Monitoring training Status with Player-tracking Technology – Still on the road to Rome

M. Lacome, B.M. Simpson and M. Buchheit. Monitoring training Status with Player-tracking Technology – Still on the road to Rome. Aspetar Journal, 7, 2018

Full paper

Road to Rome

dataviz

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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

 

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 🙂

Outside the Box

M. Buchheit. Outside the Box. IJSPP 2017, 12, 1001 -1002.

sortir-du-lot

When I submitted my first paper in the early 2000’s, web-based editorial manager systems were in their infancy. I posted via regular mail three hard copies of my manuscript -with a neatly hand-written cover letter- to the editor in chief of the American Journal of Physiology, who sent copies to two reviewers (contacted by email, but also often by phone or mail!). I then had to wait for a couple of months for those annotated copies to be returned… with the final decision being…’rejected’. At this time, irrespective of the outcome, submitting and getting a paper reviewed was already an achievement. The procedure in itself was a lesson of patience and humility, which likely made academics think twice before starting the overall process. Today with electronic platforms, submissions can be completed in 15 min and reviewers, secured within a few clicks. Considering the ongoing development of new technologies that facilitate data collection, and more importantly the increased need for achieving greater academic levels and the associated ‘necessity’ to publish, the number of research paper submissions has never been so high. The acceptance rate in well-ranked journals ranges from <10% (e.g., Nature) to 20-30%. For IJSPP, on the 795 papers submitted in 2016, only 214 made it in print. In overall, publishing papers has never been so competitive.

An even greater level of competitiveness can be seen when it comes to work as a practitioner in high-profile institutions and clubs. Back in the days, these positions were mainly accessible for former top athletes, who would drag with them the practitioners that worked with them during their career. With the expansion of individual athlete care in elite structures and the development of sport analytics as a whole, some of these jobs are now also accessible to people from outside the sport itself; further increasing the competitiveness of those positions. Every year, >1000-1500 Sport Sciences and/or Strength & Conditioning master students graduate in each European country;1 the number of available positions, in contrast, likely stagnates or may only grow at a very slow rate.

So, how do researchers get their papers within the 10-25%? How do aspiring coaches/sport scientists get the job everyone dreams of? The answer is simple: they break from the pack, make the choice to become a “linchpin”,2 surpass their peers while doing differently and better. They do what the others are not prepared to do. In addition to the necessary levels of knowledge, skills and experience that make great researchers and practitioners, some specific character traits are required to make an impact.3-5 Here, I wish to discuss further this aspect, using the example of 3 personality archetypes in relation to people’s ability and willingness to grow, share knowledge, collaborate and adopt an open-minded attitude. The archetypes are based on the idea that people’s mindset travels continually back and forth through an infinity-shape loop (Figure 1), between more (left) and less (right) comfortable zones; its however where people sit for most of the time that define their profile and allows them to make a substantial difference (or not).

Figure 1

Figure 1. Schematic representation of the three personality archetypes. The archetypes are based on the idea that people’s mindset travels continually back and forth through an infinity-shape loop (Figure 1), between more (left) and less (right) uncomfortable zones. Drive for dev: derive for development.

