Science and Application of High Intensity Interval Training – The book

A preview to: The Science and Application of High Intensity Interval Training

Release date: towards the end of 2018

L&B - Science and Application of HIT

Most of us have heard of high-intensity interval training (HIIT) – that so called time efficient training strategy we should use to improve our cardiorespiratory and metabolic health and performance. Today in fact, HIIT is considered the highest interest topic in our field. But as I’ve written, our ability to link much of the sport science research outputs derived from our academic institutions, including HIIT, into today’s elite sport practice, can often be considered limited by those it matters most to, the coaches and athletes in the trenches of high performance sport.

This past year, my colleague Paul Laursen and I have taken on the project of working towards putting a book together on the topic of HIIT and its real world application in high performance sport. The initiative stems from the popularity of a two-part literature review we wrote on the topic back in 2013 (Part I & Part II, see also the 2013 UKSCA presentation below). As shown in the infographic, Science and application of high-intensity interval training takes the reader though the history of HIIT and its traditional methods, before diving into our scientific understanding of how it can be used to gain a response in certain biological targets of importance for sport performance. From there, we break down the key components of an HIIT session (intensity, duration, recovery, etc) to learn how we can manipulate these factors to form different HIIT formats, or what we term our ‘weapons’. Our HIIT weapons can be further refined to hit the biological targets of importance, in line with the sport type, the individual, and the all-important sport context. Other important considerations covered include concurrent strength programming and health aspects, as well as load monitoring and individual response surveillance.

Most importantly, we are privileged to have gained the generous contributions of practitioners embedded within 20 high profile individual and team-based sports, who tell us precisely how they apply the science of HIIT in their practice to maximise athlete and sport performance. The detail they offer will leave the enthusiastic coach and sport scientist breathless. It is our hope that the work will inspire a future generation of sport scientists to think outside the box when it comes to high performance sport science research and HIIT application, and critically, narrow today’s void between science and practice.

Videos from the 2013 UKSCA Conference

(many thanks to them for making the link available to all)

Nb: White man before Yann Le Meur‘s Infographics 🙂


Metabolic power requirement of change of direction speed in young soccer players: not all is what it seems

Hader K, A Mendez-Villanueva , D Palazzi, S Ahmaidi and M Buchheit. Metabolic power requirement of change of direction speed in young soccer players: not all is what it seems. PlosOne, In press. Full text here


Purpose. The aims of this study were to 1) compare the metabolic power demand of straight-line and change of direction (COD) sprints including 45° or 90°-turns, and 2) examine the relation between estimated metabolic demands and muscular activity throughout the 3 phases of COD-sprints.

Methods. Twelve highly-trained soccer players performed one 25-m and three 20-m sprints, either in straight-line or with one 45º- or 90º-COD. Sprints were monitored with 2 synchronized 100-Hz laser guns to assess players’ velocities before, during and after the COD. Acceleration and deceleration were derived from changes in speed over time (Figure 1). Metabolic power was estimated based on di Prampero’s approach (2005). Electromyography amplitude (RMS) of 2 lower limb muscles was measured. The expected energy expenditure during time-adjusted straight-line sprints (matching COD sprints time) was also calculated.

Results. As shown in Figure 2, locomotor-dependant metabolic demand was largely lower with COD (90°, 142.1±15.0 compared with time-adjusted (effect size, ES = -3.0; 193.2±18.7 and non-adjusted straight-line sprints (ES = -1.7; 168.4±18.2 Metabolic power requirement was angle-dependent, moderately lower for 90º-COD vs. 45º-COD sprint (ES = -1.0; 149.5±12.9 Conversely, the RMS was slightly– (45°, ES = +0.5; +2.1%, 90% confidence limits (±3.6) for vastus lateralis muscle (VL)) to-largely (90°, ES = +1.6; +6.1 (3.3%) for VL) greater for COD-sprints. Metabolic power/RMS ratio was 2 to 4 times lower during deceleration than acceleration phases (Figure 7).

Conclusion. Present results show that COD-sprints are largely less metabolically demanding than linear sprints. This may be related to the very low metabolic demand associated with the deceleration phase during COD-sprints that may not be compensated by the increased requirement of the reacceleration phase. These results also highlight the dissociation between metabolic and muscle activity demands during COD-sprints, which questions the use of metabolic power as a single measure of running load in soccer.

