Brain stimulation: does it enhance sports performance?

jkma.org

Brain stimulation has been introduced more than 100 years ago initially in animal studies and later in clinical studies involving humans. This method was initially designed to help patients with brain injuries but it is now being used in other areas too (for example in exercise physiology research & in skill acquisition studies).

What is brain stimulation?

Brain stimulation uses constant, low current delivered to the brain area of interest via surface electrodes. Research in healthy participants has shown that brain stimulation can improve cognitive performance on a variety of tasks depending on the area of stimulation.

Potential applications in sports

Based on the current evidence it seems that brain stimulation can be used to enhance exercise training-induced benefits and maximize sports performance.

Indeed, studies have shown that skill acquisition rate may improve with brain stimulation and this might have implications for training. If the players/athletes learn better and faster when brain stimulation is being used this will result in improved performance in the long term. Reis et al (2009) had their participants to perform a simple motor task on the computer while receiving transcranial direct current stimulation over the primary motor cortex (experimental condition) or without it. Measurements were performed before the experiment at 5 days of training and at 3 months post training. The results showed better performance for the experimental trial, even at 3 months post-training, compared to the control condition. 

Other studies have shown that time to fatigue and response time is improved immediately after stimulation and for the following 20-60 min. If this is true in real life situation, players/athletes might feel less tired towards the end of the game if they receive brain stimulation. Brain stimulation might also help the players/athletes to feel less tired the days between matches. However, it must be noted that this is only speculation and there is no scientific evidence in favor of this hypothesis.

Possible limitations

Studies with brain stimulation have been contacted in non-experts and we don’t know what would be the benefits in elite athletes.

Results so far are on simple motor tasks and we don’t know the response with more complex tasks as is the scenario in sports.

Health risks

As experts state some health risks may arise when brain stimulation is used outside safety parameters.

For further reading

Cogiamanian et al (2007). Improved isometric force endurance after transcranial direct current stimulation over the human motor cortical areas. Eur J Neurosci 26:242-249.

Jang et al (2009). The effect of transcranial direct current stimulation on the cortical activation by motor task in the human brain: an fMRI study. Neurosci  Lett 460:117-120.

Reis et al (2009). Noninvasive cortical stimulation enhances motor skill acquisition over multiple days through an effect on consolidation. PNAS 106:1590-1595.

Is altitude training appropriate for football players? New evidence

usatoday.com

A nice study was published about two weeks ago by McLean and colleagues from Australia on 30 elite Australian Football players. Twenty one of them completed 19 days of living and training at moderate altitude (around 2130 m) whereas the remaining 9 served as the control group (sea level training). Time-trial running performance in 2000m and hemoglobin mass were assessed before, immediately after the intervention as well as 4 weeks after returning from altitude in both groups.

Main findings

• Running performance improved in both conditions. However, the improvement in 2000 m performance was 1.5% greater after altitude training compared with sea level.
• This beneficial effect was maintained after 4 weeks of altitude training cessation.
• Hbmass increased by 2.8% with altitude training but returned to baseline values at 4 weeks after returning to sea level.

Conclusion & comments

As the authors suggest the maintenance of  running performance improvement at 4 weeks after returning from altitude suggests that altitude training may be beneficial to performance in team-sport athletes. It is worth noting, however, that no testing was conducted in the control group at that time. Hence, we don't know if the performance maintenace at 4 weeks postdescent was due to altitude training per se.

Finally, whether this benefit translates into improved match running performance in football (soccer) remains to be proven.

Source

McLean, Buttifant, Gore, White, Liess and Kemp (2013). Physiological and performance responses to a preseason altitude-training in elite team-sport athletes. Int J Sports Physiol Perform 8:391-399.

Going from good to great: lessons from business

by Jim Collins

Recently, I read the “Good to Great” by Jim Collins. Jim Collins is a former faculty member at the Stanford University Graduate School of Business, who conducted the “Good to Great” study. In his study, he identified the companies that progressed from good to great and sustained those results for 15 years. He then compared these companies with a control group of companies which did not make the transition or were unable to sustain the great results for so long. Many of the findings of this study apply and/or may be useful in sports (team building, sports science and medical departments building etc.). For those who are interested in such issues, I have summarized the findings below:

Leadership style: These are the characteristics of the leaders (CEO) of the companies that made the leap from good to great:

• They are results oriented while at the same time they are modest and shy.
• They are determined to do whatever neede to achive the best results. On the other hand they are quit, calm, and friendly with the colleagues.
• They set high goals and work hard and smart to achieve them. Ambitions are for the company not for themselves.
• They look "in the mirror not out of the window". When something goes wrong they look in the mirror, when things go well they give credit to the team members.
• They have the ability to "get the right people on the bus, the right peple in the right place and the wrong people off the bus".  Importantly, they get self-disciplines people on the bus. If you lead such a team, you spend little time trying to motivate people and hence focus on more important issues.
• Leaders face the brutal facts, don’t cover them and never lose faith that they will succeed in the end.
• They carefully plan their actions and insire others to do the same by asking simple questions:

                      -What is my passion? Let’s go for it!

