be used to infer energy demands. However, the advent and evolution of automated systems, with higher sampling rates and improved accuracy, have enabled data collection to occur on a mass scale, and served as a catalyst for extensive research into the demands of team sport activity, including comparisons between different groups of athletes, and the effects of various interventions on performance. The inherent assumption with this research is that, based on steady-state models where energy cost is independent of speed, total distance and average speed are indicative of the amount and rate of work done, respectively. This assumption could be justified if the activity was performed at a constant speed in a straight line. However, team sport movement involves continual changes in both speed and direction, both of which increase energy cost. Accordingly, new models have emerged that incorporate both speed and acceleration to determine metabolic power. This provides a more complete measure of energy expenditure in intermittent activity, and is potentially more suitable than displacement variables for research into the demands of team sports.