Never too late to do well. In this post, I will present the works that I found interesting and innovative in my current main field of research: sports performance and especially explosive movements like jumping or sprinting.
Maybe it is only a feeling, but Covid pandemic seems to cause an inflation in published-submitted reviews of literature or opinion-editorial papers, i.e. non-experimental science. While these pieces of work are sometimes informative, justified and important, the drawback is that “publish or perish” in the Covid restrictions context leads to works that are not justified (e.g. 6th or 7th review on the same topic over the last 5 years) or not informative (e.g. systematic review with bold conclusions based on 3 or 4 experimental papers without risk of bias assessment). So, what I really hope for 2021, and what I wish for the PhD students I supervise and others, is that experimental research will resume so new results are published, instead of (or at least in addition to) old results being reviewed, meta-analyzed or commented.
New Lab, new place…back to the future
First, the big change for me in 2020 was to move from the University of Nice back to my former Lab at the University of Saint-Etienne. Since I left in 2014, the lab has become a 100+ members team spread over three Universities in the Rhône-Alpes Region: Lyon, Saint-Etienne and Chambery. The research team is led by Pr Guillaume Millet, and I was also happy to join two other of my main collaborators Pr Pascal Edouard and Dr Pierre Samozino.
Discover our research team “LIBM” on the website of the lab and our great facilities at the IRMIS (Regional Institute of Sports Medicine and Engineering) in this video summary. From muscle cell biology to exercise for health and sports performance. Follow our Twitter account here for some news. Feel free to contact me for a visit when you’re in the center of France!
Force-velocity profile in jumping, “2-load” testing approach confirmed
This open access study by Sarabon et al. compared the linearity, validity and reliability of the lower limbs force-velocity relationship obtained in laboratory conditions (gold standard measure of force and velocity during push-off with a force plate system) between three modalities:
1/ Classical multiple-load procedure with additional loads ranging from 20 kg to the load with which athletes could comfortably jump more than 7.5 cm (30 to 100kg in this population)
2/ “2-load” approach suggested in a recent study by Amador Garcia-Ramos et al. using the 2 extreme loads (i.e. unloaded jump for the light load point and the highest additional load for the heavy load point)
3/ a “novel Jump-MVC” method, using unloaded jump data and force obtained during an isometric maximal contraction push performed in a still position close to that of the push-off phase start.
The main results show that the classical multiple load method generates highly reliable linear FV relationships, and that the 2-load approach leads to very similar outcomes. This confirms previous works performed in similar laboratory conditions by Samozino et al., Giroux et al. and Garcia-Ramos et al. for the “2-load” approach.
This study also confirms that using only 2 loads (bodyweight and the load associated with a 7.5 to 10 cm jump height) leads to reliable force-velocity analyses, which could save testing time. This could be expected since a linear relationship can be obtained in theory from only two data points. However, when applying this approach in practice, it is necessary to keep in mind that these results were obtained in laboratory conditions, and that reliable results require reliable jumping ability, height, technique and measurement devices. Clearly, if jump height and push-off distance (main mechanical inputs of the approach) and/or measuring devices are not reliable, then force-velocity outputs will show poor reliability and difficult interpretations. This is what we observed in our own practice and unfortunately in recently published research, which we will discuss soon (and likely within the 2021 edition of my take-homes).
Improving jump height: effectiveness of an individualised training based on “force-velocity imbalance” in professional rugby players
https://pubmed.ncbi.nlm.nih.gov/20109471/Following the pilot study of Pedro Jimenez-Reyes et al. in 2017 and a replication and confirmation study published in 2019, this study published by Simpson et al. was performed in a professional rugby context. During the final phase of their pre-season, the players followed either a training content that was indexed to their individual FV “imbalance” (for full details on the concept see the basic papers by Pierre Samozino in 2010, 2012, 2014 and 2016), or a general power training that was common to all members of the control group, and most importantly, not designed to stimulate the weakest part of the profile for each individual. The main result was that after the 8-week protocol, the FV profiles in the intervention group got closer to the individual optimal value (i.e. FV imbalance closer to 0), and squat jump height improved clearly more than in the control group.
