Injury rate and prevention in elite football: let’s first search within our own hearts

Buchheit M, Eirale C,  Simpson BM and Lacome M. Injury rate and prevention in elite football: let’s first search within our own hearts. BJSM, In press.



Full text here

Research and discussions about injury rates and their prevention in elite football is one of the hottest topics in the medical and sport science literature. Over the past years, there has been an explosion of the number of publications, including surveys,1 observational, retrospective or prospective2 studies, training interventions and various types of expert opinions and commentaries.3 This array of information are likely useful to improve our understanding of what the best practices may be, and in turn, increase our ability to better prepare, manage and treat players. However, a recent survey has shown that 83% of UEFA clubs do not follow evidenced-based prevention programs.1 It was also shown that hamstring injuries kept increasing over the last 13 years.2 Taken together, those two papers may suggest that the majority of elite club practitioners likely disregard research findings1 and may therefore be the one to be blamed for those increased injury rates.2

Making supporting staff and coaches responsible for those injuries is easy, especially when considering their perceived typical personality traits (i.e., so-called Type 2,4 high egos and little open-mindedness and willingness and learn – “why could they be bothered applying the new study findings?”). While this may be true sometimes, the reality is that elite club practitioners are rather often in the frontline with new treatment options and training programs. We believe therefore that there may be alternate, less naïve ways to look at those latter findings,1 2 which could suggest that club practitioners may not be as bad as they may appear from those papers. In fact, type 2-researchers4 often discard new research findings that contradict their own paradigm (confirmation bias); they may also be more prone to pursue their old research topics in the name of security and comfort,4 missing in turn potentially important advances in the field. Two examples highlighting how those attitudes have increased the disconnect and misunderstanding between research findings and real practice are discussed below.

  1. Are club injury prevention programs that bad? What if practitioners were just doing differently (and maybe better) than what is restrictively ‘evidenced-based’?5 Survey questionnaires and Delphi consensus are often better suited for well-identified group-based approaches and generic answers to be given, where highly individual and multifactorial approaches6 are more difficult to be registered and reported. In fact, in real practice, people use multiple types of exercises and use variations in terms of volume and intensity; they adapt their programming as a function of player needs, profile, context, game schedule, acute loading, availability of tools on site (e.g., away game, camps), beliefs, experience and many other considerations. Some players have their own external-to-the-club physios and fitness coaches, who obviously don’t complete the questionnaires. Clubs encouraging these individual-player practices end up being classified as “non-compliant”1 to evidenced-based programs, but does this mean that what those supporting staff do has no value? What about “best practice”? In fact, the understanding of the field context is often overlooked by research recommendations, and when it comes to train and work with elite athletes, the science doesn’t always apply.5 It is however worth mentioning that elite practitioners’ attitude toward innovation may be a double-edged sword; new practices (not researched yet) may also sometimes, in retrospect, turn out not to be that efficient. Finally, since randomized controlled trials are impossible to implement in an elite population, the ‘evidence’ is often based on interventions conducted in sub-elite/amateur populations. In fact, the response of both muscle strength and architecture to training is likely training-status dependent; therefore, extrapolating the research findings obtained in sub-elites to what could be expected in highly-trained players remains hazardous. This in fine questions the relevance of a lot of research findings, and in turn, limits their adoption by top athletes.
  2. Have injuries really increased over the past 13 years? The 2-4% increase in injury rate2 reported between the years 2000 and 2013 was established while reporting injury occurrence as a function of both training attendance and game participation, as measured by minutes/hours of training and play. First, as discussed recently,7 the fact that team doctors may tend to adopt now a more conservative approach to withdraw players from training when early muscle warnings are apparent (but before an injury is actually registered) may artificially increase training injury rate.7 Second, when the slightly increased match injury occurrence2 is reported as a function of the corresponding high-intensity running demands over the same periods (which have moderately-to-largely increased8) – and not simply relative to overall playing time-2 it appears that match injury incidence has in fact slightly decreased (̴ 20%) over time (Table 1)! In fact, this small but substantial decrease in injury rate over the past years lends support to the individual prevention programs and load management strategies implemented in clubs, that may turn out to be more efficient than previously thought. In other words, the individual, multifactorial, context-driven approaches implemented in those ‘evidenced-based non-compliant’ clubs may in fine work at decreasing injuries during matches. Using some specific running demands rather than playing time to examine injury rate (Table 1) makes actually a lot of sense given the strong association between high-speed running and injuries,3 and should probably be expanded further to the majority of epidemiological investigations in team sports.