                      -How can I make the difference?

• Leaders preserve their personal and team's core values while they are ready to modify strategies to adapt to a changing environment.

Source: Jim Collins. Good to Great. HarperCollins Publishers Inc, New York, 2001

Effect of electrokinetically modified water on exercise-induced muscle damage and recovery



leanbulk.com



An interesting study was published on June 15th in the Journal of Applied Physiology by PA Borsa, KL Kaiser and JS Martin from the University of Florida. The aim was to examine the effect of ingesting electrokinetically modified water on muscle damage and post exercise recovery. To my knowledge this is a novel approach and findings need to be confirmed in future investigations and in particular in athletes.

What they did?

Non-trained males were assigned to an experimental or a control (placebo) group. The experimental group consumed electrokinetically modified water daily for 23 days. On day 19 participants performed an exercise protocol to induce muscle damage. Various measurements were taken for the next 96 hours.

Main findings

1. Muscle pain was significantly greater post exercise in the control compared with the experimental group.
2. Creatine Kinase and C-reactive protein levels were higher in the control group.

Conclusion

Oral consumption of electrokinetically modified water for 23 days reduced exercise-induced muscle damage and this seemed to be due to suppressed inflammation.

Source

Borsa et al. (2013). Oral consumption of electrokinetically modified water attenuates muscle damage and improves postexercise recovery. Journal of Applied Physiology 114(12): 1736-1742

Protein ingestion immediately before sleep improves post-exercise recovery

The role of protein ingestion before sleep on metabolism was the aim of an interesting study published by the group of Professor Luc Van Loon, Maastricht University, in Medicine & Science in Sports & Exercise last year (Res et al., 2012).

What they did?

Sixteen healthy men volunteers performed resistance exercise in the evening (20:00 h) and ingested 20 g of protein and 60 g of carbohydrate immediately after exercise (21:00 h). Thirty minutes before sleep (23:30 h) participants received either placebo or 40 g of proteins. Protein digestion and absorption, whole-body protein balance and muscle protein balance were assessed for the sleep period.

Main findings & practical applications

• Dietary protein ingested before sleep was normally digested and absorbed
• This raised plasma amino acid levels and stimulated muscle protein synthesis

In conclusion, dietary protein ingested immediately before sleep seems to increase plasma amino acid availability and stimulate muscle protein synthesis.

Source

Res et al. (2012). Protein ingestion before sleep improves postexercise overnight recovery. Med Sci Sports Exerc 44(8):1560-1569

Under performance: update and management plan

chriskresser.com

Sports scientists often use the term overtraining to describe the condition the player feels tired and is simply underperforming. I am not quite sure if the term “overtraining” is the most appropriate one because of two reasons: a) under performance might not be due to overtraining but rather due to imbalance between training and recovery, and b) coaches do not feel comfortable with the term since it implies that they simply have designed a bad training. For the purpose of this post I will use both terms when necessary focusing on the end result which is under performance.  I will also try to summarize the scientific evidence behind the phenomenon and outline a brief plan of actions based on the literature and on my experience.

What is the cause of under performance?

As you understand under performance might be the result of a number of factors like a) poor training, b) inadequate recovery, c) imbalance between training and recovery, d) psychological factors that create excessive stress, and e) poor tapering. In some cases, under performance is due to inappropriate training that leads to overtraining. To implement and effective plan of actions one needs to understand the possible mechanism(s) behind overtraining.  

• Excessive muscle stress due to training and inappropriate recovery will result in increased inflammation.
• Elevated inflammatory markers and molecules will negatively affect central nervous system (CNS) function causing lower appetite and sleep disturbances
• Excessive inflammation and stimulation of the CNS will also stimulate the hypothalamus-pituitary-adrenal axis resulting in a number of imbalances, like elevated catabolism, suppressed immune function etc.

