Scheduling of Eccentric Lower-limb Injury Prevention Exercises during the Soccer micro-cycle: Which day of the week?

Lovell R, Whalan M, Marshall P, Sampson JA, Siegler JC and Buchheit M. Scheduling of Eccentric Lower-limb Injury Prevention Exercises during the Soccer micro-cycle: Which day of the week? Scand J Med Sci Sports. In Press.

Full text here

CK lovell

Abstract

Scheduling eccentric-based injury prevention programs (IPP) during the common 6-
day micro-cycle in Soccer is challenged by recovery and tapering phases. This study
profiled muscle damage, neuromuscular performance, and perceptual responses to a
lower-limb eccentric-based IPP administered 1 (MD+1) versus 3 days (MD+3) postmatch.
18 semi-professional players were monitored daily during 3 in-season 6-day
micro-cycles, including weekly competitive fixtures. Capillary creatine kinase
concentration (CK), posterior lower limb isometric peak force (PF), countermovement
jump (CMJ) performance, and muscle soreness were assessed 24 h prior
to match-day (baseline), and every 24 h up to 120 h post-match. The IPP consisted
of lunges, single stiff leg dead-lifts, single leg-squats and Nordic hamstring
exercises. Performing the IPP on MD+1 attenuated the decline in CK normally
observed following match-play (CON: 142%; MD+3: 166%; small
differences). When IPP was delivered on MD+3, CK was higher versus CON and
MD+1 trials on both MD+4 (MD+3: 260%; CON: 146%; MD+1: 151%; moderate
differences) and MD+5 (MD+3: 209%; CON: 125%; MD+1: 127%; small
differences). Soreness ratings were not exacerbated when the IPP was delivered on
MD+1, but when prescribed on MD+3, hamstring soreness ratings remained higher
on MD+4 and MD+5 (small differences). No between trial differences were observed
for PF and CMJ. Administering the IPP in the middle of the micro-cycle (MD+3)
increased measures of muscle damage and soreness, which remained elevated on
the day prior to the next match (MD+5). Accordingly, IPP should be scheduled early
in the micro-cycle, to avoid compromising preparation for the following match.

Keywords: injury prevention, scheduling, muscle, soccer

 

Advertisements

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.

 

logic

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

References

  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 of post-match fatigue in professional soccer: welcome to the real-world

Carling C., Lacome M., McCall A., Dupont G.,  F.Le Gall, Simpson B.M. and Buchheit M. Monitoring of post-match fatigue in professional soccer: welcome to the real-world. Sports Med, In press.

Full text here

Abstract

Participation in soccer match-play leads to acute and transient subjective, biochemical, metabolic and physical disturbances in players over subsequent hours and days. Inadequate time for rest and regeneration between matches can expose players to the risk of training and competing whilst not entirely recovered. In professional soccer, contemporary competitive schedules can require teams to compete in-excess of 60 matches over the course of the season while periods of fixture congestion occur prompting much attention from researchers and practitioners to the monitoring of fatigue and readiness to play. A comprehensive body of research has investigated post-match acute and residual fatigue responses. Yet the relevance of the research for professional soccer contexts is debatable notably in relation to the study populations and designs employed. Monitoring can indeed be invasive, expensive, time-inefficient and difficult to perform routinely and simultaneously in a large squad of regularly competing players. Uncertainty also exists regarding the meaningfulness and interpretation of changes in fatigue response values and their functional relevance, and practical applicability in the field. The real-world need and cost-benefit of monitoring must be carefully weighed up. In relation to professional soccer contexts, this opinion paper intends to: 1) debate the need for PMF monitoring, 2) critique the real-world relevance of the current research literature, 3) discuss the practical burden relating to measurement tools and protocols and the collection, interpretation and application of data in the field, and, 4) propose future research perspectives.

 

Key points

Uncertainty exists around the real-world impact of research regarding post-match fatigue monitoring and its usefulness in informing readiness to play in professional soccer players.

Practitioners must carefully weigh up the need and cost-benefit for monitoring post-match fatigue and requirements should be determined on a case-by-case basis.

Fatigue monitoring requires a more practical approach using data derived in training sessions and the development of tools to enable the simultaneous, instantaneous and non-invasive capture of multiple sources of information during and following play.

