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Energy Cost of Running Under Hypogravity in Well-Trained Runners and Triathletes: A Biomechanical Perspective

References Barnes, K. R., & Janecke, J. N. (2017). Physiological and Biomechanical Responses of Highly Trained Distance Runners to Lower-Body Positive Pressure Treadmill Running. Sports Med Open, 3 (1), 41. doi:10.1186/s40798-017-0108-x Barnes, K. R., & Kilding, A. E. (2015). Running economy: measurement, norms, and determining factors. Sports Med Open, 1 (1), 8. doi:10.1186/s40798-015-0007-y Beneke, R., Beyer, T., Jachner, C., Erasmus, J., & Hütler, M. (2004). Energetics of karate kumite. European Journal of Applied Physiology, 92 (4), 518

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Kinematic quantification of straight-punch techniques using the preferred and non-preferred fist in taekwon-do

.16926/par.2017.05.11. 16. Rahnama N., Lees A., Bambaecichi E. (2005) A comparison of muscle strength and flexibility between the preferred and non-preferred leg in English soccer players. Ergonomies , 48(11-14): 1568-1575. 17. Romanenko V., Podrigalo L., Iermakov S., Rovnaya O., Tolstoplet E., Tropin Y., Goloha V. (2018) Functional state of martial arts athletes during implementation process of controlled activity–comparative analysis. Phys. Activ. Rev. , 6: 87-93. DOI: 10.16926/par.2018.06.12. 18. Sachlikidis A., Salter C. (2007) A biomechanical

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The impact of fatigue on agility and responsiveness in boxing

and its relationship to sprint speed and change of direction speed. J. Sci. Med. Sport, 9: 342-349. DOI: 10.1016/j.jsams.2006.05.019. 16. Sienkiewicz-Dianzenza E., Tomaszewski P., Stupnicki R. (2005) „Performance index” and application to the assessment of multiple bouts of leg exercise. Phys. Educ. Sport., 49: 52-55. 17. Smith M.S., Dyson R.J., Hale T., Janaway L. (2000) Development of aboxing dynamometer and its punch force discrimination efficacy. J. Sport. Sci., 18: 445-450. DOI: 10.1080/02640410050074377. 18. Stupnicki R., Norkowski H

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Temporal effects of final action on the performance of the Portuguese men’s volleyball teams

. Quant. Anal. Sport, 6. DOI: 10.2202/1559-0410.1216. 4. Batterham A.M., Hopkins W.G. (2006) Making Meaningful Inferences about Magnitudes. Int. J. Sports Physiol. Perform., 1: 50–57. DOI: 10.1123/ijspp.1.1.50. 5. Castro J., Souza A., Mesquita I. (2011) Attack Efficacy in Volleyball: Elite Male Teams. Percept. Mot. Skills, 113: 395-408. DOI: 10.2466/05.25.PMS.113.5.395-408. 6. Cohen J. (1988) Statistical power analysis for the behavioral sciences, 2 nd Edition. 7. Costa G., Castro H., Evangelista B., Malheiros L., Greco P., Ugrinowitsch H

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Forecasting Soccer Outcome Using Cost-Sensitive Models Oriented to Investment Opportunities

. P., Jarmoszko, A. T., & Labedz Jr, C. S. (2016). Predicting wins and spread in the Premier League using a sentiment analysis of twitter. Decision Support Systems , 88 (C), 76-84. doi: 10.1016/j.dss.2016.05.010 Scibilia, B. (2012). How Could You Benefit from a Box-Cox Transformation?. [The Minitab Blog.] Retrieved September 10 2018 from http://blog.minitab.com/blog/applying-statistics-in-quality-projects/how-could-you-benefit-from-a-box-cox-transformation . Sharpe, W. (1994). The Sharpe Ratio. The Journal Of Portfolio Management , 21 (1), 49

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Intra-seasonal Variability of Ball Speed and Coordination of Two Team-Handball Throwing Techniques in Elite Male Adolescent Players.

:10.1016/j.humov.2011.05.005 Wagner, H., Pfusterschmied, J., von Duvillard, S. P., & Müller, E. (2012). Skill-dependent proximal-to-distal sequence in team-handball throwing. Journal of Sports Sciences , 30 (1), 21–9. doi:10.1080/02640414.2011.617773 Wu, G., van der Helm, F. C. T., (DirkJan) Veeger, H. E. J., Makhsous, M., Van Roy, P., Anglin, C., … Buchholz, B. (2005). ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion—Part II: shoulder, elbow, wrist and hand. Journal of

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Using Several Types of Virtual Characters in Sports - a Literature Survey

environments. Computer & Graphics 37, 121-136. Argelaguet Sanz, F., Multon, F. & Lécuyer (2015). A methodology for introducing competitive anxiety and pressure in VR sports training. Frontiers in Robotics and AI 2:10. DOI: 10.3389/frobt.2015.00010 Bailenson, J.N., Blascovich, J., Beall, A.C. & Loomis, J.M. (2003). Interpersonal distance in immersive virtual environments. Personality and Social Psychology Bulletin, 29 (7), 819-833. DOI: 10.1177/0146167203029007002 Bandow, N., Emmermecher, P., Stucke, C., Masik, S. & Witte, K

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Linear and Nonlinear Prediction Models Show Comparable Precision for Maximal Mean Speed in a 4x1000 m Field Test

., Theakston, S. C., Owen, A. & Nevill, A. M. (2003). Characteristics Associated With 10-km Running Performance Among a Group of Highly Trained Male Endurance Runners Age 21-63 Years. Journal of Aging and Physical Activity, 11, 333-350. doi: 10.1123/japa.11.3.333 Breiman, L. (2001). Random forests. Machine learning, 45, 5-32. Darr, K. C, Bassett, D. R, Morgan, B. J., Thomas, D. P. (1988). Effects of age and training status on heart rate recovery after peak exercise. American Journal of Physiol, 254(2), H340-343. Deuster, P

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Lawful Solutions For Violation On Women In Sports

: Norská sportovní univerzita a Český olympijský výbor Oslo a Praha. ISBN 80-239-5723-6. 8. FASTING, K., 2013. Preventing sexual harassment in sport - a need for transforming coaching education? [online]. 2013 [2015-03-02]. Dostupné z: http://www.ews-online.org/files/doc/Conference-Paris/Fasting.pdf . 9. FASTING, K., C. BRACKENRIDGE and J. SUNDGOT-BORGEN, 2000. Females, Elite Sports and Sexual Harassment. The Norwegian Women Project . Oslo, Norwegian Olympic Committee. 10. FASTING, K., C.H. BRACKENRIDGE and J. SUNDGOT-BORGEN, 2004. Prevalence of

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Predicting Win-Loss outcomes in MLB regular season games – A comparative study using data mining methods

soccer result prediction. Paper presented at the Seventh International Conference on Intelligent Systems Design and Applications. Baumer, B., & Zimbalist, A. (2014). Quantifying Market Inefficiencies in the Baseball Players’ Market. Eastern Economic Journal, 40(4), 488-498. doi: 10.1057/eej.2013.43 Burges, C. J. C. (1998). A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery, 2(2), 121-167. doi: 10.1023/a:1009715923555 Chang, J., & Zenilman, J. (2013). A study of

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