Figure 1: Summary of the mechanisms of overtraining (Source: Hug et al. (2003). Training modalities: over-reaching and over-training in athletes, including a study of the role of hormones. Best Pract Res Clin Endocrinol Metab 17(2):191-209).  



Can we predict overtraining and under performance?

There is no definite answer. To be able to identify under performance in advance one must follow the same player for long period. Below I have summarized a plan of actions based on my experience:

• Assess players’ performance with valid and reliable tests. Although there are excellent tests proposed in the literature some of them might not be practical and this is a concern. Ideally, a submaximal test which could be part of the warm-up is the best option.
• You might have more than one performance tests. Whatever the decision, tests should be practical, and no time consuming.
• Repeat those tests as many times as possible. The more data you have the better. There are tests you can do once a week depending on your sport science team man power.
• Follow a more holistic approach. Gather as many information as practically possible. For instance, you need to have information from:
•  health screening,
• functional movement screening
• quality of sleep and general well-being
• injury and illness reports
• training logs

• Create the pattern (yearly, weekly) for each individual. All players are not the same. Some players show a decline in performance during the winter months (December-January) some other are pacing themselves and don’t show this pattern.
• Look for the cause when test values deviate substantially from the expected ones. The expected values can be the mean for the group +/- 1-2 standard deviations (SD) or, ideally, the mean +/- 1-2 SDs for the individual based on repeated measures.

How can you assist as a sport scientist to avoid overtraining and under performance

This is an outline of the plan:

• Monitor training. This is very important to the whole process. Training monitoring might be done with heart rate monitors or GPS or, when not available, with the RPE scales. RPE scales are good tools and should be used more frequently in training because they are fast, practical and inexpensive. To improve reliability you must familiarize your players before the actual use. Whatever tool you use, ensure that a) you collect enough information, b) understand them before you communicate with coaches. In some cases you might need a season of data collection before you can make safe conclusions.
• Implement frequent performance tests. As said before this is of paramount importance because performance is the key parameter in sports.
• Monitor as many other parameters as possible. Again, serum iron levels and hormones concentration might help. Don’t forget that measures should be as non-invasive as possible. Hormones and immune system indices in the saliva (testosterone, cortisol, IgA) are promising tools.
• Estimate the player’s dietary intake. Sometimes inadequate caloric intake or low micronutrient’s intake may lead to chronic fatigue when not corrected.
• Implement appropriate recovery strategy. For instance, cold water bathing, deep water running during the recovery days might be useful depending on the player.
• Ensure adequate sleep of good quality. Sleep is of paramount importance and should be evaluated at frequent intervals either with small, easy to wear devices that are in the market or with questionnaires.
• Eliminate or manage other stress factors (family, personal matters etc). In this case the contribution of a sports psychologist may help.

For further reading

Coutts et al. (2007). Monitoring of overreaching in rugby players. Eur J Appl Physiol 99: 2313-324.

Meeusen et al. (2013). Prevention, diagnosis and treatment of the overtraining syndrome: joint consensus statement of the European College of Sport Science and American College of Sports Medicine. Med Sci Sports Exerc 45(1): 186-205.

Nedelec et al. (2013). Recovery in soccer. Part I-Recovery strategies. Sports Med 43: 9-22

Papacosta and Nassis (2011). Saliva as a tool for monitoring steroid, peptide and immune markers in sport and exercise science. J Sci Med Sport 14(5): 424-434.



In this blog
http://georgenassis.blogspot.com/2013/04/does-sleep-affect-performance.html

What supplements are used to improve performance?

Below you can access a recent study on the use of dietary supplements in athletes. Although there is a need for surveys in more populations the results of this study might be useful to other groups too. To download free please use the link below http://jssm.org/vol12/n1/26/v12n1-26pdf.pdf

Ifigenia Giannopoulou, Kostantinos Noutsos, Nikolaos Apostolidis, Ioannis Bayios and George P.

Nassis.  Performance Level Affects the Dietary Supplement Intake of Both Individual

and Team Sports Athletes. Journal of Sports Science and Medicine (2013) 12, 190-196

Goal setting & team building: learn from Dr Stephen Covey

Football is a team sport. This means that success is determined by the optimal combination of physical, tactical and technical skills of each one of the players. To train a team effectively, a coach must transform and adjust individual's characteristics to fit the team’s goals and objectives. He must also effectively communicate the goals to players and staff members and get them engaged. At the end, he needs to develop a strategy to translate these goals into top performance and visible results.

