Academy for Sports Excellence

Doha, Qatar

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Doha, Qatar
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Buchheit M.,Academy for Sports Excellence | Buchheit M.,Physiology Unit | Laursen P.B.,High Performance Sport New Zealand | Laursen P.B.,Auckland University of Technology
Sports Medicine | Year: 2013

High-intensity interval training (HIT), in a variety of forms, is today one of the most effective means of improving cardiorespiratory and metabolic function and, in turn, the physical performance of athletes. HIT involves repeated short-to-long bouts of rather high-intensity exercise interspersed with recovery periods. For team and racquet sport players, the inclusion of sprints and all-out efforts into HIT programmes has also been shown to be an effective practice. It is believed that an optimal stimulus to elicit both maximal cardiovascular and peripheral adaptations is one where athletes spend at least several minutes per session in their 'red zone,' which generally means reaching at least 90 % of their maximal oxygen uptake ( VO2max). While use of HIT is not the only approach to improve physiological parameters and performance, there has been a growth in interest by the sport science community for characterizing training protocols that allow athletes to maintain long periods of time above 90 % of VO2max (T@VO2max). In addition to T@VO2max, other physiological variables should also be considered to fully characterize the training stimulus when programming HIT, including cardiovascular work, anaerobic glycolytic energy contribution and acute neuromuscular load and musculoskeletal strain. Prescription for HIT consists of the manipulation of up to nine variables, which include the work interval intensity and duration, relief interval intensity and duration, exercise modality, number of repetitions, number of series, as well as the between-series recovery duration and intensity. The manipulation of any of these variables can affect the acute physiological responses to HIT. This article is Part I of a subsequent II-part review and will discuss the different aspects of HIT programming, from work/relief interval manipulation to the selection of exercise mode, using different examples of training cycles from different sports, with continued reference to T@VO2max and cardiovascular responses. Additional programming and periodization considerations will also be discussed with respect to other variables such as anaerobic glycolytic system contribution (as inferred from blood lactate accumulation), neuromuscular load and musculoskeletal strain (Part II). © Springer International Publishing Switzerland 2013.


Buchheit M.,Academy for Sports Excellence | Laursen P.B.,High Performance Sport New Zealand | Laursen P.B.,Auckland University of Technology
Sports Medicine | Year: 2013

High-intensity interval training (HIT) is a well-known, time-efficient training method for improving cardiorespiratory and metabolic function and, in turn, physical performance in athletes. HIT involves repeated short (<45 s) to long (2-4 min) bouts of rather high-intensity exercise interspersed with recovery periods (refer to the previously published first part of this review). While athletes have used 'classical' HIT formats for nearly a century (e.g. repetitions of 30 s of exercise interspersed with 30 s of rest, or 2-4-min interval repetitions ran at high but still submaximal intensities), there is today a surge of research interest focused on examining the effects of short sprints and all-out efforts, both in the field and in the laboratory. Prescription of HIT consists of the manipulation of at least nine variables (e.g. work interval intensity and duration, relief interval intensity and duration, exercise modality, number of repetitions, number of series, between-series recovery duration and intensity); any of which has a likely effect on the acute physiological response. Manipulating HIT appropriately is important, not only with respect to the expected middle- to long-term physiological and performance adaptations, but also to maximize daily and/or weekly training periodization. Cardiopulmonary responses are typically the first variables to consider when programming HIT (refer to Part I). However, anaerobic glycolytic energy contribution and neuromuscular load should also be considered to maximize the training outcome. Contrasting HIT formats that elicit similar (and maximal) cardiorespiratory responses have been associated with distinctly different anaerobic energy contributions. The high locomotor speed/power requirements of HIT (i.e. ≥95 % of the minimal velocity/power that elicits maximal oxygen uptake [v/p ̇V ̇ O2max] to 100 % of maximal sprinting speed or power) and the accumulation of high-training volumes at high-exercise intensity (runners can cover up to 6-8 km at v ̇ V ̇ O2max per session) can cause significant strain on the neuromuscular/musculoskeletal system. For athletes training twice a day, and/or in team sport players training a number of metabolic and neuromuscular systems within a weekly microcycle, this added physiological strain should be considered in light of the other physical and technical/tactical sessions, so as to avoid overload and optimize adaptation (i.e. maximize a given training stimulus and minimize musculoskeletal pain and/or injury risk). In this part of the review, the different aspects of HIT programming are discussed, from work/relief interval manipulation to HIT periodization, using different examples of training cycles from different sports, with continued reference to the cardiorespiratory adaptations outlined in Part I, as well as to anaerobic glycolytic contribution and neuromuscular/musculoskeletal load. © 2013 Springer International Publishing Switzerland.