In addition to bringing an independent, external confirmation of the results obtained in laboratory conditions by Pedro Jimenez-Reyes, this study shows that such an individualized approach can be implemented in a real-life scenario and elite rugby context. This is also what we are currently doing at the FC Grenoble Rugby in France during the PhD program of the S&C coach of the professional group Patrick Chassaing. Some preliminary results presented during a French Rugby Federation symposium (here, in French) tend to confirm the effectiveness of this approach. Of course, whether it is important, useful, necessary to improve jumping capability in Rugby players depends on the role, position, initial capability and many other context elements, but the point here was to discuss and test how, not why.
Finally, an interesting secondary finding of this study was that, in this group of high-level rugby players, clear improvements in jump height likely caused (in part) by a decrease in their FV imbalance were not associated to significant improvements in 10-m or 20-m sprint performance. This result seems to indicate that training for jump height and sprint acceleration are two distinct processes, at least in elite rugby players. Our unpublished data confirm that over the course of a professional rugby season, changes in vertical jump and sprint performance are not correlated.
Sprint acceleration mechanical outputs profiling: important updates and application to ice hockey
Based on the simple method for computing sprint acceleration mechanical outputs initially proposed by Pierre Samozino in 2016 and confirmed in our study using a single sprint approach in 2019, studies are published or in review that bring “normative” data for various sports and levels (e.g. Jimenez-Reyes et al. 2018). An interesting extension of this approach was presented to analyse on-ice acceleration in Ice Hockey players, first by Jerôme Perez et al. in 2019, which was confirmed by Lauri Stenroth et al. in 2020. This study confirmed the possibility to compute the main sprint acceleration mechanical variables (horizontal force output, displacement velocity, associated mechanical power, orientation of the ground reaction force, etc…) over time, based on the modeling of position- or speed-time data with an exponential function.
To know more about the model used here, see this lecture recorded by the International Society for Sports Biomechanics.
The main results show the validity and reliability of the approach, but also and more importantly, that these are improved when adding a “time shift” correction to the exponential model for actual start of motion data. This is what we’ve also added to our simple computation method published in 2016, as discussed in our book published in 2018 and our paper published in 2019 comparing computed data to gold standard force plate measurements.
What I really appreciated in this study is that the authors generated a free spreadsheet that includes the time shift correction for improved measurement validity, but also allows computing markers position for video-based analyses of motion with any filming distance and sprint acceleration splits. (Download the spreadsheet here). It is great to see that young scientists openly share their work and help others freely and easily apply their methods and conclusions in real-life setting. This adds to our updated spreadsheet for the same computations based on speed-time measurements (e.g. radar, GPS, laser, 1080Sprint, Dynaspeed devices). (Download the spreadsheet here). Also, the authors show that using an Apple device and MySprint app is not obligatory, provided your video device (GoPro in their study) has a slow motion mode >100 frames/second and you can analyse the videos for split times (for example with the free online Kinovea application).
Finally, an important point to keep in mind is that, as for any model, the reliability of the output variables (F0, v0, Pmax etc) highly depends on the validity and reliability of the input variables (position- or speed-time data recorded during an all-out acceleration). So, if input variables are not measured correctly and/or athletes do not perform with maximal effort, no surprise, computation outcomes will not be reliable.
Seasonal changes in sprint acceleration mechanical outputs in professional football players
Descriptive studies and normative data of sprint acceleration mechanical outputs and “force-velocity-power” and mechanical effectiveness of ground force orientation (for definitions see this 2016 paper) are scarce in elite football (i.e. international level or professional level in a major European league). This pilot study (professional players from a Sanish Liga team) led by Pedro Jimenez-Reyes shows these changes in mechanical variables over the course of a season between pre-season1 (September), four times in-season (November, January, March, May) and pre-season2 (August the next season).