To conclude, those two examples suggest that injuries may in fact be better prevented and managed in clubs than it may appear from some of the research papers. Since elite environments are more complex than meets the eye, before making any recommendations, we, both as researchers and practitioners, should never oversee the importance of context. Pragmatism, use of common sense and the consideration of best practices4 are often to be prioritized over oversimplified research findings.

Table 1


  1. Bahr R, Thorborg K, Ekstrand J. Evidence-based hamstring injury prevention is not adopted by the majority of Champions League or Norwegian Premier League football teams: the Nordic Hamstring survey. Br J Sports Med 2015;49(22):1466-71. doi: 10.1136/bjsports-2015-094826 [published Online First: 2015/05/23]
  2. Ekstrand J, Walden M, Hagglund M. Hamstring injuries have increased by 4% annually in men’s professional football, since 2001: a 13-year longitudinal analysis of the UEFA Elite Club injury study. Br J Sports Med 2016;50(12):731-7. doi: 10.1136/bjsports-2015-095359 [published Online First: 2016/01/10]
  3. Gabbett TJ. The training-injury prevention paradox: should athletes be training smarter and harder? Br J Sports Med 2016;50(5):273-80. doi: 10.1136/bjsports-2015-095788 [published Online First: 2016/01/14]
  4. Buchheit M. Outside the Box. Int J Sports Physiol Perform 2017;12(8):1001-02. doi: 10.1123/ijspp.2017-0667 [published Online First: 2017/11/02]
  5. Buchheit M. Houston, We Still Have a Problem. Int J Sports Physiol Perform 2017;12(8):1111-14. doi: 10.1123/ijspp.2017-0422 [published Online First: 2017/07/18]
  6. Mendiguchia J, Martinez-Ruiz E, Edouard P, et al. A Multifactorial, Criteria-based Progressive Algorithm for Hamstring Injury Treatment. Med Sci Sports Exerc 2017;49(7):1482-92. doi: 10.1249/mss.0000000000001241 [published Online First: 2017/03/10]
  7. Eirale C. Hamstring injuries are increasing in men’s professional football: every cloud has a silver lining? Br J Sports Med 2018 doi: 10.1136/bjsports-2017-098778 [published Online First: 2018/01/25]
  8. Barnes C, Archer DT, Hogg B, et al. The evolution of physical and technical performance parameters in the English Premier League. Int J Sports Med 2014;35(13):1095-100. doi: 10.1055/s-0034-1375695 [published Online First: 2014/07/11]

Monitoring locomotor load in soccer: is metabolic power, powerful?

Buchheit M, Manouvrier C, Cassirame J and Morin JB. Monitoring locomotor load in soccer: is metabolic power, powerful? Int J Sport Med, In press, 2015.

 Full text here 

MetabonotpowerulFigure 1. Oxygen uptake (VO2), speed and metabolic power estimated from locomotor demands (PGPS) during the warm-up and the 3 exercise bouts in a representative player. VO2max: maximal oxygen uptake reached during an incremental test to exhaustion.