Billaut F.,Institute national du sport du Quebec | Buchheit M.,Academy for Sports Excellence
Scandinavian Journal of Medicine and Science in Sports | Year: 2013

This study examined the influence of muscle deoxygenation and reoxygenation on repeated-sprint performance via manipulation of O2 delivery. Fourteen team-sport players performed 10 10-s sprints (30-s recovery) under normoxic (NM: FIO2 0.21) and acute hypoxic (HY: FIO2 0.13) conditions in a randomized, single-blind fashion and crossover design. Mechanical work was calculated and arterial O2 saturation (SpO2) was estimated via pulse oximetry for every sprint. Muscle deoxyhemoglobin concentration ([HHb]) was monitored continuously by near-infrared spectroscopy. Differences between NM and HY data were analyzed for practical significance using magnitude-based inferences. HY reduced SpO2 (-10.7±1.9%, with chances to observe a higher/similar/lower value in HY of 0/0/100%) and mechanical work (-8.2±2.1%; 0/0/100%). Muscle deoxygenation increased during sprints in both environments, but was almost certainly higher in HY (12.5±3.1%, 100/0/0%). Between-sprint muscle reoxygenation was likely more attenuated in HY (-11.1±11.9%; 2/7/91%). The impairment in mechanical work in HY was very largely correlated with HY-induced attenuation in muscle reoxygenation (r=0.78, 90% confidence limits: 0.49; 0.91). Repeated-sprint performance is related, in part, to muscle reoxygenation capacity during recovery periods. These results extend previous findings that muscle O2 availability is important for prolonged repeated-sprint performance, in particular when the exercise is taken in hypoxia. © 2013 John Wiley & Sons A/S.


Buchheit M.,Academy for Sports Excellence | Buchheit M.,University of Picardie Jules Verne
International Journal of Sports Medicine | Year: 2012

To examine the respective associations between indices of aerobic fitness, metabolic control and locomotor function and repeated sprint-performance, 61 team sport players performed: a repeated-sprint sequence (RSS), an incremental test to exhaustion to determine maximal oxygen uptake (VO 2max) and peak incremental test speed (Inc. test speed), and 2-4 submaximal runs to determine the time constant of the primary phase of VO 2 kinetics at exercise onset (VO 2τ on) and cessation (VO 2τ off). The best (RS best) sprint times and mean sprint times (RS mean) and the percent sprint decrement (%Dec) were calculated. RS mean was almost perfectly correlated with RS best (r=0.92;90%CL(0.88;0.95)), largely correlated with Inc. test speed (r=-0.71;90%CL(-0.79;-0.59)) and moderately correlated with VO 2max (r=-0.58;90%CL(-0.70;-0.43)); the correlations with VO 2τ on or VO 2τ off were unclear. For%Dec, the correlations with Inc. test speed, VO 2max and VO 2τ on were moderate (r=-0.41;90%CL(-0.56;-0.23)), small (r=-0.26;90%CL(-0.43;-0.06)) and small (r=0.28;90%CL(0.09;0.46)), respectively. Stepwise multiple regression analyses showed that the only significant predictors of RS mean were RS best and Inc. test speed (r 2=0.88). Inc. test speed and RSbest were also the only significant predictors of %Dec (r 2=0.26). Present results obtained in a large sample of team sport players highlight that locomotor factors (i.e., RS best and Inc. test speed) show much larger associations with repeated-sprint performance than VO 2max and VO 2 kinetics. © Georg Thieme Verlag KG Stuttgart - New York.


Buchheit M.,Academy for Sports Excellence | Simpson B.M.,Academy for Sports Excellence | Mendez-Villanueva A.,Academy for Sports Excellence
International Journal of Sports Medicine | Year: 2013

