Random thoughts

I am back from vacation to Zakynthos and I am pretty much recharged. The rest of the season is about to begin and what we did last week in terms of physical preparation was testing of the players and creating player profiles (strength~weaknesses based on team rankings). The newest video by Joel Jamieson was really helpful in this regard (I will do a full review soon) since one of the presentations by Joel goes into the topic of creating athlete profiles based on the test scores. 

Based on rankings (percentiles instead of Z-score since it is more easier to explain both to players and coaches and most of the time data is not normal), each player has spider diagram when we can clearly and quickly see their standing within the rest of the team, along with aerobic-anaerobic profile.  Also, each position has four composite scores (index scores) that include different tests with different weighting factors: speed, explosive power, endurance and strength. This way we can compare players on the same position to the physical demands of the same.   All of this can be found in great presentation by Joel Jamieson.

I am not going to describe our testing battery in great detail, but I will cover some interesting insights.

505 Agility test

When it comes to speed tests, we did 30m run with 10m split, which gives us 10m time, 30m time and 20m fly time. For the agility testing we decided to do 505 Agility test (click HERE and HERE for more info). You can see how it is done in the following video.

Basically, what 505 gives us is the ability to change direction from high speed run. 505 Agility test did not correlate with 10m (r=0,16), 30m (r=0,17) which means we are measuring distinct motor quality.

The trick with this test is to take full speed approach in the 10m. I wonder would the scores be any different if the run-up was sub-maximal, thus making the COD quicker. On the flip side, submaximal run-up may yield longer times to COD line, but more tough COD.

 I will try to find a reliability study for 505, but we are pretty sure the run-up must be controlled with achieving at least 90% of 10m sprint speed which might protects us from pacing of the athletes. If anyone has info on this or experience with this test please contact me or leave a comment.

30-15 Intermittent field test

For endurance testing we decided to do 30-15IFT and MAS test (1600m time trial; 4x400m). The correlation between the two is r=0,67. HRpeak in MAS test was 98% of HRpeak in 30-15IFT on average. 

The guys who sprinted the last lap during MAS test achieved closer HRpeak scores – compared to guys who slowed down at the end (as showed with higher SD of HRpeak as well). Thus, pacing is making conclusion on what is HRmax difficult and I suggest that to be really certain one need to use test specifically designed to elicit HRmax in running. Although 98% was pretty close.

One thing with 30-15IFT and with all other test that have discrete increments is that this might affect sensitivity and reliability of the tests (Martin Buchheit reported ICC r =0,96 which is high reliability. Check the study HERE). For example, we used as the score the stage (speed) at which the player quit/was disqualified (where Martin uses the last fully completed stage, which is basically our method minus 0,5km/h). 

Some of the players quit during the stage and some of them quit during the recovery. In Martin’s method, should there be a difference between a player who completed the stage and then quit, or the guy who completed the same stage, waited for 15sec recovery and started then next stage and quit during it? Their test score would be the same, yet I think they are slightly different (sensitivity of the test).

 Without having the strict protocol about this it might affect reliability of the tests and thus its sensitivity to evaluate training effects. I know Martin Buchheit reported high reliability, but I would love to see longitudinal study reporting ES and percent change compared to CV of the test, since I think lower sensitivity can artificially improve reliability score (do I need a reference for this, anyone?).

Still, if I would design a test  I would love it to start at higher speed, have more stages at certain speed (instead of only one) and provide a way to deal with the situation mentioned (maybe timing of the quitting?).   

Up to this point I find 30-15IFT the best test for creating individualize groups for intermittent conditioning.

We did both test since we plan using MAS for longer intervals (like 3x3min) and v30-15 for more intermittent intervals (like 15-15 or 30-30). As far as I remember the relation between v30-15 and vVO2max (assessed with incremental protocol on treadmill or on track) reported was around 80% of v30-15. If v30-15 is 20km/h, according to this formula MAS is about 16,6 km/h. In our case, MAS (average speed over 1600m time trial) was 75% (range: 68-81%).  

My training

Since writing on that bench study  I wanted to play with Power Tool / GymAware with my own training. So, I decided to give it a shot.

After couple of weeks of doing nothing, my lifts detrained a little bit, especially the bench press. I tested them using 1RM test with pause on the bottom of the lift and aiming to have perfect form.

My BW was 91.x kg in the morning, but during the testing was 93.3kg. I managed to do 100kg bench press (please don’t laugh – it was with 2 sec hold on the chest and no helper-spotter… don’t ask what happened when I tried 105kg), squat 155kg and pull-up with 45kg attached (which makes it 140kg total with BW). Everything was strict form with no psyching up, yelling and acting like a gorilla. Not too bad except the bench press.  

So, I am starting a training program where my aim is to improve my VJ, counter movement jump with 20kg and 40kg (mean power to the bar – which means that I don’t take into account system weight, or in other words BW – I went with this with Dan Baker over the email) and bench throw with 40kg. I didn’t do any specific/dedicated testing for them, so I will collect the data from the week #1.

