Effect of Specific Table Tennis Trainingon the Selected Skill Performance variables of School Boys

10.26524/1433 ◽  
2014 ◽  
Vol 3 (3) ◽  
pp. 11-17
Author(s):  
M Srinivasan
Author(s):  
Mervat Ahed Deeb ◽  
Hashem Adnan Kilani

The purpose of the study was to detect the effect of a psychological program supported by Macromedia Flash technology on some of psychological conditioning skills and the level of skills performance for table tennis players. Seven subjects comprised of 5 male and 2 female players from the Jordan national team with age ranges 12-15 year of old were intentionally selected. Measurement of muscle relaxation, mental imagery, state of competition anxiety, self talk, and colored readiness concentration (in-house built) for table tennis players. Skill performance during the competition was also assessed using special forms. Experiment design involved one group with pre and post hoc test after 12 weeks of the program application, 4 sessions per week in a simulated competition circumstances. Results of none parametric statistics (Welcoxon) revealed that there was a significant effect of the program at post hoc test for all skills variables. It is imperative to provide an early psychological conditioning program for table tennis juniors’ players with practice sessions as it is important part of training regimen. In addition, it was suggested to use the Macromedia Flash technology for simulation enhancement of the real competition. 


Sports ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 168 ◽  
Author(s):  
Andrew W. Pichardo ◽  
Jon L. Oliver ◽  
Craig B. Harrison ◽  
Peter S. Maulder ◽  
Rhodri S. Lloyd ◽  
...  

This study aimed to examine the extent to which maturity offset, strength, and movement competency influences motor skill performance in adolescent boys. One hundred and eight secondary school boys completed anthropometric and physical testing on two non-consecutive days for the following variables: Maturity offset, isometric mid-thigh pull absolute (IMTPABS) and relative (IMTPREL) peak force, resistance training skills quotient, 10-, 20-, and 30-m sprint time, countermovement jump height, horizontal jump distance, anaerobic endurance performance, and seated medicine ball throw (SMBT). The IMTPREL displayed significant small to large correlations with all performance variables (r = 0.27–0.61), whereas maturity offset was significantly correlated with IMTPABS (r = 0.69), sprint (r = 0.29–0.33), jump (r = 0.23–0.34), and SMBT (r = 0.32). Absolute and relative strength were the strongest predictors of all performance variables and combined with maturity to explain 21%–76% of the variance. Low and average relative strength boys were nearly eight times (odds ratio: 7.80, confidence interval: 1.48–41.12, p < 0.05) and nearly four times (odds ratio: 3.86, confidence interval: 0.95–15.59, p < 0.05) more likely to be classified as lower competency compared to high relative strength boys. Relative strength has more influence on motor skill performance than maturity when compared with movement competency.


Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 769
Author(s):  
Kate S. Early ◽  
Nathan P. Lemoine ◽  
Annie Simoneaux ◽  
Shelly Mullenix ◽  
Jack Marucci ◽  
...  

This study aimed to describe the physical demands of American football players using novel performance analysis techniques. Heart rate (HR) and accelerometer-based activity levels were observed across two pre-season scrimmages in 23 Division I collegiate football players (age: 19 ± 1 y, height: 1.90 ± 0.06 m, weight: 116.2 ± 19.4 kg). Data were analyzed using a MATLAB program and inter-rater reproducibility assessed using inter-class correlations (ICC). Players were analyzed by side (offense/defense) and position (skill/non-skill). Performance variables assessed in bursts of activity included burst duration, HRmean and HRmax (bpm), and mean activity (vector magnitude units [vmu]). Exercise intensity was categorized as time spent in % HRmax in 5% increments. The burst duration (8.1±3.9 min, ICC = 0.72), HRmean (157 ± 12 bpm, ICC = 0.96) and mean activity (0.30 ± 0.05 vmu, ICC = 0.86) were reproducible. HRmean (p = 0.05) and HRmax (p = 0.001) were greater on defense. Offense spent more time at 65–70% HRmax (p = 0.01), 70–75% HRmax (p = 0.02) while defense spent more time 90–95% HRmax and ≥95% HRmax (p = 0.03). HRmean (p = 0.70) and HRpeak (p = 0.80) were not different between positions across both sides. Skilled players demonstrated greater mean activity (p = 0.02). The sport-specific analysis described HR and activity level in a reproducible manner. Automated methods of assessing HR may be useful in training and game time performance but ultimately provides support to coaching decision making.


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