The aim of this study was to examine in highly-trained young soccer players whether substantial changes in either maximal sprinting speed (MSS) or maximal aerobic speed (as inferred from peak incremental test speed, V Vam-Eval) can affect repeated high-intensity running during games. Data from 33 players (14.5±1.3 years), who presented substantial changes in either MSS or VVam-Eval throughout 2 consecutive testing periods (∼3 months) were included in the final analysis. For each player, time-motion analyses were performed using a global positioning system (1-Hz) during 2-10 international club games played within 1-2 months from/to each testing period of interest (n for game analyzed=109, player-games=393, games per player per period=4±2). Sprint activities were defined as at least a 1-s run at intensities higher than 61% of individual MSS. Repeated-sprint sequences (RSS) were defined as a minimum of 2 consecutive sprints interspersed with a maximum of 60 s of recovery. Improvements in both MSS and VVam-Eval were likely associated with a decreased RSS occurrence, but in some positions only (e. g., - 24% vs. - 3% for improvements in MSS in strikers vs. midfielders, respectively). The changes in the number of sprints per RSS were less clear but also position-dependent, e. g., +7 to +12% for full-backs and wingers, - 5 to - 7% for centre-backs and midfielders. In developing soccer players, changes in repeated-sprint activity during games do not necessarily match those in physical fitness. Game tactical and strategic requirements are likely to modulate on-field players' activity patterns independently (at least partially) of players' physical capacities. © Georg ThiemeVerlag KG Stuttgart. New York.


Buchheit M.,Academy for Sports Excellence | Mendez-Villanueva A.,Academy for Sports Excellence
Journal of Sports Sciences | Year: 2013

The aim of the study was to examine supramaximal intermittent running performance in highly-trained young soccer players, with regard to age and locomotor profile. Twenty-seven Under 14, 19 U16 and 16 U18 highly-trained soccer players performed an incremental intermittent running test (30-15 Intermittent Fitness Test) to assess supramaximal intermittent running performance (VIFT), an incremental running test to estimate maximal aerobic speed (VVam-Eval) and a 40-m sprint to estimate maximal sprinting speed (MSS). U16 and U18 presented very likely greater VIFT (19.2 ± 0.9, 19.7 ± 1.0 vs. 17.4 ± 0.9 km · h-1) and VVam-Eval (16.2 ± 0.9, 16.7 ± 1.0 vs. 14.6 ± 0.9 km · h-1) than U14, while there was no clear difference between U16 and U18. MSS (25.1 ± 1.6, 29.3 ± 1.6 and 31.0 ± 1.1 km · h-1 for U14, U16 and U18) was very likely different between all groups. When data were pooled together, VIFT was very largely correlated with VVam-Eval and MSS (overall r =0.89, partial r = 0.74 and 0.29, respectively). Within-age group correlations showed that the older the players, the greater the magnitude of the correlations between VIFT and VVam-Eval (r = 0.67, 0.73 and 0.87). In conclusion, the major predictors of VIFT were, in order of importance, VVam-Eval and MSS; however, the older the players, the greater the correlations with VVam-Eval. © 2013 Taylor & Francis.


Buchheit M.,Academy for Sports Excellence
European Journal of Applied Physiology | Year: 2010

In this study, the performance and selected physiological responses to team-sport specific repeated-sprint and jump sequence were investigated. On four occasions, 13 team-sport players (22 ± 3 year) performed alternatively six repeated maximal straight-line or shuttle-sprints interspersed with a jump ([RS+j, 6 × 25 m] or [RSS+j, 6 × (2 × 12.5 m)]) or not ([RS, 6 × 25 m] or [RSS, 6 × (2 × 12.5 m)]) within each recovery period. Mean running time, rate of perceived exertion (RPE), pulmonary oxygen uptake ( $$ \dot{V} $$ O2), blood lactate ([La]b), and vastus lateralis deoxygenation ([HHb]) were obtained for each condition. Mean sprint times were greater for RS+j versus RS (4.14 ± 0.17 vs. 4.09 ± 0.16 s, with the qualitative analysis revealing a 82% chance of RS+j times to be greater than RS) and for RSS+j versus RSS (5.43 ± 0.18 vs. 5.29 ± 0.17 s; 99% chance of RSS+j to be >RSS). The correlation between sprint and jump abilities were large-to-very-large, but below 0.71 for RSSs. Jumps increased RPE (Cohen's d ± 90% CL: +0.7 ± 0.5; 95% chance for RS+j > RS and +0.7 ± 0.5; 96% for RSS+j > RSS), $$ \dot{V} $$ O 2 (+0.4 ± 0.5; 80% for RS+j > RS and +0.5 ± 0.5; 86% for RSS+j > RSS), [La]b (+0.5 ± 0.5; 59% for RS+j > RS and +0.2 ± 0.5; unclear for RSS+j > RSS), and [HHb] (+0.5 ± 0.5; 86% for RS +j > RS and +0.5 ± 0.5; 85% for RSS+j > RSS). To conclude, repeated-sprint and jump abilities could be considered as specific qualities. The addition of a jump within the recovery periods during repeated-sprint running sequences impairs sprinting performance and might be an effective training practice for eliciting both greater systemic and vastus lateralis physiological loads. © 2010 Springer-Verlag.


