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Evaluation of key-strokes on the basketball game analysis software

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As the development of match analysis software has enhanced performance in sports, the evaluation of the applications is currently relevant in the field of sport and ergonomics. In order to utilize those applications or systems in real-time situations, however, limits of data collection, data analysis, time and validity of the data must be addressed in match analysis applications. Modern technologies, on the other hand, tend to overcome the limitations of match analysis applications by the construction or internal procedure (Choi, 2008; Choi, Hughes, & O'Donoghue, 2007). The main aim of this study, therefore, is to compare the key strokes of basketball match analysis software between the England Women Basketball DIV 2 2005-2006 and 2006-2007. The game data were collected in real-time by CyberSport for Basketball™ 4.0 and then determined by Mann-Whitney U test, independent T-test and descriptive statistics. As results, there were no significant differences found on analysis time ( 85.3±4.7 minutes in 2005-2006, 83.6±4.6 minutes in 2006-2007), but there were significant differences on the total strokes by key presses/mouse clicks ( 1198.3±143.3 in 2005-2006, 1316.0±164.9 in 2006-2007, p<0.05) and the strokes per analysis minute ( 14.1±1.7/min in 2005-2006, 15.8±1.8/min in 2006-2007, p<0.05) between the seasons. Consequently, the ascend numbers of strokes and descend minutes of analysis time have found in the comparison despite of no difference between analysis time statistically that the intensity of analysis depended on game process would have caused the results of the study. Therefore, the application on the match analysis software has to be concerned for all operators who collate performance data or match data using such software. For further research, the development of game intensity index is required in order to evaluate the software evenly

Abstract

As the development of match analysis software has enhanced performance in sports, the evaluation of the applications is currently relevant in the field of sport and ergonomics. In order to utilize those applications or systems in real-time situations, however, limits of data collection, data analysis, time and validity of the data must be addressed in match analysis applications. Modern technologies, on the other hand, tend to overcome the limitations of match analysis applications by the construction or internal procedure (Choi, 2008; Choi, Hughes, & O'Donoghue, 2007). The main aim of this study, therefore, is to compare the key strokes of basketball match analysis software between the England Women Basketball DIV 2 2005-2006 and 2006-2007. The game data were collected in real-time by CyberSport for Basketball™ 4.0 and then determined by Mann-Whitney U test, independent T-test and descriptive statistics. As results, there were no significant differences found on analysis time ( 85.3±4.7 minutes in 2005-2006, 83.6±4.6 minutes in 2006-2007), but there were significant differences on the total strokes by key presses/mouse clicks ( 1198.3±143.3 in 2005-2006, 1316.0±164.9 in 2006-2007, p<0.05) and the strokes per analysis minute ( 14.1±1.7/min in 2005-2006, 15.8±1.8/min in 2006-2007, p<0.05) between the seasons. Consequently, the ascend numbers of strokes and descend minutes of analysis time have found in the comparison despite of no difference between analysis time statistically that the intensity of analysis depended on game process would have caused the results of the study. Therefore, the application on the match analysis software has to be concerned for all operators who collate performance data or match data using such software. For further research, the development of game intensity index is required in order to evaluate the software evenly

참고문헌 (13)

  1. Choi, H. J., "Ergonomics Issues and Human-Computer interaction in sport: A case study evaluation of a match analysis system for basketball", 6th International Symposium Computer Science in Sport, pp.31~35 (2007), Liverpool John Moores University Press
  2. Choi, H. J., "The identification of optimal sets of performance indicators for real-time analysis using Principle Components Analysis in sports, In World Congress of Performance Analysis of Sport VIII", pp.295~301 (2008), Otto von Guericke University Press
  3. Choi, H. J., "The analysing system of broadcasting in real time, In Performance Analysis of Sport VI", pp.245~252 (2004), Centre for Performance Analysis
  4. Choi, H. J., "A comparison of whole match and individual set data in order to identify valid performance indicators for real-time feedback in men's single tennis matches, In Science and racket sports IV", pp.227~231 (2008), Routledge
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  6. George, K., "Ergonomics and sport and leisure revisited. Ergonomics", Ergonomics, 48, pp.1333~ (2005)
  7. Hughes, M., "Using notational analysis to create a more exciting scoring system for squash, In International conference of Sport Leisure and Ergonomics", pp.243~247 (1995), E. & F.N. Spon
  8. Hughes, M., "The use of performance indicators in performance analysis", Journal of Sports Sciences, 20, pp.739~754 (2002)
  9. Reilly, T., "Ergonomic aspects of sport and recreation", Canadian Journal of Applied Sport Sciences, 6, pp.1~10 (1981)
  10. Reilly, T., "The effect of partial sleep deprivation on weight-lifting performance", Ergonomics, 37(1), pp.107~116 (1991)
  11. Sommerville, I., "Software Engineering" (2001), Pearson Education Limited
  12. Vanezis, A., "A biomechanical analysis of good and poor performers of the vertical jump", Ergonomics, 48, pp.1594~1603 (2005)
  13. Williams, J., "The development of a real-time data capture application for rugby union", World Congress of Performance Analysis of Sport VI, pp.253~261 (2004), Centre for Performance Analysis

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