Key words: Energy demand, muscular activity, electromyography amplitude, acceleration, deceleration, sprint, braking forces, running load.


Fig 1w

Fig. 1: Electromyography amplitude (RMS) of vastus lateralis and biceps femoris muscles and speed profiles during sprints with (45° or 90°) or without (i.e., straight-line, SL) one change of direction (COD). 90°25: 25-m sprint with one 90°-COD. The medial panel represents the standardized difference (Std Diff) of RMS between COD- and SL- sprints. The number of ‘*’ and ‘†’ refers to possible, likely, very likely and almost certain difference versus straight-line and 45°-COD sprints, respectively.


Fig 2

Fig. 2: Estimated energy expenditure of sprints with (45° or 90°) or without (i.e., straight-line, SL) one change of direction (COD); 90°25: 25-m sprint with one 90°-COD. The upper panel represents the standardized difference (Std Diff) between COD- and SL sprints. Since 90°25 vs. 20-m SL sprints could not be properly compared (i.e., differences in both running time and distance), their standardized difference (black circle) was not provided. The number of ‘*’ and ‘†’ refers to possible, likely, very likely and almost certain between-sprints differences versus the 45°-COD sprint trial, and within-sprint differences vs. the acceleration phase, respectively. The associated number refers to the magnitude of the difference, with 1 standing for small, 2 for moderate, 3 for large and 4 for very large magnitude.


Fig7 Ratio phases

Fig. 7: Metabolic power/electromyography amplitude (RMS) ratio during the different phases of sprints with (45° or 90°) or without (i.e., straight-line (SL)) one change of direction (COD). 90°25: 25-m sprint with one 90°-COD; BF: biceps femoris; VL: vastus lateralis. The number of ‘*’ and ‘†’ refers to possible, likely, very likely and almost certain difference versus straight-line and 45°-COD sprints, respectively. The associated number refers to the magnitude of the difference, with 1 standing for small, 2 for moderate, 3 for large and 4 for very large magnitude


Changes in repeated-sprint performance in relation to change in locomotor profile in highly-trained young soccer players

How to use changes in non soccer-specific locomotor entities (i.e., maximal aerobic and sprinting speeds) to predict changes in performance that is believed to be soccer specific (although I have my doubts too!)

Figure 1Buchheit, M. and Mendez-Villanueva, A., Changes in repeated-sprint performance in relation to change in locomotor profile in highly-trained young soccer players, J Sports Sci., 2014, In press

To examine the effects of changes in maximal aerobic (MAS) and sprinting (MSS) speeds, and the anaerobic reserve (ASR), on repeated-sprint performance, 270 highly-trained soccer players (14.5±1.6 yr) 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 ∆RSb were related to ∆MSS and ∆body mass (r2=0.42, 90%CL[0.34;0.49] for the overall multiple regression, n=334), ∆RSm was also correlated with ∆MAS and ∆sum of 7 skinfolds (r2 =0.43 [0.35;0.50], n=334). ∆%Dec was related to ∆MAS (r2=0.02 [-0.07;0.11], n=334). Substantial ∆MSS and ∆MAS had a predictive value of 70 and 55% for ∆RSm, respectively. Finally, ∆ASR per se was not predictive of ∆RSm (Cohen’s = +0.8 to -0.3 with increased ASR), but the greater magnitude of ∆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 ∆RS performance.

Key words: football association; repeated-sprint ability; maximal sprinting speed; maximal aerobic speed; anaerobic speed reserve

Programming High-intensity Training in Handball

Based on the 2-part HIT review (I and II) on HIT programming with my mate Paul Laursen, I provide in this new paper some examples on how to practically implement HIT with players, and compare the performance benefits of different HIT formats in highly-trained Handball players. Many thanks to Aspetar Journal for the nice formatting too !

Pages from Buchheit - Programming High-intensity Training in Handball


Changes of direction during high-intensity intermittent runs: neuromuscular and metabolic responses

Karim Hader, Alberto Mendez-Villanueva, Said Ahmaidi, Ben Williams and Martin
Buchheit. Changes of direction during high-intensity intermittent runs: neuromuscular and metabolic  responses. Accepted to BMC Sports Science, Medicine and Rehabilitation on 19 December 2013.