Monitoring players’ readiness using predicted heart rate responses to football drills – legacy of Nick Broad

Nick Broad

Nick Broad was an exceptional man who inspired a whole generation of sports scientists and nutritionists the world over. Four years after his loss, Nick is still with us in the office. Our daily work at the club wouldn’t be the same without his legacy. As some of you may have noticed, Nick is also listed as one of the authors of the paper presented below, accepted this morning in IJSPP.

Tweet Unai

As I already wrote elsewhere, I had the chance to work with Nick on various occasions. Our discussions fostered many ideas and shaped the way I think today. “Statistics are our weapons” is probably one of the things he said that really hit home and motivated my years of research and practice. One of the top projects that Nick shared with me the last time I visited him in Paris (while I was still working in Qatar), was about the development of a player monitoring system that would not require formal testing. The brilliant idea was to use players’ HR responses to some football dills, and to compare them to what would be expected from historical data (of the same drills). More precisely, we chatted about the best ways to predict those HR responses from GPS outputs using (individual) multiple regressions for example. The difference between measured and predicted HRs would be a simple but relevant index of fitness (with when a measured HR is lower than that predicted = fitter player). If Sport Performance & Science Reports had existed earlier, I am sure that I would have managed to convince Nick to write a short report on that. But given the context, tragically, Nick (and Jack Nayler at that time) didn’t have the time to pursue the project.

When I joined the club in July 2014, I decided to bring back this exciting project on the table, and made it one of our priorities. Both because I still believed that the idea was brilliant, but also as way to make sure we would be prolonging Nick’s ideas and work. With Yannick Cholley and Ben Simpson, we then started to add new drill datasets to the databases, and after several years of individual players data, we left the analysis to Mathieu Lacome who efficiently cracked the numbers and the individual equations. It then, as always, took (too much) time to get the manuscript written, submitted and finally accepted.

Sorry, Nick, we are a bit late, but this one is definitely for you mate. Thank you so much.

nick 2

Lacome M., Simpson B.M., Broad N. and Buchheit M. Monitoring players’ readiness using predicted heart rate responses to football drills. IJSPP, In press

Full text here

Fig HRpred

Figure: Between-month changes in the differences between actual and predicted heart-rate.

Purpose: To examine the ability of multivariate models to predict the HR responses to some specific training drills from various GPS variables and to examine the usefulness of the difference in predicted vs actual HR responses as an index of fitness or readiness to perform.

Method: All data were collected during one season (2016-2017) with players’ soccer activity recorded using 5-Hz GPS and internal load monitored using heart rate (HR). GPS and HR data were analysed during typical small-sided games and a 4-min standardized submaximal run (12 km/h). A multiple stepwise regression analysis was carried out to identify which combinations of GPS variables showed the largest correlations with HR responses at the individual level (HRACT, 149±46 GPS/HR pairs per player) and was further used to predict HR during individual drills (HRPRED). HR predicted was then compared with actual HR to compute an index of fitness or readiness to perform (HRΔ,%). The validity of HRΔ was examined while comparing changes in HRΔ with the changes in HR responses to a submaximal run (, fitness criterion) and as a function of the different phases of the season (with fitness being expected to increase after the pre-season).

Results: HRPRED was very largely correlated with HRACT (r=0.78±0.04). Δ HRΔ very likely decreased from July to August (3.1±2.0 vs 0.8±2.2%) and most likely decreased further in September (-1.5±2.1%).

Conclusion: HRΔ is a valid variable to monitor elite soccer players’ fitness and allows fitness monitoring on a daily basis during normal practice, decreasing the need for formal testing.

Key words: Small-sided games, soccer, fitness monitoring, GPS

 

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 🙂

Locomotor and heart rate responses of floaters during small-sided games in elite soccer players: effect of pitch size and inclusion of goal keepers

Lacome M., Simpson B.M, Cholley Y., Buchheit M. Locomotor and heart rate responses of floaters during small-sided games in elite soccer players: effect of pitch size and inclusion of goal keepers. IJSPP, In press

Full text here

Figure 1_All stats_Joker

Figure 1: Standardised differences between floaters and regular players SWC: smallest worthwhile change; *: possibly; **: likely; ***: most likely; ****: almost certainly difference.

