O. Ueberschär, D. Fleckenstein, F. Warschun, N. Walter, J. C. Wüstenfeld, B. Wolfarth and M. W. Hoppe
, D., Taylor, W. R., Singh, N. B., & Schega, L. (2014). Towards clinical application: repetitive sensor position re-calibration for improved reliability of gait parameters. Gait & posture, 39 (4), 1146-1148. doi:10.1016/j.gaitpost.2014.01.020
Hollander, K., Riebe, D., Campe, S., Braumann, K.-M., & Zech, A. (2014). Effects of footwear on treadmill running biomechanics in preadolescent children. Gait & posture, 40 (3), 381-385. doi:10.1016/j.gaitpost.2014.05.006
Karatsidis, A., Bellusci, G., Schepers, H. M., de Zee, M., Andersen, M. S., & Veltink, P. H
Javier Yanci, Asier Los Arcos, Daniel Castillo and Jesús Cámara
.3–0.5, moderate; < 0.5–0.7, large; < 0.7–0.9, very large; and < 0.9–1.0, almost perfect ( Hopkins et al., 2009 ). Data analysis was performed using the Statistical Package for Social Sciences (version 20.0 for Windows, SPSS™ Inc, Chicago, IL, USA) for Windows. Statistical significance was set at p < 0.05.
The results of the physical performance in sprint, CODA and HJ tests of the total sample, boys and girls are described in Table 2 . The CV of all the physical tests were between 1.9 and 4.9%. No significant differences ( p > 0.05, d < 0.10, trivial) were
Mean ± SDs for MV, MP, and RPE are presented in Figures 2 and 3 . There were no differences between RR6 and TS in MV ( Figure 2A; p > 0.05; d = 0.10 (-0.35, 0.56)), MP ( Figure 2B; p > 0.05; d = 0.19 (-0.27, 0.64)), MVD ( Figure 4 ; p > 0.05; d = 0.16 (-0.30, 0.62)), MPD ( p > 0.05; d = 0.22 (-0.24, 0.68)), MVM ( Figure 5 ; p > 0.05; d = 0.12 (0.34, 0.56)), or MPM ( p > 0.05; d = 0.09 (-0.36, 0.55)).
Means and standard deviations during rest redistribution sets (RR6) and traditional sets (TS) across 30 repetitions for: A) mean
Nikki Kolman, Barbara Huijgen, Tamara Kramer, Marije Elferink-Gemser and Chris Visscher
difference in the mean VA-index between the first and the second test-session. The non-bold dotted lines represent the 95% limits of agreement (± 1.96 × SD). ICC: intra-class correlation coefficient (model: one-way random); * p < .05.
Reliability outcomes of the Dutch Technical- Tactical Tennis Test (D4T) in youth tennis players (n=10
Mean ± SD
ICC 95% Cl
Absolute reliability 95% CI
-2.06 - 2
Jacek Wąsik, Tomasz Góra, Dorota Ortenburger and Gongbing Shan
sparring. Journal Combat Sports and Martial Arts , 5(1): 27-30. DOI: 10.5604/20815735.1127450
29. Wąsik, J., Shan, G. (2014). Factors influencing the effectiveness of axe kick in taekwon-do. Arch Budo ., 10(1): 29-36
30. Wąsik J. (2015) Kinetics of the knife-hand strike used in power breaking in ITF Taekwon-do. Phys. Activ. Rev ., 3: 37-43. DOI: 10.16926/par.2015.01.05.
31. Wąsik J., Ortenburger D., Gora T., Mosler D. (2018) The influence of effective distance on the impact of a punch-Preliminary Analysis. Phys. Activ. Rev ., 6: 81-86. DOI: 10
Olyvia Donti, Gregory C. Bogdanis, Maria Kritikou, Anastasia Donti and Kalliopi Theodorakou
execution score. Differences between gymnasts of a higher and lower performance level were determined using independent samples t-tests. Cohen (d) effect sizes were calculated and their magnitude was categorized as follows: trivial, <0.2; small, 0.2 to 0.5; small to moderate, 0.5 to 0.8, and large, >0.8 (Cohen, 1988). Multiple regression analysis was used to investigate which physical fitness variables contributed most significantly to the technical execution score in each group separately. Test–retest reliability for all the dependent variables measured in this
th June 2013 , Barcelona-Spain, pp. 175-176.
3. Davis P., Benson P.R., Pitty J.D., Connorton A.J., Waldock R. (2015) The activity profile of elite male amateur boxing. Int. J. Sports Physiol. Perform., 10: 53-57. DOI: 10.1123/ijspp.2013-0474.
4. Ghosh A.K., Goswami A., Ahuja A. (1995) Heart rate and blood lactate response in amateur competitive boxing. Indian J. Med. Res., 102: 179-183.
5. Ghosh A.K. (2010) Heart rate, oxygen consumption and blood lactate responses during specific training in amateur boxing. Int. J. App. Sports Sci., 22
Pedro Reche-Soto, Donaldo Cardona-Nieto, Arturo Diaz-Suarez, Alejandro Bastida-Castillo, Carlos Gomez-Carmona, Javier Garcia-Rubio and Jose Pino-Ortega
1 = 19.85 ± 4.43; SH3 = 17.41 ± 3.26; p < .001; d = ‐ 0.75) and MP (FH1 = 6646.05 ± 1005.23; FH3 = 6256.51 ± 823.34; p < .001; d = ‐0.47; SH1 = 6188.42 ± 954.32; SH3 = 5359.15 ± 838.76; p < .001; d = ‐0.98).
Player Load and Metabolic Power dynamics according to the 15‐min game period, playing position and match‐to‐match variability. FH1 Significant differences with first half 1 (p < .05), FH2 Significant differences with first half 2 (p < .05), FH3 Significant differences with first half 3 (p < .05), SH1 Significant differences with
Ricardo Lima, Ana Filipa Silva and Filipe Manuel Clemente
1. Afonso J., Esteves F., Araújo R., Thomas L., Mesquita I. (2012) Tactical determinants of setting zone in elite men’s Volleyball. J. Sports Sci. Med., 11: 64-70.
2. Alexandru S.D., Sabin S.I. (2015) Study on the Interpretation of the Results in a Volleyball Game by Using a Specific Program of Statistics. Procedia – Soc. Behav. Sci., 180: 1357–1363. DOI: 10.1016/j.sbspro.2015.02.277.
3. Araújo R.M., Castro J., Marcelino R., Mesquita I.R. (2010) Relationship between the Opponent Block and the Hitter in Elite Male Volleyball. J