You know, better than anyone else, that there might be players with no commitment to team’s goals. Or they might have different goals to the team's goals. How can you, as a coach, get them involved and contribute to the common goal? Goal setting and team building are not easy tasks!

Dr. Stephen Covey, one of 25 most influential American’s and an internationally respected leader has done excellent work on goal setting and team building. Below you can see the link for a video prepared by Dr Covey which I think also applies to football. Hope it helps you and gives you some ideas for your every day work in the field. 

Enjoy it! 

https://www.youtube.com/watch?v=wPwrfa7oY-M

How can sports science assist high level players: some recent examples

source: uefa.com

Buchheit M, Racinais S, Bilsborough JC, Bourdon PC, Voss SC, Hocking J, Cordy J, Mendez-Villanueva A, Coutts AJ.

Monitoring fitness, fatigue and running performance during a pre-season training camp in elite football players.

J Sci Med Sport 2013 Jan 16 [Epub ahead of print]

ASPIRE, Academy for Sports Excellence, Doha, Qatar

ASPETAR, Qatar Orthopaedic & Sports Medicine Hospital, Doha, Qatar

Carton FC, Australia

Aim: To examine the usefulness of selected physiological and perceptual measures to monitor fitness, fatigue and running performance during a pre-season, 2-week training camp in eighteen professional Australian Rules Football players. Methods: Training load, perceived ratings of wellness (e.g. fatigue, sleep quality) and salivary cortisol were collected daily. Submaximal exercise heart rate (HRex) and a vagal-related heart rate variability index (LnSD1) were also collected at the start of each training session. Yo-Yo Intermittent Recovery level 2 test (Yo-YoIR2, assessed pre-, mid- and post-camp, temperate conditions) and high-speed running distance during standardized drills (HSR, >14.4kmh(-1), 4 times throughout, outdoor) were used as performance measures. Results: There were significant (P<0.001 for all) day-to-day variations in training load, wellness measures (6-18%), HRex (3.3%), LnSD1 (19.0%), but not cortisol (20.0%, P=0.60). While the overall wellness did not change substantially throughout the camp, HRex decreased and cortisol, Yo-YoIR2 performance and HSR increased. Day-to-day ΔHRex, ΔLnSD1 and all wellness measures were related to Δtraining load. There was however no clear relationship between Δcortisol and Δtraining load. ΔYo-YoIR2 was correlated with ΔHRex (r=0.88 (0.84; 0.92)), ΔLnSD1 (r=0.78 (0.67; 0.89)), Δwellness (r=0.58 (0.41; 0.75), but not Δcortisol. ΔHSR was correlated with ΔHRex (r=-0.27 (-0.48; -0.06)) and Δwellness (r=0.65 (0.49; 0.81)), but neither with ΔLnSD1 nor Δcortisol.

Conclusions

Training load, HRex and wellness measures are the best simple measures for monitoring training responses to an intensified training camp; cortisol post-exercise and LnSD1 did not show practical efficacy.

 

 

Poppendieck W, Faude O, Wegmann M, Meyer T. Cooling and Performance Recovery of Trained Athletes - a Meta-Analytical Review. Int J Sports Physiol Perform 8: 227-242, 2013

Saarland University, Institute of Sports and Preventive Medicine, Germany

Fraunhofer Institute for Biomedical Engineering, Germany

Aim: Cooling after exercise has been investigated as a method to improve recovery during intensive training or competition periods. As many existing studies include untrained subjects, the transfer of those results to trained athletes is questionable. Methods: Therefore, we conducted a literature search and located 21 peer-reviewed randomized controlled trials addressing the effects of cooling on performance recovery in trained athletes. For all studies, the effect of cooling on performance was determined and effect sizes (Hedges' g) were calculated. Results: Regarding performance measurement, the largest average effect size was found for sprint performance (2.6%, g=0.69), while for endurance parameters (2.6%, g=0.19), jump (3.0%, g=0.15) and strength (1.8%, g=0.10), effect sizes were smaller. The effects were most pronounced when performance was evaluated 96 h after exercise (4.3%, g=1.03). Regarding the exercise used to induce fatigue, effects after endurance training (2.4%, g=0.35) were larger than after strength-based exercise (2.4%, g=0.11). Cold water immersion (2.9%, g=0.34) and cryogenic chambers (3.8%, g=0.25) seem to be more beneficial with respect to performance than cooling packs (-1.4%, g= -0.07). For cold water application, whole-body immersion (5.1%, g=0.62) was significantly more effective than immersing only the legs or arms (1.1%, g=0.10).