Interview – discussion podcast on the paper here 



The aim of the present study was to examine the validity and reliability of metabolic power (P) estimated from locomotor demands during soccer-specific drills. Fourteen highly-trained young soccer players (15.4±1.6 yr) performed a soccer-specific circuit with the ball (3 x 1-min bouts, interspersed with 30-s passive recovery) on two different occasions. Locomotor activity was monitored with 4-Hz GPS units, while oxygen update (VO2) was collected with a portable gas analyzer. P was calculated using either net VO2 responses and traditional calorimetry principles (PVO2, or locomotor demands (PGPS, Distance covered into different speed, acceleration and P zones was recorded. Players covered 30 times more distance >20 W/kg (PGPS) than >14.4 km.h-1. While PGPS was 29 ± 10 % lower than PVO2 (Cohen’s d<-3) during the exercise bouts, it was 85 ± 7 % lower (d<-8) during recovery phases. The typical error of the estimate between PGPS vs PVO2 was moderate: 19.8%, 90% confidence limits: (18.4;21.6). The correlation between both estimates of P was small: 0.24 (0.14;0.33). Very large day-to-day variations were observed for acceleration, deceleration and >20 distances (all CVs >50%), while total distance, average PVO2 and PGPS showed CVs <10%. ICC ranged from very low- (acceleration and >20 distances) to-very high (PVO2). To conclude, PGPS largely underestimates the energy demands of soccer-specific drills, especially during the recovery phases. Together with its moderate agreement with calorimetry-related P estimations, the poor reliability of PGPS >20 questions its value for monitoring purposes in soccer.

Key words: soccer, acceleration, deceleration, energy demands, soccer-specific, training load.

Peak match speed and maximal sprinting speed in young soccer players: effect of age and playing position

Hani Al Haddad, Ben M. Simpson, Martin Buchheit, Valter Di Salvo and Alberto Mendez-Villanueva. Peak match speed and maximal sprinting speed in young soccer players: effect of age and playing position. IJSPP, 2015, In press.

Figure 1Figure 1. Data are presented as mean and 90% confidence interval for maximal sprinting speed (MSS, white circles), peak match speed (PMSAbs, gray circles) and PMSAbs as percentage of MSS (PMSRel, black circles).


In this study we assessed the relationship between peak match speed (PMS) and maximal sprinting speed in regard to age and playing positions. Maximal sprinting speed and absolute PMS (PMSAbs) were collected from 180 male youth soccer players (U13 to U17, 15.0 ± 1.2 yrs, 161.5 ± 9.2 cm and 48.3 ± 8.7 kg). The fastest 10-m split over a 40-m sprint was used to determine maximal sprinting speed. PMSAbs was recorded using a global positioning system and was also expressed as a percentage of maximal sprinting speed (PMSRel). Sprint data were compared between age groups and between playing positions. Results showed that regardless of age and playing positions, faster players were likely to reach higher PMSAbs and possibly lower PMSRel. Despite a lower PMSAbs compared with older groups (e.g., 23.4 ± 1.8 vs. 26.8 ± 1.9 km/h for U13 and U17, respectively, ES= 1.9 90% confidence limits (1.6;2.1)), younger players reached a greater PMSRel (92.0±6.3% vs. 87.2±5.7% for U13 and U17, respectively, ES= -0.8 90% CL (-1.0; -0.5)). Playing position also affected PMSAbs and PMSRel, as strikers were likely to reach higher PMSAbs (e.g., 27.0 ± 2.7 vs. 23.6 ± 2.2 km/h for strikers and central midfielder, respectively, ES= 2.0 (1.7;2.2)) and PMSRel (e.g., 93.6 ± 5.2% vs. 85.3 ± 6.5% for striker and central midfielder, respectively, ES= 1.0 (0.7;1.3)) compared with all other positions. Present findings confirm that age and playing positions affect the absolute and relative intensity of speed-related actions during matches.