Along with that, I will use Power Tool to stop my squat and bench press sets when my speed/power drops below 90%. Thus, I take the weight, lower it, make a pause and try to move it fast on the way up. Repeat until power drops to 90%. So, no failure and a lot of quality sets with pyramid progression (i.e. week 1 – 75%, 80%, 85% x 3, week 2 – 77,5%, 82,5%, 87,5%, week 3 – 80%, 85%, 90%, week 4 - unload). For easy days I will do 60-70% for 3 sets of 5.  

I have attached the week 1-2 program I created in Excel.  I basically used Joe Kenn template from Tier System and his percent based cycles for some of the lifts.

On the following video  you can see me performing bench throw with 40kg using Power Tool and newest version of GymAware iPhone app. It is AWESOME! I can take a real time video, then the app inserts power reading. This way I can see real time correlation of technique and power reading and then make correction, etc, etc.  Everything is so intuitive and quick and I am more than happy that we have Power Tool.

So, my power output (P40kg) is 354W which is 3,79 W/kg. I will see how is this going to improve over the weeks, along with 1RMs in bench, squat, pull-ups, VJ, and squat jump with 20 and 40kgs. Also, I will be doing running conditioning along the way. Will report back how this goes.

Till next time…

RSA is overrated? Part 4

RSA is overrated?

Part 4

I want to finish this article so I can go to vacation with ‘clear head’, and spend my time eating gyros, swimming and playing beach volleyball instead of thinking about RST/RSA/RSS.

I am afraid that this article got away from sole RST/RSA/RSS discussion. The things I warned against, besides trying to answer whether RST/RSA is overrated, are the following

• Watch out for the mean/average values – pay more attention to variability of the data, distributions, zones and how the data evolves over time

• Watch out for the velocity based time motion analysis (especially with absolute zones without relative ones) – pay more attention to acceleration and power expression, not only movement speed.

• Watch out for the linear/mechanical logic, especially deducted from the cross-sectional studies (whose conclusions were based on mentioned flaws) – pay more attention to longitudinal studies and complex systems logic

Regarding the first bullet-point, David Tenney from Seattle Sounders recommended me a book Flaw of Averages by Sam Savage worth checking. When I checked the author’s website, the following picture popped out: 

I just can’t agree more. 

Another feedback I received lately was by Martin Buchheit regarding intermittent critical power (iCP) concept. He actually did a study on it (Int J Sports Med. 2008 Apr;29(4):307-15), which I forgot to reference. You can check it HERE. The conclusion was that iCP is basically hopeless.

When it comes to velocity-based time motion analysis, I already pointed out to the two posts, but I will repeat this one more time and stop bitching on it for the rest of the article (please check THIS and THIS  posts). Instead I will focus on the last bullet-point: Watch out for the linear/mechanical logic.

The mentioned linear thinking can be depicted in the following way:

Let’s deal with the first link. Will RST improve RSA? I’ve covered this problem in my Troubles with RSA article, but I want to give you a heads up on the article/commentary by Martin Buchheit in  Sports Med. 2012 Feb 1;42(2):169-72 (check it HERE). Basically, Martin concluded the same think (but with more proof). Here are some of the sentences:

...In support of this, a speed/agility training programme targeting the development of COD speed more precisely, resulted in greater improvements in both linear sprinting speed and RS performance than RST.[5] Taken together, these data suggest that RST is likely effective at improving pre-planned COD speed, but not for developing linear speed qualities and RSA per se. Therefore, the suggestion of using ‘‘repeated-sprint training to improve sprint performance’’ (p. 750[1]) is misleading ...Again, this suggests that the greater improvement in RS performance following RST is more likely related to the training specificity of RST and testing, rather than to improvements in RSA per se. In support of this idea, the only HIT programme that was more effective than RST for improving RS performance included COD at high speeds ...Finally, if sessions targeting ‘isolated’ physiological capacities need to be implemented, it is important to consider the best predictors of RS performance. While it is clear that maximal sprinting speed is the strongest determinant,[1] the relative importance of other parameters such as maximal aerobic speed (MAS), VO2max, and on and off-O2 uptake (VO2) kinetics have been overlooked.[1] ...A faster MAS is associated with a lower relative exercise intensity during the between-sprint recovery periods and reduces the proportion of the anaerobic reserve[15] that is used during the RS exercise.[16] This likely results in a lower anaerobic system participation and diminished local peripheral physiological disturbance and, in turn, a better RSA. In a practical way, these data suggest that the development of these two key running speeds (maximal sprinting speed and MAS) should be targeted first when the goal is to develop RS performance in team sport players. All additional training strategies targeting specific physiological adaptations (e.g. buffer capacity or phosphocreatine resynthesis) are also obviously welcomed.[1] ...To conclude, a combination of all training methods is probably the best option in real practice.[1] I will always keep in my records the 2004–5 season of my formerHandball team (Se´lestat, First French League), when, as a strength and conditioning coach, I almost exclusively implemented RST during the preparatory phase. While there is obviously no direct link between the players’ physical capacities and the game outcomes, the team had the worst start to the season in years (possible interference phenomenon[17]). Interestingly, the team became much more successful during the second part of the season, when handball specific but ‘isolated’ speed and HIT training sessions were implemented. Taken from Sports Med. 2012 Feb 1;42(2):169-72

