PREDICTING THE RANKING OF POSITION-BASED BEST PLAYERS IN FOOTBALL COMPETITIONS IN INDONESIA USING SUPPORT VECTOR REGRESSION Muhammad Noorridho Ilmansyah & Dedy Dwi Prastyo
Institut Teknologi Sepuluh Nopember,
Abstract
The industrial era brings football into the modern industry, which happens globally, including in Indonesian football competitions. One component that must be improved in this business is league quality. If the quality of the league is good, then indirectly, the value of television broadcasting rights will increase, which indicates an increase in media exploration, and further, it can undoubtedly attract sponsors to become official partners in the league. The more and more significant sponsorship value indicates that the competition has bright prospects from the business side. The value of sponsorship can also make plots such as awarding. A good award is based on data and statistics relevant to the field^s situation. Therefore, an awarding assessment method is needed to look at the statistics of each player. Statistics can help us understand the game and how to judge the players^ performance properly. However, the use of statistics must also be contextual because the use of statistics without context will result in poor interpretation. Therefore, the awarding assessment that is carried out apart from statistics also uses a different assessment for players in each position because each player has a different task. This research employs Support Vector Regression, with benchmarks Ridge Regression method and Principal Component Regression, to predict which week the best players in each position will be known almost surely before the competition end.
Keywords: Please Just Try to SuFootball Industry, Ranking of each Position, Support Vector Regression, Ridge Regression, Principal Component Regressionbmit This Sample Abstract