  • Type 1. Balanced profile, which reflects the mindset of the majority of people. They spend most of their time in their comfort zone (Figure 1), but can, when required and/or when pushed by others, step out transiently to grow and make substantial progress. Most of them stay nevertheless for a long time on the left side of the loop by laziness and/or naively believing that “it will be ok”. The others miss a strong drive for improvement, and/or self-confidence to make the Type 3. Their chances to make the 10-25% are real but limited; those for the good jobs are almost null.
  • Type 2. These people have often been working in high-level positions for a long time, both at the academic (e.g., head of faculty or departments, journal editors) and practitioner (e.g., head coaches, head physios and strength coaches) levels. They have chosen to ‘be’, rather than to do, even though this meant compromising their integrity at some stages. This is not a problem for them, as long as their titles, salary, public roles are secured and allow them to feel unique and important. Centred on themselves, they check the boxes, and continue within the same looping circle that keeps them in their own comfort zone (Figure 1). They purposely avoid challenges and can’t be bothered listening to others. They are “more satisfied with old problems than committed to finding new solutions”.6 When it comes to giving lectures, they teach what they know, not what the students need. They want to have their names on papers as last authors, but they wouldn’t be able to collect the data or discuss the stats and study findings. Their blindness keeps them away from the recent literature and the reality of journal requirements (i.e., topics, quality, designs), which inevitably leads to inappropriate and irrelevant submissions, likely to be directly rejected by editors. In some extreme scenarios, people keep digging deeper against the evidence. For example, while the need to move away from the null hypothesis testing approach is in the process of being accepted,7,8 those running into their own circle (or staying on orbit9) still ignore effect magnitudes10 and chose to further decrease the P value threshold to make decisions (<0.005)11!? In high-performance sports, those people don’t read research papers either, never update their skills and methods. They avoid to use new technologies and keep delivering outdated programs. They purposively don’t share what they do to protect themselves. Their focus on their own personal comfort is so prevalent that it often derails the optimal training or recovery process of the athletes they are in charge of. “They want to wear the tracksuit but not run the laps”.3 Providing any advice to help those people is a waste of space here, since they would not be reading these lines anyway. While they made some of the 10-25% or got some of the good jobs by luck and opportunism, their future is related to their political and survival strategies.
  • Type 3. Complete opposite of Type 2. Ultimate progression of Type 1 toward the right side of the shape (Figure 1). Those people are selfless, open-minded, curious, ambitious, accountable for their actions and show a critical mind. They know well that getting “out of the box” is necessary to learn, grow, innovate, create and eventually, succeed. They have understood that life is continuously brought into question, and are always willing to do better. They have embraced the uncomfortable truth that natural assets and talent can be outmatched through consistent efforts, deliberate practice,12 and in turn, the development of skills. There are open to constructive criticism.13 They listen more than they talk. They are not afraid to ask for help. They accept and acknowledge their errors to learn from them. In fact, they set very high standards for themselves, apply strict self-discipline and tend to be long-life learners:14 they read daily, listen to podcasts from various fields, travel, seek for information in different disciplines and always say yes when it comes to share experience and knowledge. They are more concerned by the process than by the results. They are interested in “doing”, and act to keep their integrity. They treat everyone the same, regardless of their status.14 They are those the more likely to make the 10-25% and to get some of the highly-competitive jobs.

Everyone is free to take the life path they want, and there are likely as many ways to follow as there are people. While I’ll never feel entitled to give any lessons to anybody, there is a feeling that less ego, more open-mindedness and collaborative work (i.e., Type 3 archetype) should help getting more quality papers out and delivering better programs to athletes. Successful people manage to enjoy life daily and keep doing what they want, which helps them to realize their potential both at the academic or field level. Getting out of box is likely compulsory to achieve this on the long term.

Martin Buchheit

Associate Editor IJSPP

 Acknowledgements: Many thanks to my Type 3 friends Mathieu Lacome, Ben Simpson and Yann LeMeur for their insightful comments on a draft of the present manuscript.

References

  1. Ingham S, A letter to the 15000. Https://www.Supportingchampions.Co.Uk/single-post/2015/09/27/a-letter-to-the-15000-updated-for-2016, in Supporting Champions. 2015.
  2. Godin S, Linchpin: Are you indispensable? 2011, London: Peunguin Books.
  3. Close GL, Changing an athlete’s behaviour: What can we learn from sport psychology? Http://www.Closenutrition.Com/?P=619, in Close Nutrition. 2017.
  4. Buchheit M. Chasing the 0.2. Int J Sports Physiol Perform, 2016;11(4):417-418.
  5. Mujika I. Winning the big medals. Int J Sports Physiol Perform, 2017;12(3):273-274.
  6. Maxwell JC, Thinking for a change: 11 ways highly successful people approach life and work 2005: Warner Books, Inc.
  7. Buchheit M. The numbers will love you back in return-i promise. Int J Sports Physiol Perform, 2016;11(4):551-4.
  8. Nuzzo R. Scientific method: Statistical errors. Nature, 2014;506(7487):150-2.
  9. Buchheit M. Houston, we still have a problem. Int J Sports Physiol Perform, 2017:1-13.
  10. Cohen J. Things i have learned (so far). American Psychologist, 1990;45:1304-1312.
  11. Benjamin DJ, Berger OJ, Johannesson M, et al. Redefine statistical significance. Nature Human Behaviour, 2017. DOI: doi:10.1038/s41562-017-0189-z.
  12. Ericsson KA and Pool E, Peak: Secrets from the new science of expertise. 2016: Boston: Houghton Mifflin Harcourt.
  13. Cressey E, The success is in the struggle. Https://ericcressey.Com/the-success-is-in-the-struggle, in Eric Cressey. 2017.
  14. McCaw A, 7 keys to being a great coach: Become your best and they will too, ed. K. Whyte. 2016: PrintShopCentral.com.

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.