Background: The ability to sustain brief high-intensity intermittent efforts (HIE) is meant to be a major attribute for performance in team sports. Adding changes of direction to HIE is believed to increase the specificity of training drills with respect to game demands. The aim of this study was to investigate the influence of 90°-changes of direction (COD) during HIE on metabolic and neuromuscular responses.
Methods: Eleven male, team sport players (30.5±3.6 y, 81±6 kg, 180± 6cm) performed randomly HIE without (straight-line, 2x[10x 22m]) or with (2x[10x ~16.5m]) two 90°-COD. To account for the time lost while changing direction, the distance for COD runs during HIE was individually adjusted using the ratio between straight-line and COD sprints. Players also performed 2 countermovement (CMJ) and 2 drop (DJ) jumps, during and post HIE. Pulmonary oxygen uptake ( O2), quadriceps and hamstring oxygenation, blood lactate concentration (Δ[La]b), electromyography amplitude (RMS) of eight lower limb muscles and rating of perceived exertion (RPE) were measured for each condition.
Results: During HIE, CODs had no substantial effects on changes in  O2, oxygenation, CMJ and DJ performance and RPE (all differences in the changes rated as unclear). Conversely, compared with straight-line runs, COD-runs were associated with a possibly higher Δ[La]b (+9.7±10.4%, with chances for greater/similar/lower values of 57/42/0%). There was also a lower decrease in lateral gastrocnemius (-8.5±9.3%, 1/21/78) and semitendinosus (-11.9 ± 14.6%, 2/13/85) electromyography amplitude; the decrease in electromyography amplitude for the other muscles was not clearly different.
Conclusion: Adding two 90°-CODs on adjusted distance during two sets of HIE is likely to elicit equivalent decreases in CMJ and DJ height, and similar cardiorespiratory and perceptual responses, despite a lower average running speed. A fatigue-induced modification in lower limb control observed with CODs may have elicited a selective reduction of electromyography activity in hamstring muscles and may induce, in turn, a potential mechanical loss of knee stability. Therefore, changing direction during HIE might be an effective training practice 1) to manipulate some components of the acute physiological load of HIE, 2) to promote long-term COD-specific neuromuscular adaptations aimed at improving performance and knee joint stability.
Key Words: cardiorespiratory responses; neuromuscular adjustment; selective activation; knee stabilization.

Full paper available on the Journal Website (open Access)

Physiological and Performance Responses to a Training-Camp in the Heat in Professional Australian Football Players

2011-10-21 11.49.17

Sebastien Racinais, Martin Buchheit, Johann Bilsborough, Pitre C. Bourdon, Justin Cordy and Aaron J Coutts. International Journal of Sports Physiology and Performance, In press.


Purpose: To examine the physiological and performance responses to a heat-acclimatization camp in highly-trained professional team sport athletes. Methods: Eighteen male Australian Rules Football players trained for two weeks in hot ambient conditions (31-33ºC, humidity 34-50%). Players performed a laboratory-based heat-response test (24 min walk + 24 min seated; 44ºC), a YoYo Intermittent Recovery Level 2 Test (YoYoIR2; indoor, temperate environment, 23ºC) and standardized training drills (STD; outdoor, hot environment, 32ºC) at the beginning and end of the camp. Results: The heat-response test showed partial heat acclimatization (e.g., a decrease in skin temperature, heart rate and sweat sodium concentration, p<0.05). In addition, plasma volume (PV, CO-rebreathing, +2.68, 95%CI[0.83;4.53] ml·kg-1]) and distance covered during both the YoYoIR2 (+311[260;361]m) and the STD (+45.6[13.9;77.4]m) increased post camp (p<0.01). None of the performance changes showed clear correlations with PV changes (r<0.24), but the improvements in running STD distance in hot environment was correlated with changes in haematocrit during the heat-response test (r=-0.52,90%CI[-0.77;-0.12]). There was no clear correlation between the performance improvements in temperate and hot ambient conditions (r<0.26). Conclusion: Running performance in both hot and temperate environments was improved following a Football training-camp in hot ambient conditions that stimulated heat-acclimatization. However, physiological and performance responses were highly individual and the absence of correlations between physical performance improvements in hot and temperate environments suggests that their physiological basis might differ.