The main result was that some variables show significant changes (e.g. maximal power output in relation to the maximal propulsive force output in the antero-posterior direction, and the maximal ratio of force) but others did not (e.g. maximal running velocity). In addition to showing that such a frequent monitoring of these variables is possible in an elite context (only one or two maximal accelerations over 30-m are necessary as explained in this previous blog post), these results may help coaches better anticipate and design individual programs to avoid “throughs” in sprint-related mechanical variables over the season.
The reasons explaining these seasonal fluctuations (fatigue, lack of specific in-season stimuli…) and whether specific training could help maintain sprint-related physical performance justify further studies. I think that the two next big steps in sprint training for team sport are related to (i) a more individualized approach of the training content: different profiles, different positions, status, different training regimen and (ii) focus on “how” players sprint, i.e. their sprint kinematics and pattern, in addition to how much force they generate. Software and hardware… Good news is that some studies discussed in this post and others in preparation will focus on these interesting tracks.
On a similar topic, I really liked this open-access review of literature by Nicholson et al. about improving short sprints performance in football. The main outcome is that the sport itself and primary (sprint) type of training are likely not efficient approaches, except when combined with secondary (e.g. resisted sprint training) training, and tertiary methods (e.g. basic and specific strength work and plyometrics) which seem to provide efficient overload and stimuli. Evidence that 2020 was not only a “one more useless or underpowered meta-analysis” year.
Better acceleration mechanical outputs after resisted or assisted sprinting: highly individual adaptation magnitude and kinetics
Resisted sprinting is an effective training stimulus/overload to improve sprint mechanical outputs and in turn performance. I’ve covered the topic in several blog posts (e.g. this one) and you may read more about what we know and don’t know on the topic in the works of Matt Cross and our group. Two papers we’ve published in 2020 clearly show that the training response (magnitude and kinetics) to high resistance sprint training (and assisted sprint training in the case of Johan Lahti’s study) differs between individuals, even within the same training group. In the open-access study of Johan Lahti et al., professional rugby players trained with either very high resistance (sled load associated with a 70-80% decrease in maximal running velocity) or assistance (1080Sprint machine pulling them 5-10% faster than their maximal running velocity). The main results show improvements in key components of the force-velocity profile (expected from previous studies) such as maximal power or force output, but one very interesting and new result is that the “group mean” changes were associated with very different individual responses. The story of the group is not the story of each member of the group, which echoes one of my blog posts about the risks of “averagiarism”, i.e. interpreting each individual’s behaviour based on the group trend. More specifically, a deeper analysis of the individual training-induced response showed that the players who responded beyond the minimal detectable change threshold to either very heavy resisted or assisted sprint training.
This study also included several measurements post-training, to monitor the individual changes in the main variables after specific training cessation. I guess more than 95% of intervention studies (including ours until 2020) use a typical “pre-post” design where variables are compared between one week pre (or at the first session) and one week post (or at the last session) 4-12 weeks of specific training. This is a limitation since it does not allow researchers to assess (i) baseline pattern of the variable tested before the intervention (several time points instead of only one) and (ii) post-intervention kinetics and possible tapering effect, “rebound effect” and de-training effect. After obtaining unexpected results in one of our previous protocols, we realized by talking with the players and staff that some players benefitted from the high resistance training intervention right after the 10-week stimulus (i.e. at the moment of post-tests) while others were still adapting to the overload and were under-performing at that time. According to their coaches, they were really more powerful and better at sprinting 2 or 3 weeks after. Issue #1: we measured and analysed their data at the time they were “down” and likely still overreaching, so they were negative responders at that time which skewed the group results. Issue #2: we did not record their peak performance data when it occurred a few days/weeks later, at the time their maximal power and sprint performance were peaking, likely as a result from the training intervention. Different individual adaptations kinetics, but one single, one-size-fits-all pre-post testing design and picture. Nonsense, how could we miss that.