Key words: youth players, soccer, sprinting speed, playing position

@HaniAlHaddad2 @benMsimpson

Relative match intensities at high altitude in highly-trained young soccer players (isa3600)

qantas-joeys-held-to-scoreless-draw-in-bolivia_00048620-leadimageMartin Buchheit, Kristal Hammond, Pitre C. Bourdon, Ben M. Simpson, Laura A. Garvican-Lewis, Walter F. Schmidt, Christopher J. Gore and Robert J. Aughey. Relative match intensities at high altitude in highly-trained young soccer players (isa3600). Journal of Sports Science and Medicine, In press.

Figure 1Full text here


To compare relative match intensities of sea-level versus high-altitude native soccer players during a 2-week camp at 3600 m, data from 7 sea-level (Australian U17 National team, AUS) and 6 high-altitude (a Bolivian U18 team, BOL) native soccer players were analysed. Two matches were played at sea-level and three at 3600 m on Days 1, 6 and 13. The Yo-Yo Intermittent recovery test (vYo-YoIR1) was performed at sea-level, and on Days 3 and 10. Match activity profiles were measured via 10-Hz GPS. Distance covered >14.4 km.h-1 (D>14.4 km.h-1) and >80% of vYo-YoIR1 (D>80%vYo-YoIR1) were examined.

Upon arrival at altitude, there was a greater decrement in vYo-YoIR1 (Cohen’s d +1.0, 90%CL ± 0.8) and D>14.4 km.h-1 (+0.5 ± 0.8) in AUS. D>14.4 km.h-1 was similarly reduced relative to vYo-YoIR1 in both groups, so that D>80%vYo-YoIR1 remained similarly unchanged (-0.1 ± 0.8). Throughout the altitude sojourn, vYo-YoIR1 and D>14.4 km.h-1 increased in parallel in AUS, so that D>80%vYo-YoIR1 remained stable in AUS (+6.0%/match, 90%CL ± 6.7); conversely D>80%vYo-YoIR1 decreased largely in BOL (-12.2%/match ± 6.2).

In sea-level natives competing at high-altitude, changes in match running performance likely follow those in high-intensity running performance. Bolivian data confirm that increases in ‘fitness’ do not necessarily translate into greater match running performance, but rather in reduced relative exercise intensity.

Key words: association football; hypoxia; match running performance

Effect of birth date on playing time during international handball competitions with respect to playing positions

Karcher, C, Ahmaidi S and Buchheit M. Effect of birth date on playing time during international handball competitions with respect to playing positions. Kinesiology 46(2014) 1:23-32. Full text here / Journal original website

Abstract: While a relative age effect (RAE) has been reported in handball, such analyses do not consider actual playing time during competitions, which may actually have more impact on performance in matches. The objective of the present study was to examine the RAE on playing time during international competitions with respect to playing positions. Team compositions (477 players) of the quarter finalists of the 2012 Olympic Games, 2013 World Championships, and 2014 European Championships were analyzed. Month and year of birth where collected in the starting list of each team for center, left and right backs, left and right wings, goalkeepers and pivots. Players were categorized into birth quartile (Q1 Jan–Mar; Q2 Apr–Jun; Q3 Jul– Sep; and Q4 Oct–Dec) and as odd/even year. Playing times were retrieved from official statistics. Data were analyzed for practical significance using magnitude-based inferences. We observed a strong selection bias towards players born earlier within a two-year selection period for all playing positions (Chi-square, p<.001). There was, however, an inconsistent effect of age (i.e. expected, reversed or a lack of it) on actual playing time during competitions. In conclusion, the present study showed for the first time that, despite its large effect on players’ selection, players’ relative age had a limited and position-dependent effect on their actual playing time during top-level competitions. Present findings suggest that the reasons supporting the relative age effect with respect to team selection are at odds with the current utilization of players by coaches in the field.