Keywords: acclimation; acclimatization; exercise; hot environment; temperature; football

Supramaximal Training: repeated sprints vs. high-intensity running (individualized based on VIFT)


Med Sci Sports Exerc. 2008 Feb;40(2):362-71. doi: 10.1249/mss.0b013e31815aa2ee.

Supramaximal training and postexercise parasympathetic reactivation in adolescents.


Research Laboratory, Physical Activity and Motor Control: Adaptation and Rehabilitation, Faculty of Sport Sciences, University of Picardie Jules Verne, Amiens, France.


Repeated supramaximal exercise training is an efficient means of improving both aerobic and anaerobic energy system capacities. However, the influence of different levels of supramaximal training on parasympathetic function is unknown.


To compare the effects of repeated-sprint (RS) versus high-intensity intermittent training (HIT) on performance and postexercise parasympathetic reactivation in trained adolescents.


Fifteen male adolescents (15.6 +/- 0.8 yr) were divided into two groups that performed 9 wk of either RS (repeated all-out 6-s shuttle sprints; 14-20 s of recovery; N = 8) or HIT (15- to 20-s runs at 95% of the speed reached at the end of the 30-15 intermittent fitness test (V(IFT)); 15-20 s of recovery; N = 7). Groups performed intervals twice per week and maintained similar external training programs. Before and after training, performance was assessed by the V(IFT), countermovement jump (CMJ), 10-m sprint time (10 m), mean RS ability time (RSAmean), and heart rate (HRsub) level during a 6-min submaximal (60% V(IFT)) exercise test, where parasympathetic reactivation was assessed during the recovery phase (i.e., HR recovery time constant (HRRtau) and HR variability (HRV)).


Parasympathetic function, V(IFT), and RSAmean were improved with HIT but not RS training. In contrast, changes in CMJ and HRsub were similar in both groups. A significant relationship was shown between the decrease in HRRtau and RSAmean (r = 0.62, P < 0.05; N = 15).


HIT was more effective than RS training at improving postexercise parasympathetic function and physical performance. In addition, HRRtau, which was more sensitive to training than HRV indices, seems to be a useful performance-related measurement.

Monitoring Accelerations With GPS in Football: Time to Slow Down?

 Aren’t we losing our time? GPS-derived accelerations are not as good as we wished! 😦

Here is the sled used for the tests...



Int J Sports Physiol Perform. 2013 Jul 30. [Epub ahead of print]

Monitoring Accelerations With GPS in Football: Time to Slow Down?


Physiology Unit, Football Performance and Science Department, ASPIRE Academy for Sports Excellence, Doha, Qatar.


The aim of the present study was to 1) examine the magnitude of between-GPS model differences in commonly reported running-based measures in football, 2) examine between-unit variability and 3) assess the effect of software updates on these measures. Fifty identical brand GPS units (15 SPI-proX and 35 SPI-proX2, 15 Hz, GPSports, Canberra, Australia) were attached to a custom-made plastic sled towed by a player performing simulated match running activities. GPS data collected during training sessions over 4 weeks from 4 professional football players (n = 53 files) were also analyzed before and after 2 manufacturer-supplied software updates. There were substantial differences between the different models (e.g., standardized difference for the number of acceleration >4 m.s-2 = 2.1; 90% confidence limits (1.4, 2.7), with 100% chance of a true difference). Between-unit variations ranged from 1% (maximal speed) to 56% (number of deceleration >4 m.s-2). Some GPS units measured 2 to 6 times more acceleration/deceleration occurrences than others. Software updates did not substantially affect the distance covered at different speeds or peak speed reached, but one of the updates led to large and small decreases in the occurrence of accelerations (-1.24;-1.32,-1.15) and decelerations (-0.45; -0.48,-0.41), respectively. Practitioners are advised to apply care when comparing data collected with different models or units, or when updating their software. The metrics of accelerations and decelerations show the most variability in GPS monitoring and must be interpreted cautiously.

Supramaximal intermittent running performance in relation to age and locomotor profile in highly-trained young soccer players



J Sports Sci. 2013 Jun 28. [Epub ahead of print]

Supramaximal intermittent running performance in relation to age and locomotor profile in highly-trained young soccer players.


a Aspire, Academy for Sports Excellence , Football Performance and Science Department , Doha , Qatar.


Abstract 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.