To better illustrate the point of individual kinetics and magnitude of adaptation to sprint resisted training, Pedro Jimenez-Reyes ran a heavy sled training protocol in well trained sprinters (individual load associated with 50% decrease in maximal running velocity). We compared the classical “one week pre – one week post” changes in the main target outcome (maximal power output) to the individual “pre-peak” change, i.e. the difference between the pre value (measured one week before training start) and the peak value recorded over the four weeks that followed training. The main result was that the pre-peak stats were much clearer than the pre-post, which comes from the fact that athletes differed strongly in their response pattern. This “individual adaptation kinetics” may impact the interpretation of research protocols (or training studies) in which a significant overload is programmed, and single measurements are performed pre and post. The typical “one week” post measurement window may mask delayed positive adaptations and illustrate the “overreaching” window rather than the real training-induced changes. The second major result is that the peak in maximal power output occurred at week one, two or three depending on the athletes, with no clear group trend. We concluded that in addition to “group average” trends and results, training studies should report and interpret the individual response patterns. To do so, repeated measurements of performance or main outcomes studies should be (if possible) performed both pre (baseline trend) and post (adaptation kinetics) intervention.
This gap between group average trend and individual was also discussed and brilliantly illustrated in an open-access study by Neil Welch (Sports Surgery Clinic Dublin) et al. in the context of a rehabilitation protocol. The summary points provided by the authors are clear and carry major ilmplications for better design and interpretation or training and/or rehabilitation interventions: “None of the single-subject profile intervention was the same as the between-group intervention. A single-subject approach can show detail that is lost in a between-group approach”.
This “individual puzzle” approach was discussed in one of my previous posts on the limitations of group-average analyses, and will be the basis of a multifactorial, individualized protocol for hamstring injuries prevention in soccer. This protocol was detailed in an open-access paper by Johan Lahti et al. and the ambitious approach is to screen for various know risk factors so that each player’s prevention “menu” is indexed on their own profile and needs in terms of range of motion, posterior chain strength, sprint mechanical output and lumbo-pelvic control.
The intervention study is in progress within several professional football teams, and Johan Lahti explains this approach in details in this webinar:
Resisted sprint training with high resistances does not alter the unresisted sprint pattern. A pilot study in professional football players.
This open-access study by Johan Lahti is the first one to analyse the acute (during resisted sprinting) and long-term (after a high resistance training program) changes in sprint acceleration mechanical outputs and sprint kinematics (sagittal plane motion of the main body segments). The “training with heavy sled will ruin athlete’s running pattern or technique and cause injuries” assertion was based on no scientific data until this work, but I guess every coach or researcher had their own opinion (as discussed in a previous post). Like the dish young kids don’t like but have never tasted, high resistance sprinting (i.e. pulling sleds or loads that slow you down by at least 50% of your maximal speed, typically 50-120 % body mass depending on athletes and conditions), these opinions were not supported by data. The paper is very detailed and addresses four research questions at a time: what changes in the mechanical profile (force, velocity, power output) after high resistance sprint training in football players? What consequences on their normal sprint pattern? Is a very heavy load (60% velocity decrement) more effective than a heavy load (50% Vdec)? Are individual training-induced changes related to the players initial profile at the beginning of the protocol?
To summarize the huge amount of experimental work and data processing put in by Johan and the S&C coaches involved, here are the answers to the initial questions:
1/ Yes, high resistance sprint training in the form of heavy sled leads to improved maximal force, power and “effectiveness” of the forward orientation of the ground reaction force.
2/ Acute changes in sprint pattern (obvious when pulling such heavy sleds) are not observed during unresisted sprinting, so improved kinetics do not come with altered kinematics (see the stick figures). Myth busted?
3/ No, very heavy does not seem to provide a better stimulus in this population than the “optimal” 50%Vdec load.