Conclusions

The average effects of cooling on recovery of trained athletes were rather small (2.4%, g=0.28). However, under appropriate conditions (whole-body cooling, recovery of sprint exercise), post-exercise cooling seems to have positive effects which are large enough to be relevant for competitive athletes.

Elias GP, Wyckelsma VL, Varley MC, McKenna MJ, Aughey RJ. Effectiveness of Water Immersion on Post-Match Recovery in Elite Professional Footballers. Int J Sports Physiol Perform 8: 243-253, 2013

Institute of Sport, Exercise and Active Living, School of Sport and Exercise Science, Victoria University, Australia

Aim: The efficacy of a single exposure to 14-min of contrast water therapy (CWT) or cold water immersion (COLD) on recovery post-match in elite professional footballers was investigated. Methods: Twenty four elite footballers participated in a match followed by one of 3 recovery interventions. Recovery was monitored for 48-hrs post-match. Repeat-sprint ability (6 x 20-m), static and countermovement jump performance, perceived soreness and fatigue were measured pre, immediately following, 24 and 48 h after the match. Soreness and fatigue were also measured 1 h post-match. Post-match, players were randomly assigned to complete passive recovery (PAS) (n=8), COLD (n=8) or CWT (n=8). Results: Immediately post-match, all groups exhibited similar psychometric and performance decrements, which persisted for 48 h only in the PAS group. Repeat-sprinting performance remained slower at 24 and 48 h for PAS (3.9% and 2.0%) and CWT (1.6% and 0.9%) but was restored by COLD (0.2% and 0.0%). Soreness after 48 h was most effectively attenuated by COLD (ES 0.59±0.10) but remained elevated for CWT (ES 2.39±0.29) and PAS (ES 4.01±0.97). Similarly, COLD more successfully reduced fatigue after 48 h (ES 1.02±0.72) compared to CWT (ES 1.22±0.38) and PAS (ES 1.91±0.67). Declines in static and countermovement jump were ameliorated best by COLD.

Conclusions

An elite professional football match results in prolonged physical and psychometric deficits for 48 h. Cold water immersion was more successful at restoring physical performance and psychometric measures than contrast water therapy, with complete passive recovery being the poorest.

Tonnessen E, Hem E, Leirstein S, Haugen T, Seiler S. Maximal aerobic power characteristics of male professional soccer players, 1989-2012. Int J Sports Physiol Perform 8: 323-329, 2013

Aim:The purpose of this investigation was to quantify maximal aerobic power (VO_2max) in soccer as a function of performance level, position, age, and time of season. In addition, the authors examined the evolution of VO_2max among professional players over a 23-y period. Methods: 1545 male soccer players were tested for VO_2max at the Norwegian Olympic Training Center between 1989 and 2012. Results: No differences in VO_2max were observed among national-team players, 1st- and 2nd-division players, and juniors. Midfielders had higher VO_2max than defenders, forwards, and goalkeepers (P < .05). Players <18 y of age had ~3% higher VO_2max than 23- to 26-y-old players (P = .016). The players had 1.6% and 2.1% lower VO_2max during off-season than preseason (P = .046) and in season (P = .021), respectively. Relative to body mass, VO2max among the professional players in this study has not improved over time. Professional players tested during 2006–2012 actually had 3.2% lower VO_2max than those tested from 2000 to 2006 (P = .001).

Conclusions

This study provides effect-magnitude estimates for the influence of performance level, player position, age, and season time on VO_2max in men’s elite soccer. The findings from a robust data set indicate that VO_2max values ~62–64 mL · kg^–1 · min^–1 fulfill the demands for aerobic capacity in men’s professional soccer and that VO_2max is not a clearly distinguishing variable separating players of different standards.