Abstract

Purpose: To (1) compare the locomotor and heart rate responses between floaters and regular players during both small and large small sided games (SSGs) and (2) examine whether the type of game (i.e., game simulation vs possession game) affects the magnitude of the difference between floaters and regular players.

Methods: Data were collected in 41 players belonging to an elite French football team during three consecutive seasons (2014-2017). 5-Hz GPS were used to collect all training data, with the Athletic Data Innovation analyser (v5.4.1.514, Sydney, Australia) used to derive total distance (m), high-speed distance (> 14.4 km.h-1, m) and external mechanical load (MechL, a.u). All SSGs included exclusively one floater, and were divided into two main categories, according to the participation of goal-keepers (GK) (game simulation, GS) or not (possession games, PO) and then further divided into small and large (>100 m2/player) SSGs based on the area per player ratio.

Results: Locomotor activity and mechanical load performed were likely-to-most likely lower (moderate to large magnitude) in floaters compared with regular players, while differences in HR responses were unclear to possibly higher (small) in floaters. The magnitude of the difference in locomotor activity and MechL between floaters and regular players was substantially greater during GS compared with PO.

Conclusions: Compared with regular players, floaters present decreased external load (both locomotor and MechL) despite unclear to possibly slightly higher HR responses during SSGs. Moreover, the responses of floaters compared with regular players are not consistent across different sizes of SSGs, with greater differences during GS than PO.

Keywords: Small-sided games, soccer, floaters, locomotor activity, mechanical load.

Neuromuscular responses to conditioned soccer sessions assessed via GPS-embedded accelerometers: insights into tactical periodization

Buchheit M, Lacome M, Cholley Y & Simpson B.M. Neuromuscular responses to conditioned soccer sessions assessed via GPS-embedded accelerometers: insights into tactical periodization. IJSPP, In press.

Full text here

Abstract

Purpose. To 1) examine the reliability of field-based running-specific measures of neuromuscular function assessed via GPS-embedded accelerometers and 2) examine their responses to three typical conditioned sessions (i.e., Strength, Endurance and Speed) in elite soccer players.

 Methods. Before and immediately after each session, vertical jump (CMJ) and adductors squeeze strength (Groin) performances were recorded. Players also performed a 4-min run at 12 km/h followed by 4 ~60-m runs (run =12 s, r =33 s). GPS (15-Hz) and accelerometer (100 Hz) data collected during the four runs + the recovery periods excluding the last recovery period were used to derive vertical stiffness (K), peak loading force (peak force over all the foot-strikes, Fpeak) and propulsion efficiency (i.e., ratio between velocity and force loads, Vl/Fl).

Results. Typical errors were small (CMJ, Groin, K and Vl/Fl) and moderate (Fpeak), with moderate (Fpeak), high (K and Vl/Fl) and very high ICC (CMJ and Groin). After all sessions, there were small decreases in Groin and increases in K, while changes in F were all unclear. In contrast, the CMJ and Vl/Fl ratio responses were session-dependent: small increase in CMJ after Speed and Endurance, but unclear changes after Strength; the Vl/Fl ratio increased largely after Strength, while there was a small and a moderate decrease after the Endurance and Speed, respectively.

 Conclusions. Running-specific measures of neuromuscular function assessed in the field via GPS-embedded accelerometers show acceptable levels of reliability. While the three sessions examined may be associated with limited neuromuscular fatigue, changes in neuromuscular performance and propulsion-efficiency are likely session objective-dependent.

Keywords: specificity; running mechanisms; fatigue; horizontal force application; association football.

Figure 1Figure 1. Changes in counter movement jump (CMJ) and groin squeeze (Groin) performance, vertical stiffness (K), peak loading force (Fpeak) and velocity load/force load ratio (Vl/Fl) following the three conditioned sessions. *: possible, **: likely, ***: very likely and ****: almost certain change/difference in the change.

Small-Sided Games in elite soccer: Does one size fits all?

Lacome M., B.M. Simpson, Y. Cholley, P. Lambert, and M Buchheit. Small-Sided Games in elite soccer: Does one size fits all? IJSPP, In press 2017.