 

When I was chatting with Håkan Andersson we touched upon this RST à RSA issue (click HERE to read the interview with Håkan). His opinion was to take context/athletes into account – soccer players (with couple of exceptions) are not even close to high level sprinters, and thus training aimed for high level sprinters might not be needed for soccer players. This included speed work with very long rest, etc. So, RST might kill two birds with the same rock. I am not sure if I completely agree with this – I am more in line with Martin Buchheit that possible the combination of the methods might be the best option. I am not sure if I touched upon this, but I am pretty sure I warned against blindly applying training methods and planning/programming from power/endurance sports for mixed sports in THIS article.  To keep the long story short, in my mind the story of improving RSA goes like this:

Of course, this logic is valid only if improvement in RSA is related to improvement in Game Performance (and if that actually matter for the final outcome). I will come to this ‘flawed’ logic of mine later. 

When it comes to the logic that improving RSA or any other physical preparedness quality will improve game performance, most of our proof is based on the cross-sectional studies and correlations. In the letter to the editors (Eur J Appl Physiol. 2011 Sep;111(9):2387-9), Martin Buchheit  (yes, the hero of this article) and Alberto Mendez-Villanueva were critiquing the series of studies on YoYo test by a group of authors (Bradley et al.) in which the concluded that YoYo was sensitive to predict match-related physical performance in soccer. I won’t go in much detail here (make sure to check the article HERE) besides quoting the title (Physical Capacity-Match Physical Performance relationship in soccer: simply, more complex) and the following sentence: 

...Thus, the fact that players occupying different positions have similar physical capacities (i.e., Yo-Yo IE2 test) despite the marked differences in match physical performances suggest that the game’s tactical requirements rather than players’ physical capacity might be more important in determining on-field players’ activity patterns

Speaking from my own experience, we had GK that covered more distance in YoYo Intermittent Recovery Test Level 1 than couple of fullback and middle fielders. 

Thus, it is hard (impossible?) to conclude that players with better physical qualities (MAS, YoYo, etc) will perform better physically (more HIA, RSS and even ball contacts, etc) in a game (without taking game tactical constraints of the positions played into account), and it is even harder (more impossible?) to conclude that improving physical qualities will improve physical game performance, especially out from cross-sectional data. 

The first longitudinal study to measure effects of improvement/decrements in physical capacities on game performance that is going to be published in Int J Sports Med is Repeated High-Speed Activities during Youth Soccer Games in Relation to Changes in Maximal Sprinting and Aerobic Speeds by Martin Buchheit, B. Simpson and A. Mendez-Villanueva.  You can read the slides from the presentation at 3rd World Conference on Science and Soccer, Ghent, Belgium HERE. 

The advantages of this study is that it compared improvements/decrement in MAS (Vam-Eval) and Vmax (MSS – Maximum Sprinting Speed) on the occurrence and nature of repeated-sprint sequences, but assessed in two ways: absolute (defined as at least 1sec long and  above 19 km/h with maximum of 60sec recovery) [RHSS] and relative (defined as at least 1sec long and  above 61% of individual MSS with maximum of 60sec recovery) [RSS].

The disadvantages were that it involved only MAS and MSS tests (no RSA), the long delay between sprints in RSS (longer than the other studies, which used below 20sec), 1-Hz GPS unit and it involved junior players (14.5 year old players). Anyway, even with that ‘flaws’ this study is unique in it’s longitudinal study.

Also, improvements/decrements in MAS and MSS were judged as greater or lower than ½ of coefficient of variation (CV) of each test (which they assessed previously). This is great statistical method, along with using Effect Sizes, which they did.  

I won’t go into deep analysis of this study, but I will copy-paste some of the interesting sentences:

...It was recently highlighted in highly-trained young soccer players that the relationship between on-fi eld running performance and physical capacities is essentially position-dependent [ 7 , 30 , 31 ] . In fact, for some positions, the magnitude of the correlations between match running performance and physical capacities is very large (e. g., strikers), while for others, very low and non-significant (e. g., centre-backs). This is probably related to the fact that tactical duties associated with playing as a defender limit running activities. In contrast, attacking players have more space and opportunity to express and use their full physical potential ... We examined, in highly-trained young soccer players, whether substantial changes in physical capacities (i. e., MSS and estimated MAS) can impact repeated high-speed efforts (i. e., the occurrence and nature of repeated high-speed and sprint sequences) during international club matches. With data limited to 1-Hz GPS analyses, the main results are as follows:  1) a substantial increase in either MSS or V Vam-Eval was at least likely associated with a greater RHSS occurrence, while the magnitude of this increase was position-dependent,  2) a substantial increase in either MSS or V Vam-Eval was likely associated with a lower RSS occurrence during games, but for some playing positions only, 3) despite the limited available data, substantial reductions in either MSS or V Vam-Eval were associated with maintained or even small-to-moderate increases in the occurrence of both RHSS and RSS, and finally 4) the effects of substantial changes in physical capacities on the number of high-speed efforts and sprints per RHSS and RSS were clearly position dependent. ...Not surprisingly, the players who became substantially faster (+4 to +7 % in MSS) and/or fitter (+7 to +13 % in VV am-Eval ) managed to perform a greater number of runs above 19 km.h – 1 (i. e., RHSS) during games (+5 to +44 %). Present results are in accordance with previous longitudinal studies, where well-trained young soccer players [ 23 , 26] were shown to cover a greater distance at high intensities after a short training period leading to improved physical capacities. Taken together, these data show that, at least until a given fitness level is attained [ 5 ] , improving both MSS and MAS is likely beneficial for high intensity running performance. While there is obviously no direct link between match running performance and success in soccer [ 11 ] , a higher match running capacity might still enable more involvements with the ball and increase scoring opportunities[ 19 , 23] . Whether an increase in MSS can have a greater impact on the ability to repeat high-speed efforts than an increased V Vam-Eval is not easy to examine with present data and limited sample sizes. It is however worth noting that the associated changes in game activity were of similar magnitudes. In a recent study in 61 team sport players, both MSS and peak incremental test speed were shown to be the strongest determinants of repeated-sprint performance [ 6] ; MSS showed however larger association with mean repeated-sprint time than peak incremental test speed. In this regard, both MSS and V Vam-Eval can theoretically impact high-intensity, intermittent running performance, but in different ways ...In accordance with our initial hypothesis, these results show that changes in physical fitness and match running performance are not necessarily matched, and that playing positions can affect these relationships.  In other words, this suggests that the observed improvements in running performance during games may be more related to tactical and strategic factors than physical fitness per se . This idea is further supported by the fact that the players displaying a substantial decrement in V Vam-Eval performed more RHSS per games (i. e., full-backs and centre-backs) Similarly, midfielders showing a decrement in MSS managed to maintain their number of RHSS per game. Since a majority of the other players became fitter and performed more high-intensity running during the second series of games, we can hypothesize that the players showing impairments in physical capacities had to increase their work rate during games to match those of their teammates. This suggests that fitness level was an unlikely limiting factor to their high-intensity match running activity. … The older players, while being fitter, performed less sprints and less RSS than their less fi t (and younger) counterparts. Taken together, these data confirm that in relative terms, the faster/fitter players perform less RSS than the slower/less fi t players[ 31 ] and that repeated-sprint activity is more likely affected by game technical/tactical demands rather than by physical fitness itself [ 31 ] . In support of this, we also observed in the present study an increased occurrence of RSS in players presenting impairments in physical capacities (e. g., +20 % of RSS despite a substantial 2 % decrease in MSS for midfielders). Because of their reduced locomotor speeds, these players probably had to use a greater proportion of their maximal sprinting capacity to match the running demands of their teammates (which translated into a greater number of individual ‘sprints’ as defined in the present study) ... It is however worth noting that, although poor physical fitness might not directly limit match running performance (as discussed above), it may increase relative match running demands [ 31 ] . This can affect decision making, passing ability [ 36 ] or fatigue development during the end of a game. ... To summarize, the present data shows for the first time that the changes in RSS occurrence are independent of those in physical capacities, and that playing positions can affect these relationships. ... To conclude, with data limited to 1-Hz GPS analyses, the present results show that substantial improvements in both maximal sprinting and aerobic speeds can be beneficial to (absolute) high-intensity match running performance. However, changes in match running performance did not necessarily match those in physical capacities, i. e., the magnitude of the changes in match running activity was likely lower than that of physical capacities. Additionally, players displaying impairments in their physical capacities managed to maintain or even increase their high-intensity match running activities, and the changes in match running activity in relation to those in physical capacities were position-dependent. These results confirm that, at least for some positions, physical fitness might not directly limit high- intensity match running performance. Game tactical and strategic requirements can affect on-field players’ activity patterns independently (at least partially) of players’ physical capacities [ 7 , 28 , 31 , 33 ] . These results also emphasize our lack of understanding of how “maximal physical fitness performance” influences on-field running performance, and off er a cautionary tale of viewing the physical fitness – match running performance relationship in soccer in a simplistic manner [ 28 ] . Further study should now examine the optimal position-specific training strategies and determine at which extent improvements in physical capacities are still beneficial for match running performance [ 5 ] and, in turn, overall match performance and match outcomes [ 19 ] .

Things are “simply, more complex”. And I will try to explain one more factor why I think they are even MORE complex. 

This study reported that players who showed decreases in MSS/MAS (physical capacities) were able to maintain HRSS/RSS (even improve amount RSS, which is based on MSS) and the authors hypothesized that those players had to increase their work rate during games to match those of their teammates. I wonder were these players more ‘fatigue’ after the game, more sore, demanding more easy training in practices, missed more practices, had more minor injuries?