Ingebrigtsen J, Shalfawi SA, Tønnessen E, Krustrup P, Holtermann A. Performance effects of 6 weeks of anaerobic production training in junior elite soccer players. J Strength Cond Res 2013 April 1 [Epub ahead of print]

Department of Sport and Centre for Practical Knowledge, University of Nordland, Bodø, Norway

Aim: This study investigates the performance effects of a six week biweekly anaerobic speed endurance production training among junior elite soccer players. Methods: Sixteen junior (age 16.9 ±0.6 years) elite soccer players were tested in Yo-Yo Intermittent Recovery test level 2 (IR2), 10 m and 35 m sprints, 7x35 m Repeated Sprint Ability (RSA) tests, Counter Movement Jump (CMJ) and Squat Jump (SJ) tests, and randomly assigned into either a control group performing their normal training schedule, which included four weekly soccer training sessions of ∼90 min, or a training group performing anaerobic speed endurance production training twice weekly for six weeks in addition to their normal weekly schedule . Results: We found that the intervention group significantly improved (p<0.05) their performance in the Yo-Yo IR2 (63± 74 m) and 10 m sprint time (-0.06± 0.06 s). No significant performance changes were found in the control group. Between-group pre- to post-test differences were found for 10 m sprint times (p<0.05). No significant changes were observed in 35 m sprint times, RSA, or jump performances.

Conclusions

The present results indicate that short-term anaerobic production training is effective for improving acceleration and intermittent exercise performance among well-trained junior elite players.

Keiner Keiner M, Sander A, Wirth K, Schmidtbleicher D. Long term strength training effects on change-of-direction sprint performance. J Strength Cond Res 2013 April 12 [Epub ahead of print]

Institute of Sport Science, Johann Wolfgang Goethe-University, Germany

German Luge and Bobsled Federation, Germany

Aim: The requirement profiles of sports such as soccer, football, tennis and rugby demonstrate the importance of strength and speed-strength abilities, in addition to other conditional characteristics. During a game, these athletes complete a large number of strength and speed-strength actions. In addition to the linear sprint, athletes perform sprints while changing direction (COD). Therefore, this study aims to clarify the extent to which there is a strength-training intervention effect on COD. Further, this investigation analyzes possible correlations between the One Repetition Maximum / Body Mass (SREL) in the front and back squat and COD. Methods: The subjects (n = 112) were at pretest between 13 and 18 years old and were divided into two groups with four subgroups (A = under 19-years-old, B = under 17-years-old, C = under 15-years-old). For approximately 2 years, one group (CG) only participated in routine soccer training, and the other group (STG) participated in an additional strength-training program with the routine soccer training. Additionally, the performances in COD of 34 professional soccer player of the 1st and 2nd division in Germany were measured as a standard of high-level COD. For the analysis of the performance development within a group and pairwise comparisons between two groups, an analysis of variance with repeated measures was calculated with the factors group and time. Relationships between COD and SREL were calculated for the normal distributed data using a plurality of bivariate correlations by Pearson. Our data show that additional strength training over a period of 2 years significantly affects the performance in COD. The STG in all subcohorts reached significantly (p < 0.05) faster times in COD than CG. The STG amounted up to 5% to nearly 10% better improvements in the 10 meter sprint times compared to the CG. Furthermore, our data show significant (p < 0.05) moderate to high correlations (r = -0.388 to -0.697) between SREL and COD.

Conclusion

Data show that long-term strength training improves the performance of the COD.

Abstracts modified from pubmed

Does sleep affect performance?

http://www.bdlive.co.za/life/health/2012/11/29/neuroscience-turn-down-the-light-to-brighten-up-your-mood

This is a straight forward question you might hear from your players. How can you screen athletes for sleep quality? What should I do if I identify player(s) with sleep problems?

Recently, I had the opportunity to listen to an excellent talk by Dr Charles Samuels, Medical Director-Centre for Sleep & Human Performance-Calgary, who is a leading scientist and practitioner in the field. As Dr Samuels concluded, he is not yet “fully convinced” about the role of sleep in sports performance. More research is needed to understand the relationship between sleep quantity and quality and human performance.

Here I am posting the link of a similar presentation by Dr Samuels so you can learn more

http://canadiansportforlife.ca/sites/default/files/resources/sleep_Plenaryfinal.pdf.

During this Powerpoint presentation you will learn about:

• The key sleep factors and their association with recovery & regeneration
• The implementation of sleep education within the Long-term Athlete (Player) Development Model
• How to implement an educational program, monitor and evaluate sleep behavior and decide strategies when sleep problems are identified in a player

Recent studies with practical applications to elite football





 

Testing visual elements at Panathinaikos FC Performance Lab (March 2008)


 

Soichi (2013). Peripheral visual perception during exercise: why we cannot see. Exercise & Sport Sciences Reviews 41(2): 87-92

Faculty of Sports and Health Science, Fukuoka University,  Japan

Peripheral visual perception may be relevant to performance in sports. Peripheral visual perception seems to be impaired during strenuous exercise. The hypothesis proposed is that a decrease in cerebral oxygenation is associated with impairment in peripheral visual perception during strenuous exercise. Recent behavioral and physiological data are presented to support the hypothesis.