Full Text here

Abstract

Purpose: To compare the peak intensity of typical Small Sided Games (SSGs) with those of official matches in terms of running demands and mechanical work over different rolling average durations and playing positions.

Method: Data were collected in 21 players (25±5 y, 181±7 cm, 77±7 kg) belonging to an elite French football team. SSG data were collected over two seasons during typical training sessions (249 files, 12±4 per player) and official matches (n=12). Players’ locomotor activity was recorded using 15-Hz GPS. Total distance (TD, m), high-speed distance (HS, distance above 14.4 km.h-1, m) and mechanical work (MechW, a.u) were analysed during different rolling average periods (1 to 15 min). The SSGs examined were 4v4+Goal Keepers (GKs), 6v6+GKs, 8v8+GKs and 10v10+GKs.

Results: Peak TD and HS during 4v4, 6v6 and 8v8 were likely-to-most likely largely lower than during matches (ES: -0.59,±0.38 to -7.36,±1.20). MechW during 4v4 was likely-to-most likely higher than during matches (1-4-min; 0.61±,0.77 to 2.30±,0.64). Relative to their match demands, central defenders (CD) performed more HS than other positions (0.63±,0.81 to 1.61±,0.52) during 6v6. Similarly, central midfielders (CM) performed less MechW than the other positions during 6v6 (0.68,±0.72 to 1.34,±0.99) and 8v8 (0.73,±0.50 to 1.39,±0.32).

Conclusion: Peak locomotor intensity can be modulated during SSGs of various formats and durations to either over- or underload match demands, with 4v4 placing the greatest and the least emphasis on MechW and HS, respectively. Additionally, CD and CM tend to be the most and least overloaded during SSGs, respectively.

Key words: Small sided games, soccer, peak intensity, match demands, periodisation,

 

SSG_Figure2 (600)2

Peak locomotor intensity during the different small-sided games compared with match demands as a function of each rolling average period for all players pooled together (grey zones stand for match average ± standard deviations). Confidence intervals for mean values are not provided for clarity.

@mathlacome

Want to see my report, coach?

In this new paper I merged and developed a bit further the 2 IJSPP papers on 1) the stats that changed my life and 2) some personal thoughts on chasing the 0.2 (i., making an impact) in an elite setting.

aspetar-201702

The value and importance of sport science varies greatly between elite clubs and federations. Among the different components of effective sport science support, the three most important elements are likely the following:

  1. Appropriate understanding and analysis of the data; i.e. using the most important and useful metrics only and using magnitude-based inferences as statistics. In fact, traditional null hypothesis significance testing (P values) is neither appropriate to answer the types of questions that arise from the field (i.e. assess magnitude of effects and examine small sample sizes) nor to assess changes in individual performances.
  2. Attractive and informative reports via improved data presentation/ visualisation (‘simple but powerful’).
  3. Appropriate communication skills and personality traits that help to deliver data and reports to coaches and athletes. Developing such an individual profile requires time, effort and most importantly, humility

Does beetroot juice really improve sprint and high-intensity running performance? – probably not as much as it seems: how (poor) stats can help to tell a nice story

beetrootfoot

 A few tweets, re-tweets and emails from colleagues have caught my attention within the last 24 hrs, all pointing toward a new study showing improvements in sprinting and high-intensity intermittent running performance after dietary nitrate supplementation (beetroot shots) (1). In the 36 team-sports players (training 5-10h a week) who volunteered for the study, significant “improvements” in 5- (2.3%), 10- (1.6%) and 20-m (1.2%) sprint times and a 3.9% “increase” in high-intensity intermittent performance were reported, after no longer than 5 days of supplementation! (1)

nosprint

To all practitioners who may read both the article (1) and the present blog post, the topic is obviously highly relevant; we are all looking for various ways to improve our players’ running performance – even better if these improvements can be gained legally (no doping) and without (physical) efforts. If you can convince yourself to commit to drink daily an awful 70-ml beetroot shot for 5 days before an important competition, then you may have found a really cool and lazy way to get faster and fitter!!