Key words: relative age effect, team selection, main competitions


Integrating different tracking systems in football

khalifa international stadium 2-2 Buchheit, M., Poon, T.K., Allen A., Modonutti, M.,  Gregson, W., and Di Salvo V. Integrating different tracking systems in football: multiple camera semi-automatic system, local position measurement and GPS technologies. J Sports Sci, 2014, In press. For 50 free reprints try here

Pages from Tracking system comparison Report 08.05.2013 - CopyAbstract
During the past decade substantial development of computer-aided tracking technology
has occurred. Therefore, we aimed to provide calibration equations to allow the
interchangeability of different tracking technologies used in soccer. Eighty-two highly-trained soccer players (U14-U17) were monitored during training and one game. Player
activity was collected simultaneously with a semi-automatic multiple-camera (Prozone),
local position measurement (LPM) technology (Inmotio) and two global positioning
systems (GPSports and VX). Data were analyzed with respect to three different field
dimensions (small, <30m2 to full-pitch, match). Variables provided by the systems were
compared, and calibration equations (linear regression models) between each system
were calculated for each field dimension. Most metrics differed between the four
systems with the magnitude of the differences dependant on both pitch size and the
variable of interest. Trivial-to-small between-system differences in total distance were
noted. However, high-intensity running distance (>14.4km/h) was slightly-to-moderately
greater when tracked with Prozone, and accelerations, small-to-very largely
greater with LPM. For most of the equations, the typical error of the estimate was of a
moderate magnitude. Interchangeability of the different tracking systems is possible
with the provided equations, but care is required given their moderate typical error of
the estimate.

Key Words: soccer; tracking system; match analysis; training load; agreement;
calibration equations.

Pages from Tracking system comparison Report 08.05.2013

Effects of age, maturity and body dimensions on match running performance in highly-trained under 15 soccer players

More vs less mature

Buchheit & Mendez-Villanueva. Effects of age, maturity and body dimensions on match running performance in highly-trained under 15 soccer players. Journal of Sports Science, In press

For a discussion about the stats used in this study see the comments here: don’t trust % differences

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 (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 team-mates. These age-, maturation- and body size-related differences were of larger magnitude for field test measures vs. 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.

Post-match Recovery in Youth Soccer player

J Sports Sci. 2011 Mar;29(6):591-8. doi: 10.1080/02640414.2010.546424.

Effects of age and spa treatment on match running performance over two consecutive games in highly trained young soccer players.


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


The aim of this study was to examine the effect of age and spa treatment (i.e. combined sauna, cold water immersion, and jacuzzi) on match running performance over two consecutive matches in highly trained young soccer players. Fifteen pre- (age 12.8 ± 0.6 years) and 13 post- (15.9 ± 1 y) peak height velocity (PHV) players played two matches (Matches 1 and 2) within 48 h against the same opposition, with no specific between-match recovery intervention (control). Five post-PHV players also completed another set of two consecutive matches, with spa treatment implemented after the first match. Match running performance was assessed using a global positioning system with very-high-intensity running (> 16.1-19.0 km · h(-1)), sprinting distance (>19 km · h(-1)), and peak match speed determined. Match 2 very-high-intensity running was “possibly” impaired in post-PHV players (-9 ± 33%; ± 90% confidence limits), whereas it was “very likely” improved for the pre-PHV players (+27 ± 22%). The spa treatment had a beneficial impact on Match 2 running performance, with a “likely” rating for sprinting distance (+30 ± 67%) and “almost certain” for peak match speed (+6.4 ± 3%). The results suggest that spa treatment is an effective recovery intervention for post-PHV players, while its value in pre-PHV players is questionable.

Repeated high-intensity activities during youth soccer games in relation to changes in maximal sprinting and aerobic speed

 Buchheit -  Changes in Fitness and game RSA (Small)

pdf: Buchheit – Changes in Fitness and game RSA

Int J Sports Med. 2013 Jan;34(1):40-8. doi: 10.1055/s-0032-1316363. Epub 2012 Aug 15.

Repeated high-speed activities during youth soccer games in relation to changes in maximal sprinting and aerobic speeds.


ASPIRE, Academy for Sports Excellence, Sport Science, Doha, Qatar.


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 V(Vam-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 V(Vam-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.