Free access
http://journals.lww.com/acsm-essr/Fulltext/2013/04000/Peripheral_Visual_Perception_During_Exercise___Why.4.aspx

Lehr et al (2013). Field-expedient screening and injury risk algorithm categories as predictors of noncontact lower extremity injury. Scand J Med Sci Sports March 20, [Epub ahead of print]

Department of Physical Therapy, Lebanon Valley College, Pennsylvania, USA.

In athletics, efficient screening tools are sought to curb the rising number of noncontact injuries and associated health care costs. The authors hypothesized that an injury prediction algorithm that incorporates movement screening performance, demographic information, and injury history can accurately categorize risk of noncontact lower extremity (LE) injury. One hundred eighty-three collegiate athletes were screened during the preseason. The test scores and demographic information were entered into an injury prediction algorithm that weighted the evidence-based risk factors. Athletes were then prospectively followed for noncontact LE injury. Subsequent analysis collapsed the groupings into two risk categories: Low (normal and slight) and High (moderate and substantial). Using these groups and noncontact LE injuries, relative risk (RR), sensitivity, specificity, and likelihood ratios were calculated. Forty-two subjects sustained a noncontact LE injury over the course of the study. Athletes identified as High Risk (n = 63) were at a greater risk of noncontact LE injury (27/63) during the season [RR: 3.4 95% confidence interval 2.0 to 6.0].

Conclusion
These results suggest that an injury prediction algorithm composed of performance on efficient, low-cost, field-ready tests can help identify individuals at elevated risk of noncontact LE injury.

Meister et al. (2013). Indicators for high physical strain and overload in elite football players. Scand J Med Sci Sports March 20, [Epub ahead of print]

Institute of Sports and Preventive Medicine (FIFA, Medical Centre of Excellence), Saarland University, Saarbrücken, Germany Institute of Sports Medicine, University Paderborn, Paderborn, GermanyUniversity of Basel, Institute of Exercise and Health Sciences, Basel, Switzerland.

Laboratory, psychological and performance parameters as possible indicators of physical strain and overload during highly demanding competition phases were evaluated in elite male football players. In two studies with the same objective, periods of high (HE: >270 min during 3 weeks before testing) and low (LE: <270 min) match exposure were compared over the course of an entire season. In study 1 (n=88 players of the first and second German leagues; age: 25.6±4.3 years; body mass index (BMI): 23.2±1.0 kg/m(2) ), blood count, CK, urea, uric acid, CRP and ferritin were determined. In study 2, 19 players of the third German league and the highest under-19 league (age: 19.7±2.8 years; BMI: 22.8±1.7 kg/m(2) ) were screened for individual vertical jump height, maximal velocity and by the Recovery-Stress-Questionnaire for Athletes (REST-Q Sport). The mean differences in exposure times were 180 min (study 1: quartiles: 105, 270 min) and 247 min (study 2: 180, 347 min), respectively. Significant differences were found neither in blood parameters (study 1; P>0.36) nor in physiological testing results or in REST-Q scores (study 2; P>0.20).

Conclusion
A 3-week period of high match exposure in elite football players does not affect laboratory, psychometric and performance parameters.

Casals and Martinez (2013). Modelling player performance in basketball through mixed models. Int J Perfom Anal Sport, 13(1): 64-82

University of Wales, Cardiff

The aims of this study were to identify variables which may potentially influence player performance, and to implement a statistical model to study their relative contribution in order to explain two outcomes: points and win score. We used all the possible variables affecting player performance creating a comprehensive database from two sources of statistical information about the NBA 2007 regular season: www.basketball-reference.com and www.nbastuffer.com. The data employed for the analysis were composed of 2187 cases (27 players * 81 games), having followed a filtering process. We dealt with a balanced study design with repeated measurements given that each player was observed the same number of games, and therefore the player was considered as a random effect. We carried out mixed models to quantify the variability in points and win score among players. Minutes played, the usage percentage and the difference of quality between teams were the main factors for variations in points made and win score. The interaction between player position and age was important in win score.

Conclusions
We encourage managers and coaches of sports teams to choose appropriate methods according to their aims. Future research should take into consideration the use of models with random effects on players' characteristics.

Fradua et al (2013). Designing small-sided games for training tactical aspects in soccer: extrapolating pitch sizes from full-size professional matches. J Sport Sci 31(6): 573-581.

