A novel performance evaluation technique based on integrated weighting approach: A case study in the field of sport management

It is a fact accepted by everybody that football is the most popular sport around the world. The result of a derby match may be very important for millions of people. Even the time seems to stop on a match day for so many people. Show and entertainment are the most important aspects of football. If soccer players have a high performance, a match may provide pleasure and excitement to audiences. Briefly, the performance and quality of soccer players are the key factors, which draw audiences. Goalkeepers are also one of the important components of football like other players playing different positions such as strikers, mid-fielders, and defenders. Moreover, a goalkeeper can affect the result of a match positively or negatively. Therefore, with the help of a mathematical approach as the methodological framework, it can be seen that the examination of the performance of goalkeepers can be beneficial for decision-makers performing in the fields of sport and the future studies. The current paper proposes an improved integrated multi-criteria decision-making approach to evaluate the selection of goalkeepers; and this model can be applied for goalkeeper's performance analysis. The proposed model combines the weights of criteria calculated with the help of both the CRITIC and the PSI techniques by applying the weight aggregation operator. It also ranks the decision alternatives by implementing the WASPAS technique based on the final criteria weights obtained by using the weight aggregation operator. In addition, a comprehensive sensitivity analysis consisting of three stages was performed to verify the validation of the suggested hybrid model. It has been observed that All has remained the best option for all scenarios. As a result, the results of the sensitivity analysis prove that the proposed hybrid MCDM technique is a very useful, strong and applicable approach. Also, the results obtained by applying the proposed model are accurate, realistic, and reasonable according to the results of the validation test. (C) 2021 by the authors; licensee Growing Science, Canada.