This brings me to one concept that is along the lines with Stephen Covey’s Production and Capacity to Produce:

To be effective, one must find the proper balance between actually producing and improving one's capability to produce. Covey illustrates this point with the fable of the goose and the golden egg. In the fable, a poor farmer's goose began laying a solid gold egg every day, and the farmer soon became rich. He also became greedy and figured that the goose must have many golden eggs within her. In order to obtain all of the eggs immediately, he killed the goose. Upon cutting it open he discovered that it was not full of golden eggs. The lesson is that if one attempts to maximize immediate production with no regard to the production capability, the capability will be lost. Effectiveness is a function of both production and the capacity to produce. Downloaded from HERE

Even if we forget about the flaws of most of the studies (velocity-based time motion, cross-study design, reporting mean values, etc) can we conclude that something is insignificant and not worth training for if there is no statistical significance to the game performance and the final outcome? 

In the mentioned study by DiSalvo et al. they showed that higher ranked teams perform less HIA than lower ranked teams. In the study by Carling et al. they showed that RSS does not occur so much in a game and they concluded “that the low frequency of repeated high-intensity bouts observed in the present team suggests that this specific fitness component (RSA) might not play as crucial a role in elite match performance as commonly believed “. In the study by Buchheit et al. authors showed that the players that showed significant decrease in MSS or MAS were able to maintain HRSS and RSS activities in the game.

All those data suggest that RSA is over-rated.

Let’s pretend for a minute that if the future studies show that most physical qualities have low influence on physical game performance and that physical game performance have low influence on final game/season outcome? Would we then conclude that physical preparation training is insignificant for the soccer? Be it RSA, MAS, MSS, COD and training aimed at improving them?

I think we are missing one crucial aspect here. We are focused on production, while really forgetting about capacity of production. We want to kill the goose and take the golden eggs.

One thing that studies report (or not even report) and we don’t actually pay attention to are subject drop-outs. Well, in sport studies there are a lot of drop-outs and I would really love to see meta-analysis study of drop-outs. Most of the drop-outs were because of illness or injury (or club transfer). I would be more than interested in characteristic (both physical and game performance ) of those drop-outs.

Another thing I would love to see in the (future) studies is how these drop-outs (and injuries or just unavailability) of the players influences the season outcomes (make sure to check John Orchard article in Br J Sports Med 2009;43:963-965; full text available HERE, along with this ARTICLE)

My point here i, that we are forgetting player availability/durability during the long season and grueling sessions.

Even if improving physical preparedness (which one?) doesn’t improve game performance and final outcome is not related to game performance, what it might improve is player availability/durability and that might affect the season outcome to the higher degree than being able to improve RSS in the game. Yet, I need a proof for this. Anyway, I warned about “productivity~capacity of production” complementary pair.

Preparing for a single game is pretty easy, but preparing for 10 months long season with 1-3 games played per week, with regular practices and travel is way different story. Having a high work capacity is of utmost importance. The work capacity is usually defined by VO₂max level or any other aerobic ability. Although might be related, work capacity is way more  - it is the ability to perform and recover from frequent specific work/training/playing. Smart practices and hard recovery is very important. In my mind work capacity is capacity of production, and great players are those with stable high level of performance over a long period of time. Even if their VO₂max is low. I think there are huge genetic influences on work capacity, besides training. Without expanding this discussion to talent~practice complementary pair (make sure to check What Makes Champions? in Br J Sports Med. 2012 Jun;46(8):555-61 HERE; along with this ARTICLE that concluded: “Psychology plays an important role in training, competition, tolerance of pain and motivation. However, the role of genetic variation in determining psychological state and responses remains poorly understood; only recently have specific genes been implicated in motivational behaviour and maintenance of exercise. Thyroid hormone receptors exist within the brain and influence both neurogenesis and behaviour. With the current state of knowledge, the field of genetic influences on sports performance remains in its infancy, despite over a decade of research.”)  I might say that you could have the greatest engine in the world, but if you have lousy breaks and chassis you cannot do much with such an engine. Some players are just prone to injuries and some are very robust. How can we influence this with training is beyond me. And, no I don’t think it has to do with the newest super-functional, vibrational, unstable corrective exercise. This rather has to do with individualizing training loads and implementing smart player rotation and recovery strategies.

My final point is that we are forgetting capacity of production (player availability/durability) and more studies need to take this into equation.

The thing I also noticed is that there is a fine line between de-training and under-recovering (over-training) during the in-season. The common pattern is that players start to feel tired after the games. The coach thinks they might be training too much, and that wise strategy would be to decrease training load. They feel even more tired. He decrease load even more in hope they will re-fresh. They feel even more tired. This is the thing that were confusing me over time, a lot. Still is.

