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| Abstract : Universiti Pendidikan Sultan Idris |
| The game of beach soccer at the elite level is characterised with a high tempo that leads to the scoring of many goals in a match. A draw cannot decide the outcome of a match, and thus, a winner is decided by a team that scores more goals than the opponent hence, investigating performance indicators (PIs) that could lead to a higher goal-scoring opportunity in this game is non-trivial in ensuring the success of a team during a match. In the present study, an analysis of performance indicators was carried out through which a total number of 16 relevant performance indicators were considered, and multiple linear regression (MLR) was used to extract the significant PI that could lead to chances of scoring goals. An Artificial Neural Network (ANN) was used to predict the opportunities for scoring goals based on the extracted PIs. The MLR was able to extract shot at back third, pass at front third, short inside box, turnover, tackling, as well as fouls committed as the most significant PI whilst a robust predictive model was obtained via the ANN with an R2 of 0.91 and a very low mean absolute error of 1.76 amongst the other model predictive evaluation parameters. It is postulated from the present study that the identified PIs are essential in increasing the chances of scoring goals in the elite Asian beach soccer competition. ? Springer Nature Singapore Pte Ltd. 2021. |
| References |
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