Quantification of the degree of difficulty in making a save for a soccer goalkeeper

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  • Hirashima Yusuke
    Graduate School of Comprehensive Human Sciences, University of Tsukuba
  • Nakayama Masao
    Faculty of Health and Sports Sciences, University of Tsukuba
  • Naito Kiyoshi
    Graduate School of Comprehensive Human Sciences, University of Tsukuba
  • Asai Takeshi
    Faculty of Health and Sports Sciences, University of Tsukuba

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Other Title
  • サッカーにおけるゴールキーパーのシュートストップ難易度の定量化
  • サッカー ニ オケル ゴールキーパー ノ シュートストップ ナンイド ノ テイリョウカ

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  The purpose of this study was to clarify the principal factors related to shot situations that affect the outcome of goalkeeping saves in soccer and to build a regression formula that would predict the difficulty of saving a shot. The samples were 551 shots at goal in the 2010 FIFA World Cup in South Africa. The shots data were collected using game performance analysis. For statistical processing, the principal factors affecting the outcome of a save in soccer were revealed using logistic regression analysis. The principal factors that influenced the results of a save attempt were: the duration between initiation of the shot and when the ball reached the goal, the presence or absence of a defender in front of the shooter, the presence or absence of a defender located lateral or posterior to the shooter, the part of the body used to perform the shot, i.e. the head or the leg, the type of shot, i.e., a liner, a lob, or a grounder, the shot course in a mediolateral direction, the shot course in a vertical direction, the presence or absence of a change in the direction of the shot by other players, the shooter's position angle in relation to the goal line and the line from the goal post to the shooter, and the distance from the center of the goal to the ball when the ball reached the goal line. In addition, a regression formula was constructed to predict the difficulty of the save by combining the odds ratios of the main factors. It was verified that the difficulty in making a save could be accurately predicted using the regression formula (84.8%). As a future task, using our regression formula, it would be practically important to develop predictors for evaluating the ability of a goalkeeper.<br>

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