This might be related to finding by Buchheit et al. that even the guys that showed decrement in MAS/MSS were able to maintain RHSS and RSS, but that might make them work harder (that’s why we need time-motion analysis based on relative speeds/abilities). You decrease load, they de-train even more and the game (even if they don’t show lowered HIA/RSS – they might even increase due the bad tactics and technique due decrease practice  time and getting out of the groove) makes them more tired. Then the coach decide that they are de-training and he increases the load. Guess what? They are even more tired and sore. Their work capacity was lowered and the new workloads take time to get used to. I’ve noticed this situation numerous times and solving it is not easy. It reminds me about the “sharpening the saw” principle by Stephen Covey. 

Stephen Covey tells the story of a man who was walking through a forest when he came across a frustrated lumberjack. The lumberjack was trying to cut down a tree with and was swearing and cursing as he laboured in vain. “What’s the problem?”  The man asked. “My saw’s blunt and won’t cut the tree properly.”  The lumberjack responded. “Why don’t you just sharpen it?” “Because then I would have to stop sawing.”  Said the lumberjack. “But if you sharpened your saw, you could cut more efficiently and effectively than before.” “But I don’t have time to stop!” The lumberjack retorted, getting more frustrated. The man shook his head and kept on walking, leaving the lumberjack to his pointless frustration. Downloaded from HERE

The problem might have been arisen because the coach wanted to peak for the long season, or because he was unable to continue sharpening the saw and individualizing workloads. Or maybe all of this is psychological and related to the grinding the season and routine trainings and training sessions/locations. This is still beyond me. 

Anyway, I am getting outside of the scope of this article. I want to finish and pack for the vacation. I am going to leave you with more complex graph I am working on and that touches on most of the things we were discussing here. Please note that this is work in progress.

 

Finally, this series are over and I can go with clear and calm mind to vacation. I hope you have enjoyed and learned something along the way.  Watch the big picture and continue sharpening the saw! 

Heading to Zakynthos!!!

RSA is overrated? Part 3

RSA is overrated?

Part 3

The study by Carling et al. “is the first to investigate in detail the characteristics of repeated high-intensity movement activity patterns in professional soccer match-play and demands specific to positional role” (p. 332). 

I am posting the abstract here, while I am pretty sure the full paper can be downloaded HERE. 

Carling C, Le Gall F, Dupont G. Analysis of repeated high-intensity running performance in professional soccer. J Sports Sci. 2012;30(4):325-36. The aims of this study were twofold: (1) to characterize repeated high-intensity movement activity profiles of a professional soccer team in official match-play; and (2) to inform and verify the construct validity of tests commonly used to determine repeated-sprint ability in soccer by investigating the relationship between the results from a test of repeated-sprint ability and repeated high-intensity performance in competition. High-intensity running performance (movement at velocities >19.8 km · h(-1) for a minimum of 1 s duration) was measured in 20 players using computerized time-motion analysis. Performance in 80 French League 1 matches was analysed. In addition, 12 of the 20 players performed a repeated-sprint test on a non-motorized treadmill consisting of six consecutive 6 s sprints separated by 20 s passive recovery intervals. In all players, most consecutive high-intensity actions in competition were performed after recovery durations ≥61 s, recovery activity separating these efforts was generally active in nature with the major part of this spent walking, and players performed 1.1 ± 1.1 repeated high-intensity bouts (a minimum of three consecutive high-intensity bouts with a mean recovery time ≤20 s separating efforts) per game. Players reporting lowest performance decrements in the repeated-sprint ability test performed more high-intensity actions interspersed by short recovery times (≤20 s, P < 0.01 and ≤30 s, P < 0.05) compared with those with higher decrements. Across positional roles, central-midfielders performed more high-intensity actions separated by short recovery times (≤20 s) and spent a larger proportion of time running at higher intensities during recovery periods, while fullbacks performed the most repeated high-intensity bouts (statistical differences across positional roles from P < 0.05 to P < 0.001). These findings have implications for repeated high-intensity testing and physical conditioning regimens.

As the abstract says, the aim of this study is two-fold: (1) to characterize repeated high-intensity movement activity profiles of a professional soccer team in official match-play; and (2) to inform and verify the construct validity of tests commonly used to determine repeated-sprint ability in soccer by investigating the relationship between the results from a test of repeated-sprint ability and repeated high-intensity performance in competition. 

Without going too much in the study detail (you can download it for free), what the authors tried to do is to get some insights in the frequency of both HIA and RSS during the game. Again, I am not going into details and positional difference. PLEASE NOTE THAT I WILL MOSTLY DO COPY-PASTE OF KEY SENTENCES AND PARAGRAPHS FROM THIS STUDY AND FINISH WITH MY CONCLUSIONS            AND OPINIONS.  

They used AMISCO system and defined HIA and RSS the way I defined them in the part 1 of this article. The authors then proceeded to find out distribution and quality of recovery between HIA (zones: >61sec, 31-60sec, <30sec, <20sec), maximum number of HIA during the 1 min, 3 min and 5 min window in the game, along with finding RSS patterns.

What they found is that the most commonly observed recovery duration between consecutive high-intensity actions was >61 s (67.0+9.6% of the total number of actions) with the average being 139 seconds. The analysis of activity patterns in between consecutive high-intensity actions showed that players across all positional roles spent the major part of recovery in walking and jogging activities. 