University of Granada, Physical Education and Sport , Granada , Spain.

The aims of this study were to examine the 1) individual playing area, 2) length and width of the rectangle encompassing the individual playing area and 3) distance between the goalkeepers and their nearest team-mates during professional soccer matches and compare these to previously reported pitch sizes for small-sided games (SSGs). Data were collected from four Spanish La Liga matches of the 2002-03 season, and notated post-event using the Amisco® system. The pitch sizes obtained from real matches were smaller and different from those used previously for SSGs. In addition, the current pitch sizes show significant (P < 0.001) effect of ball location in all variables examined. For example, overall individual playing area (F [5, 2562] = 19.99, P < 0.001, η(2 )= 0.04) varied significantly across six different zones of the pitch. Based on these empirical results, pitch sizes with individual playing areas ranging from 65 m(2) to 110 m(2) and length to width ratio of 1:1 and 1:1.3 are generally recommended for training tactical aspects according to different phases of play.

Conclusion
It is possible to design SSGs with a more valid representation of the tactical conditions experienced in full-size matches and their use may improve the training effect of tactical aspects of match performance in soccer.

Eynon et al. (2013). ACTN3 R577X polymorphism and team-sport performance: a study involving three European cohorts. J Sci Med Sport March 20 [Epub ahead of print]

School of Sport and Exercise Sciences, Victoria University, Australia; Institute of Sport, Exercise and Active Living (ISEAL), Victoria University, Australia.


We compared the genotype and allele frequencies of the ACTN3 R577X (rs1815739) polymorphisms between team-sport athletes (n=205), endurance athletes (n=305), sprint/power athletes (n=378), and non-athletic controls (n=568) from Poland, Russia and Spain; all participants were unrelated European men. Genomic DNA was extracted from either buccal epithelium or peripheral blood using a standard protocol. Genotyping was performed using several methods, and the results were replicated following recent recommendations for genotype-phenotype association studies. Genotype distributions of all control and athletic groups met Hardy-Weinberg equilibrium (all p>0.05). Team-sport athletes were less likely to have the 577RR genotype compared to the 577XX genotype than sprint/power athletes [odds ratio: 0.58, 95% confidence interval: 0.34-0.39, p=0.045]. However, the ACTN3 R577X polymorphism was not associated with team-sports athletic status, compared to endurance athletes and non-athletic controls. Furthermore, no association was observed for any of the genotypes with respect to the level of competition (elite vs. national level).

Conclusion
The ACTN3 R577X polymorphism was not associated with team-sport athletic status, compared to endurance athletes and non-athletic controls, and the observation that the 577RR genotype is overrepresented in power/sprint athletes compared with team-sport athletes needs to be confirmed in future studies.

Sparks and Close (2013). Validity of a portable urine refractometer: the effects of sample freezing. J Sports Sci 31(7): 745-749.

Department of Sport and Physical Activity , Edge Hill University, UK.

The use of portable urine osmometers is widespread, but no studies have assessed the validity of this measurement technique. Furthermore, it is unclear what effect freezing has on osmolality. One-hundred participants of mean (±SD) age 25.1 ± 7.6 years, height 1.77 ± 0.1 m and weight 77.1 ± 10.8 kg provided single urine samples that were analysed using freeze point depression (FPD) and refractometry (RI). Samples were then frozen at -80°C (n = 81) and thawed prior to re-analysis. Differences between methods and freezing were determined using Wilcoxon's signed rank test. Relationships between measurements were assessed using intraclass correlation coefficients (ICC) and typical error of estimate (TE). Osmolality was lower (P = 0.001) using RI (634.2 ± 339.8 mOsm · kgH2O(-1)) compared with FPD (656.7 ± 334.1 mOsm · kgH2O(-1)) but the TE was trivial (0.17). Freezing significantly reduced mean osmolality using FPD (656.7 ± 341.1 to 606.5 ± 333.4 mOsm · kgH2O(-1); P < 0.001), but samples were still highly related following freezing (ICC, r = 0.979, P < 0.001, CI = 0.993-0.997; TE = 0.15; and r=0.995, P < 0.001, CI = 0.967-0.986; TE = 0.07 for RI and FPD respectively). Despite mean differences between methods and as a result of freezing, such differences are physiologically trivial.

Conclusion
The use of RI appears to be a valid measurement tool to determine urine osmolality.


Source: Pubmed