However, before I began to tell (again) every player at the club (who would systematically pass on beetroot because of its taste) to finally commit themselves to drink this stuff, because it really works, I wished to make sure it would be worth the effort, both for them and me. After a deeper read of the paper, a closer look at the study design, the data analysis and the stat approach, I realized that in fact, beetroot supplementation, within the context of the present study, may not be as promising as it could be understood while only reading the title of the paper. This for at least two important reasons: 1) the somewhat limited magnitude of the “changes”, although significant and 2) the questionable study design/data analysis that doesn’t allow individual responses to be clearly accounted for and analyzed.

  1. The magnitude of the “improvement” may not be large enough to be meaningful. When considering the magnitude of the smallest worthwhile changes for different sprint distances (SWC, i.e., the minimum improvement likely to have an impact on the field, such as that required to be 20 cm ahead of an opponent to win a ball) (2), the changes reported in the present study are in fact either smaller (5 m: study 2.3% vs SWC ̴ 4%, 10 m: study 1.6% vs SWC ̴2%) or just similar to (20 m: study 1.2% vs SWC ̴1%) (2). Even for 20-m time, which magnitudes equals the SWC, chances for the “improvement” to be substantial may be no more than 50% at the individual level (when considering a typical error of the measurement (TE) of the same magnitude than the SWC – while in fact the TE may actually be twice as large as the SWC for such a distance (2), decreasing further the likelihood of a substantial change) (2). The same reasoning applies to the “increase” in Yo-YoIR1 performance (+3.9%), which SWC is generally twice larger (̴ +8% (3), +7% as 0.2xSD in the present study). In conclusion, the comparison of the reported changes, although significant, to their specific SWC directly questions the practical impact and in turn, the usefullness of beetroot supplementation in the context of the present study. These data illustrate once again that the use of null hypothesis significance testing (NHST) is clearly limited to assess the actual performance benefit of a supplement or an intervention (4, see the blog on the topic) – in the present case the significant P value likely results from the large sample size (n=36) – different conclusions (and probably less misleading in the present case) would be drawn with lower samples (i.e., n<15).
  1. The data analysis doesn’t allow individual responses to be clearly accounted for/analyzed. In fact, the authors simply chose to compare the sprints/YoYoIR1 performances following beetroot supplementation to these following the placebo drink (Post beetroot – Post placebo, via paired-samples t-tests)!? While it is not clear why such a limited approach was chosen, the proper way to analyze these data would be to look first at within-group changes, and more importantly, to compare these within-group changes (i.e., between-group differences in the changes – typical crossover design, as ‘post beetroot – pre beetroot’ compared with ‘post placebo – pre placebo’). This latter approach is way more powerful and allows the understanding of i) the effect of each treatment per se (within-group effect, in relation to the SWC), ii) the variability of the response within each treatment (SD of the change, which has important implications when using supplementation with athletes – some will respond, some not !! – and how many and by which magnitude?), iii) compare the efficacy of the treatments (differences in the magnitude of the changes) and even more importantly, iiii) compare the magnitude of the individual responses between each treatment (i.e., which treatment shows the greater variability in response). Unfortunately, all these relevant information for practitioners are missing in the manuscript.

That being said, I am happy to keep beetroot shots on the supplement table for the moment (for players that can cope with the taste… at least it hasn’t been shown to be detrimental). I may, however, not use the present study to advertise the benefit of beetroot to the players – if we want to keep our legitimacy and maintain the trust that the players put on us, I believe it is important to come to them with the right message – and in that case, applying some appropriate stats surely helps!

References

  1. Thompson C, Vanhatalo A, Jell H, Fulford J, Carter c, Nyman L, Bailey SJ and Jones AM. Dietary nitrate supplementation improves sprint and high-intensity intermittent running performance. Nitric Oxide 61 (2016) 55-61.
  2. Haugen T, Buchheit M. Sprint running performance monitoring: methodological and practical considerations. Sports Med. 2016;46(5):641.
  3. Bangsbo J, Iaia FM, Krustrup P. The Yo-Yo Intermittent Recovery Test: a useful tool for evaluation of physical performance in intermittent sports. Sports Med. 2008;38:37–51.
  4. Buchheit M. The Numbers Will Love You Back in Return—I Promise. Int J Sports Physiol & Perf, 2016, 11, 551 -554.