테니스 경기분석을 위한 주요 분석인자의 일관성 탐색
Identification of consistency on Key Performance Indicators for Tennis match analysis
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초록
본 연구는 테니스 경기 공식기록을 통하여 승패의 차이를 분석할 때 사용되는 분석인자들에 대한 일관성을 알아내고자 하였다. 특히, 본 연구에서는 하나의 대회가 아닌 10개의 테니스 대회에서 나타나는 ‘승자’와 ‘패자’간의 차이를 경기기록과 세트기록으로 구분하여 비교해보고, 이에 대한 차이를 논함으로써 분석인자의 탐색에 대한 일관성에 대해 살펴보고자 하였다. 본 연구를 위하여 2005년부터 2010년까지의 4대 그랜드슬램 테니스 대회의 자료(경기기록(n=687), 세트기록(n=391))가 대상이 되었으며, ‘승자’와 ‘패자’간 차이를 비교한 결과는 다음과 같다. 첫째, 대회별로 나누지 않고 전체자료를 대상으로 비교한 결과에서는 경기기록의 경우 11개의 분석인자에서 모두 통계적으로 유의한 차이를 나타낸 반면, 세트기록에서는 브레이크 포인트 승리율을 제외한 10개의 분석인자에서 통계적으로 유의한 차이를 나타냈다(p<.05). 둘째, 경기기록을 대회별로 살펴본 결과, 6개의 분석인자에서 공통적으로 통계적 차이(p<.05)를 보였다. 셋째, 세트기록을 대회별로 살펴본 결과, 3개의 분석인자에서 공통적으로 통계적 차이(p<.05)를 보였다. 따라서 각 대회의 특성과 선수의 경기력 차이와 같은 변인을 고려하지 않고 자료의 범위에 따라서 분석인자를 탐색할 때의 일관성이 나타났으며, 향후 실시간분석에 적용할 수 있을 것으로 사료된다.
Abstract
The purpose of this study was to compare the differences of identification of performance indicators which were distinguishing the winning and losing performances in Tennis Gland Slam competitions. Especially, the consistencies of identification on Performance Indicators through statistical comparisons using Wilcoxon Signed Ranks tests were considered. For this study, 687 matches and 391 sets were selected as subjects in 4 Grand Slam tennis competitions (from 2005 to 2010). Totally, 11 performance indicators were selected from the official stats of 4 Grand Slam tennis championships as independent variables for this study that they were % of successful serves, aces, double faults, unforced errors, % of successful 1st serve, % of successful 2nd serve, winners, received points, break points conversions, % of net approaches and total point obtained. As results of the study, there were 3 summarized findings as following below;Firstly, there were significant differences of all 11 performance indicators between winning and losing where the data were arranged as match results (p<.05). Likely, there were also significant differences of 10 performance indicators between winning and losing where the set data were used for comparisons (p<.05). Only 1 performance indicator was shown differently between match and set data that it was ‘Break point conversions’. Secondly, there were significant differences on 6 performance indicators distinguishing winning and losing where matches’ data were used in the comparisons of championships separately (p<.05). The performance indicators were % of successful 1st serve, % of successful 2nd serve, winners, received points, break points conversions and total point obtained. Thirdly, there were significant differences on only 3 performance indicators distinguishing winning and losing where sets’ data were used in the comparisons of championships separately (p<.05). The performance indicators were % of successful 1st serve, received points and total point obtained. Consequently, further researches are required that the development of the systematic structures of identification for KPI and real-time analysis systems as well.
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