Thursday, April 18, 2013

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


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.

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).

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.
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 (VO2max) in soccer as a function of performance level, position, age, and time of season. In addition, the authors examined the evolution of VO2max among professional players over a 23-y period. Methods: 1545 male soccer players were tested for VO2max at the Norwegian Olympic Training Center between 1989 and 2012. Results: No differences in VO2max were observed among national-team players, 1st- and 2nd-division players, and juniors. Midfielders had higher VO2max than defenders, forwards, and goalkeepers (P < .05). Players <18 y of age had ~3% higher VO2max than 23- to 26-y-old players (P = .016). The players had 1.6% and 2.1% lower VO2max 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 VO2max than those tested from 2000 to 2006 (P = .001).

This study provides effect-magnitude estimates for the influence of performance level, player position, age, and season time on VO2max in men’s elite soccer. The findings from a robust data set indicate that VO2max values ~62–64 mL · kg–1 · min–1 fulfill the demands for aerobic capacity in men’s professional soccer and that VO2max 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.

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.

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

Abstracts modified from pubmed

Monday, April 8, 2013

Does sleep affect performance?

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

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