4/ Yes, there is a significant correlation between the training-induced changes in maximal force output and the initial level of the players. So the magnitude of the training response seems to depend on the initial profile of the players, as observed in our study on rugby players? This may have consequences on individualising training input as a function of the players profile.
It is very important to note that these results were obtained in professional football players used to high resistance strength training and heavy to very heavy sled training, and that as explained above, post-measurements accounted for possible delays in peak adaptations and a taper period. Now whatever your opinion on the topic, you have clear data in this pilot study.
Sprint kinematics: the kick-butt epidemic©️ and specific training to alter pelvic position during locomotion
As observed and discussed by Cameron Josse, team sport players very often show several components of the running pattern that are associated (from a pure functional anatomy and biomechanics standpoint) with higher length/tension in the posterior chain. Running at 10 m/s or more with this pattern (e.g. forward bend trunk, anteriorly tilted pelvis, positive touchdown distance and marked backside mechanics, see Cameron’s post for the “Kick-butt” visuals) may put the weakest links of the posterior chain at risk. This is what pilot studies show in soccer players, for some of these variables. This is also what many experienced practitioners working daily with sprinting athletes and players have observed for years. On this topic, clearly professionals and practitioners’ evidence is more advanced than published academic evidence.
In a pilot study published by Jurdan Mendiguchia, we show that a specific intervention focused on lumbo-pelvic control and reducing anterior-pelvic tilt induced significant and substantial changes (more than 10% on average, see individual changes below) in pelvic orientation as measured during walking gait.
The program exercises are accessible here:
Of course, after this pilot study that simply aimed at testing if pelvis position could change during locomotion after a specific program, Jurdan has designed the similar study, but this time assessing changes during maximal speed running. Previous results (Franz et al.) showed a good intra-individual parallel between pelvic motion during walking and running gait, and the results of the sprint study (under review) confirm those of the pilot walking experiment. In other words, it is possible to change some components of the running pattern via a multimodal, specific training intervention. Never say never. Elite athletes (e.g. tennis players) are able to significantly change their specific sport technique (e.g. motion during the serve) even after years of practice, why would sprint running pattern be the only sport movement that resists to specific training stimulus and cues?
To conclude on this sprint part of the post, I want to highlight the very insightful paper by Dr Ken Clark showing that faster athletes “whip from the hip”. In this detailed study, Ken shows that the hip motion is correlated to other kinematic features of the sprinting pattern, and especially the foot-ground interaction.
In particular, it is interesting to notice that faster athletes have a more synchronous “leg switch” flow, which, again, makes muscle groups crossing and acting upon the pelvis-hip structures key for sprint performance, in addition to injury. See Ken’s presentation on the topic:
Added to previous important studies on the topic of acceleration performance (Schache et al.) or injury prevention (Chumanov et al.), this study confirms that the pelvis-hip is a central “hotspot” for sprint mechanics and performance, as it is for injury prevention.
What about deceleration?!
All the studies mentioned above focus on acceleration or top speed, and so does 99% of sprinting literature. This is not normal since sports performance depends also highly on the ability to decelerate. Except for studies on change of direction, deceleration “performance” and mechanics had rarely been studied specifically. Partly for methodological reasons and lack of basic and common descriptors. In 2020, two studies started filling this knowledge gap. The first one led by Damian Harper presented a deceleration test and associated performance and mechanical markers. This study will surely help future works build a common terminology and database, to help better understand the role of deceleration capability in sports performance, and design/interpret training interventions.
The second study (2020 year of deceleration?) published on the topic last year explored the detailed kinetics (ground reaction force and associated variables) and kinematics of sprint deceleration. No surprise this thorough work is published by a reference researcher on sprint mechanics, using a reference, world unique 60-m force plate system: Dr Ryu Nagahara. In this collaborative work with Dr Olivier Girard, the authors show how athletes decelerate, and what key mechanical variables are associated with deceleration in a voluntary decelerated run test.
