Estimate of prices of professional Iranian football players using neural networks

The purpose of conducting this study was to estimate pricesof Iranian professional football league players.

The research method was mixed exploratory designs, which is a combination of qualitative and quantitative methods. The statistical population of the research in the qualitative section included managers, club coaches and experts who were familiar with the field of buying and selling players, and fourteen of them were selected by snowball method until they reached saturation point. In the quantitative section, the statistical population included all the football players present in the Iranian Persian Gulf Football Professional League during 2016-2019. The research tool of qualitative method included in-depth interviews, the reliability of which was calculated 81% through re-test method. The data needed to analyze quantitative methods were also collected from valid sites and the Iranian Football League Organization. The model was also designed through radial neural networks using software R.

The study results of the qualitative section showed that the player's performance, personal characteristics and abilities, club characteristics and bubble-creating factors are effective on determining the price of football players. Also, in the quantitative section, a model with two hidden layers was designed, which had the least error rate in predicting the price of players.

In general, the design of this model will make the officials of buying and selling of football clubs aware so that they can attract talented and cost-effective players with the minimum cost and high level of reliability.