The highest number of high-intensity actions recorded in any single 1 min (n = 5) and 5 min (n = 11) period was observed in a fullback, and in a 3 min period (n = 7) jointly in a fullback and a central-midfielder.

Across all players, an average of 1.1+1.1 exercise bouts that met the criteria for repeated high-intensity activity (RSS) were performed per player per match with a statistical difference observed between positional roles.

The maximum number of repeated high-intensity bouts observed in any one match was six (in a wide midfielder) and the peak number of individual high intensity actions reported within any one single bout of repeated high-intensity activity was seven (in a centre-forward). The following picture  presents a graphical representation containing quantitative and qualitative information on this intense bout of activity. The overall duration of this bout was 111.0 s, equating to one high-intensity action every 15.9 s. Maximum and minimum recovery times between individual high-intensity actions within this bout were 9.5 s and 40.0 s, respectively. The mean duration and length of these high-intensity actions was 3.1+0.8 s (range 2.1–4.7 s) and 18.4+4.8 m (range 12.1–27.4 m), respectively. The mean speed of actions was 25.0+-1.9 km /h, with a peak speed of 28.2 km/h observed in the final effort of the bout. Of the recovery activity between efforts, 69.1% was spent in walking, 22.3% in jogging, and 10.8% in running activities respectively.

Taken from Carling C, Le Gall F, Dupont G. Analysis of repeated high-intensity running performance in professional soccer. J Sports Sci. 2012;30(4):325-36.

No significant decrements in the mean and maximum velocity of individual high-intensity actions performed during repeated high-intensity bouts were observed irrespective of the number of consecutive efforts (3, 4, 5, or 6) performed in each bout. 

When it comes to laboratory repeated-sprint ability, the study showed that the players ranked highest in the four scores of non-motorized treadmill test (mean velocity, highest mean velocity, peak velocity, performance decrement) generally did not display better performance in any of the match activity parameters. In contrast, a higher frequency of high-intensity actions with recovery times <20 s and <30 s was observed in players assigned to the group reporting the lowest percent performance decrement. Finally, no significant correlations were observed between any of the scores obtained in the repeated sprint ability test and measures of match-play performance.

In the discussion part of the article authors made couple of very important statements. 

The majority of consecutive high-intensity actions (67.0%) observed in the present players were performed after a recovery period >61 s. Although approximately one-fifth of consecutive high-intensity actions performed were interspersed by short recovery durations (<30 s), the present results nevertheless suggest that these players had sufficient time to completely recover ‘‘physiologically’’ from the majority of high intensity actions. A 120 s recovery period between short bouts of high-intensity activity has been shown not to lead to a decrement in running performance. even when 15 sprints were performed in succession (Balsom, Seger, Sjodin, & Ekblom, 1992). In addition, the present players performed an average of 1.1 repeated high-intensity bouts per match, with these comprising only three consecutive high-intensity actions. This result is substantially lower than the 4.8 repeated sprint bouts per match observed in international women’s soccer (Gabbett & Mulvey,2008). This discrepancy may be explained by differences in respective methods employed to collect movement data as manual coding techniques are known to lead to overestimations in high intensity running performance. These discrepancies in definitions across studies suggest a need for consensus to ensure standardization in the classification of movement thresholds (according to speed and duration) for time–motion analyses of professional soccer match-play.

Again, this is one of the limitations of this study and all studies based on velocity-based time-motion analysis as stated earlier since they underestimate high-power movement patterns. Hopefully, we will soon see more and more studies based on combination of acceleration/power and velocity. 

One of the most important conclusions of this study is that the low frequency of repeated high-intensity bouts observed in the present team suggests that this specific fitness component (RSA) might not play as crucial a role in elite match performance as commonly believed. Alternatively, the prescription of supplementary specific conditioning programmes to improve performance in the present group of elit soccer players could be warranted. Analysis of the maximum and mean running velocity of the individual efforts performed in repeated high-intensity bouts showed in general that  players were able to maintain performance even when six high-intensity actions were performed  successively with <20 s rest between runs. Analysis of data on mean and maximum velocity of consecutive high-intensity actions demonstrated no significant changes between the first and final effort across repeated high-intensity bouts. Overall, the present results suggest that the players studied were able to reproduce performance when called upon to perform sporadic but extreme  sequences of high-intensity running in match-play.

In the repeated-sprint ability treadmill test, players who reported the lowest percent performance decrement reported a greater frequency of high-intensity actions interspersed with recovery times<20 s and <30 s in duration. This result suggests that those with a greater resistance to fatigue in a treadmill test of repeated-sprint ability are able to perform a greater frequency of high-intensity actions with short rest intervals in competition. In contrast, no association was observed between test scores and the percent of the overall distance run that was covered in high intensity exercise or the frequency of high-intensity actions and recovery time between efforts. On the whole, these results might suggest a lack of empirical support for the construct validity of the present and similar tests of repeated-sprint ability as predictors of high-intensity match performance in professional soccer. 