Buchheit M.,Academy for Sports Excellence | Mendez-Villanueva A.,Academy for Sports Excellence
Journal of Sports Sciences | Year: 2013

The purpose of this study was to assess both short-term reliability and long-term stability of anthropometric and physical performance measures in highly-trained young soccer players in relation to age and maturation. Data were collected on 80 players from an academy (U13-U18, pre- (n = 14), circum- (n = 32) and post- (n = 34) estimated peak height velocity, PHV). For the reliability analysis, anthropometric and performance tests were repeated twice within a month. For the stability analysis, these tests were repeated 12 times over a 4-year period in 10 players. Absolute reliability was assessed with the typical error of measurement, expressed as a coefficient of variation (CV). Relative reliability and long-term stability were assessed using the intraclass correlation coefficient (ICC). There was no clear age or maturation effect on either the CVs or ICCs: e.g., Post-PHV vs. Pre-PHV: effect size = -0.37 (90% confidence limits (CL):-1.6;0.9), with chances of greater/similar/lower values of 20/20/60%. For the long-term stability analysis, ICCs varied from 0.66 (0.50;0.80) to 0.96 (0.93;0.98) for 10-m sprint time and body mass, respectively. The short-term reliability of anthropometry and physical performance measures is unlikely to be affected by age or maturation. However, some of these measures are unstable throughout adolescence, which questions their usefulness in a talent identification perspective. © 2013 Taylor & Francis.


Buchheit M.,Academy for Sports Excellence | Mendez-Villanueva A.,Academy for Sports Excellence
Journal of Sports Sciences | Year: 2014

The aim of this study was to examine the effects of changes in maximal aerobic (MAS) and sprinting (MSS) speeds and the anaerobic reserve (ASR) on repeated-sprint performance. Two hundred and seventy highly-trained soccer players (14.5 ± 1.6 year) completed three times per season (over 5 years) a maximal incremental running test to approach MAS, a 40-m sprint with 10-m splits to assess MSS and a repeated-sprint test (10 × 30-m sprints), where best (RSb) and mean (RSm) sprint times, and percentage of speed decrement (%Dec) were calculated. ASR was calculated as MSS-MAS. While {increment}RSb were related to {increment}MSS and {increment}body mass (r2 = 0.42, 90%CL[0.34;0.49] for the overall multiple regression, n = 334), {increment}RSm was also correlated with {increment}MAS and {increment}sum of 7 skinfolds (r2 = 0.43 [0.35;0.50], n = 334). There was a small and positive association between {increment}%Dec and {increment}MAS (r2 = 0.02 [-0.07;0.11], n = 334). Substantial {increment}MSS and {increment}MAS had a predictive value of 70 and 55% for {increment}RSm, respectively. Finally, {increment}ASR per se was not predictive of {increment}RSm (Cohen's = +0.8 to -0.3 with increased ASR), but the greater magnitude of {increment}RSm improvement was observed when MSS, MAS and ASR increased together (0.8 vs. +0.4 with ASR increased vs. not, additionally to MSS and MAS). Low-cost field tests aimed at assessing maximal sprinting and aerobic speeds can be used to monitor {increment}RS performance. © 2014 Taylor & Francis.


Buchheit M.,Academy for Sports Excellence | Mendez-Villanueva A.,Academy for Sports Excellence
Journal of Sports Sciences | Year: 2014

The aim of the present study was to compare, in 36 highly trained under-15 soccer players, the respective effects of age, maturity and body dimensions on match running performance. Maximal sprinting (MSS) and aerobic speeds were estimated. Match running performance was analysed with GPS (GPSport, 1 Hz) during 19 international friendly games (n = 115 player-files). Total distance and distance covered >16 km h-1 (D > 16 km h-1) were collected. Players advanced in age and/or maturation, or having larger body dimensions presented greater locomotor (Cohen's d for MSS: 0.5-1.0, likely to almost certain) and match running performances (D > 16 km h-1: 0.2-0.5, possibly to likely) than their younger, less mature and/or smaller teammates. These age-, maturation- and body size-related differences were of larger magnitude for field test measures versus match running performance. Compared with age and body size (unclear to likely), maturation (likely to almost certainly for all match variables) had the greatest impact on match running performance. The magnitude of the relationships between age, maturation and body dimensions and match running performance were position-dependent. Within a single age-group in the present player sample, maturation had a substantial impact on match running performance, especially in attacking players. Coaches may need to consider players' maturity status when assessing their on-field playing performance. © 2014 Taylor & Francis.

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