Among the numerous results presented, one key message is that an altered ability to maintain the magnitude of ground reaction force applied during the propulsive phase may cause greater braking force. The step frequency, contact time and net anteroposterior mean force output are determinants of the magnitudes of decreases in running speed. A bit like during acceleration, but the other way around…
Force-Velocity-Power: Endurance, the missing link and next frontier?
All the papers discussed in this post, and the vast majority of published works on maximal dynamic capabilities consider exercises performed in a fresh state, in theoretically ideal physiological conditions. While this provides insights into the maximal absolute capabilities of athletes and participants tested, it does not consider a major component in many sports: fatigue, and the alteration of these capabilities with time, and efforts repetition. How will my profile change in fatigue conditions? For the same power output constraint, will the underlying level of force output (thus movement velocity) have an influence on my endurance capability? Will this differ between individuals? How will this impact the design and interpretation of testing and training for team sports or other sports with repeated intense efforts? Does F, V and P influence “E”, and vice versa?
This fourth dimension of the “force-velocity-power-endurance” analysis is studied at our Lab with the coming works led by Dr Baptiste Morel and Pierre Samozino (see this open-access paper for example). In 2020, Dr Jean Romain Rivière published this very interesting open-access paper in which the “endurance” i.e. number of dynamic tasks (jumps) that can be performed above a given threshold until failure, is shown to depend on the dynamic force, velocity and relative power conditions. The future of force-velocity-power-endurance research is not simple (so many questions to address and methodological challenges), but research results may have major consequences on our understanding of endurance testing and training in high-power output tasks like jumping, sprinting, kicking etc.
Current and coming projects: foot strength for athletic performance?
The main research projects I’ve started at my new Lab focus on foot-ankle strength and power output capability, in relation to health, and physical performance. I hope to comment on our 2021 findings in my next yearly summary, and wish the best to the PhD students I am supervising on this topic, Romain Tourillon and Enrico Roma.
My own sport practice and observations led me to think that foot and ankle are underestimated links (often the weakest ones) of the kinetic chain that produces movements like jumping, cutting and sprinting. I also observed that specific foot-ankle strengthening was useful in many sports “powered” by lower limbs actions onto the ground, so we wanted to seriously address these questions.
In 2020, I noticed two interesting studies on this topic. The first one published by Dr Mizushima and colleagues show that school kids educated to do include barefoot exercises, drills and running in their physical education courses performed overall better than controls in various sprint and jump tasks, with associated differences in biomechanics you would expect (eg shorter contact time in running). Although I’m not a fan of all-barefoot (but who is?), I really think this approach of micro-dosing some barefoot exposure (during warm-up, runs, gym workouts) is an interesting stimulus. Great cost-benefit ratio, you remove some stuff (socks, shoes) and gain a significant stimulus.
The second study published by Dr Taddei et al. in the American Journal of Sports Medicine shows that all types of running-related injuries are clearly reduced in runners following a “foot core” strength program over a one-year follow-up. The prospective design, number of recreational runners studies and the study duration are interesting points, and keeping methodological improvements in mind (“foot strength assessment”, detailed injury mechanisms etc), the main take-home message is clear: adding foot strengthening routines to your training content is useful for prevention. Run stronger, run safer.
Below some illustrations of some of the exercises proposed by Taddei et al. that I also illustrated in a video blog post for the Football Science Institute in which I discuss some simple but effective exercises, try them at home.
Exciting works coming up!
1 thought on “2020 research highlights”
Thank you for this great info!
On Sat, Mar 6, 2021 at 4:39 AM JB Morin, PhD – Sport Science wrote:
> JB Morin posted: ” Never too late to do well. In this post, I will present > the works that I found interesting and innovative in my current main field > of research: sports performance and especially explosive movements like > jumping or sprinting. Maybe it is only a f” >