In summary, this study has provided an insight into repeated high-intensity activity profiles and the extreme demands of match-play in professional soccer. Results from this study may also cast doubt on the relative importance of repeated high-intensity activity and therefore the need for conditioning programmes in an attempt to improve the general and/or position-specific ability of professional soccer players to perform repeated high intensity work.

MY OPINIONS

I am more than thankful to the authors of this study since it is the FIRST study to report this kind of data. I also hope that they will not mind me doing a lot of COPY-PASTE activity. 

As I have already covered in earlier installments and I will repeat one more time, the main limitation of these kinds of studies are velocity-based time-motion analysis. Thus the conclusions should be taken with grain of salt until we get more data based on power and acceleration as well. For more info on this please check THIS and THIS  post.

Another limitation of this study is the reporting of mean values, without any insights how the data changes over the season or over the duration of the game. Even the authors acknowledged this limitation – “However, the possible occurrence of fatigue patterns in repeated high-intensity performance as matches progressed (e.g. towards the end of games) was not examined here and warrants inclusion in future research.” (page 333).  They could also have reported how the data correlates with the success of the team, besides doing the analysis of the HIA in possession of the ball (attacking) or without-possession of the ball (defending). Having some analysis of time-in-play vs. total time might also give some data, but I doubt. 

One interesting finding is that players with lowest decrement score (better RSA – at least this indicator, see the problems with it in Troubles with RSA) performed higher frequency of HIA with <20sec and <30sec recovery time. But, still we are dealing with mean data. The study might include  correlation of more physical qualities (MAS, Vmax, Agility, etc.) with game performance, along with analyzing game performance across the short game periods to see any “fatigue” patterns. 

To conclude, even if velocity-based time-motion analysis is valid we might miss data with reporting only mean (average) values. For example, what if the guys with better MAS showed less decrement in HIA performance across the game, especially in the last 15-20minutes of the game? What if the teams that are ranked highest perform lower amount of HIA (as it is showed in the research by Di Salvo et al.), but show higher HIA activity during certain parts of the game, or show less decrement?  This is the problem with mean data as I have warned before. What we need are distributions of the data during the game, the season, etc and the correlations of those with physical qualities and overall performance of the team. Probably the conclusion would be along the lines of di Salvo et al. that overall technical and tactical effectiveness of the team rather than high levels of physical performance per se are more important in determining success in soccer, yet they would be more informative than basic mean values. 

Although I would love to see definitive answer whether RST (repeat sprint training) is overrated, with the studies we have up till now, even if it they pointing to the yes answer, I am not confident in giving definitive conclusion, because we still lack a bunch of data. One of the most important data we miss, besides all of those I mentioned are LONGITUDINAL CHANGES .  These studies should aim to answer the following type of questions:

• If the better teams show less HIA than worse teams, will decreasing HIA improve the team performance and standing and what is the influence of tactical/strategical training on HIA during the game?

• Will changes in training programs (especially in-season) yield changes in physical qualities and will those qualities change game performance (HIA, RSS) and thus game outcomes and team standings?

This kind of questions and studies will yield more data about the CAUSALITY. For example, even if this study showed that players with lower decrement score performed more HIA in the game, that doesn’t show causality and it doesn’t mean that if you improve your decrement score you will improve HIA in the game (and it is even questionable will this make your team better). As Mendez-Villanueva and Martin Buchheit concluded this is “simply, more complex” (Eur J Appl Physiol. 2011 Sep;111(9):2387-9.) (I will come back to this letter to editor).  

Unfortunately, things are not so linear or mechanic as we would love them to be, or as some portrait them to be. Hell, maybe having high MAS and/or improving it may yield no effects to your running (HIA) in the game, but might give you better work capacity to survive long in-season and training sessions (as we know playing one game is easy – the trick is having the similar performance over the long season), making you injury-proof and at high level of playing which in the end might result in better team performance. We are forgetting about injuries and excessive need to perform crazy good year round and survive the training loads by only concentrating on the single match data. An article by John Orchard is fantastic read in this regard (click HERE). The question is: are we seeing the forest for the trees (we need to see both btw) – do we really know what KPIs (key performance indicators) are important for long term success?

Anyway, I wanted to thank Dave Tenney on heads up for Carling et al. paper along for the article by John Orchard on injuries. Also, I want to thank Arthur Smith for his prompt responses in my research papers queries. Thank you bro! 

And if you think I am done, you are wrong. We still need to cover the newest research by Martin Buchheit (hopefully he will find time to do the interview as well), because as far as I know it is the only one study using longitudinal design  showing how the improvement of physical qualities affect game performance (HIA, RSS, etc). I advise you to check these two posters before I review the study (click HERE for and HERE). I will also cover some ideas for the training, but that wouldn’t be extensive at all since I covered some of my thought in Troubles with RSA and I promised Dan Baker to finish one article for JASC. Besides, I want to talk about power testing/assessment – I don’t want to spend time on Repeat Slow Ability as Carl Valle would say :)

Stay tuned… the rant ain’t over :)