Recomendação estratégica de apoio ao comércio de Trading Card Games (TCG) usando Python

Magic: the Gathering is one of the world's largest collectible card games with millions of players worldwide. Its cards have distinct market demands and can cost thousands of dollars. With the popularization of online games and their professionalization, the search for behavioral patterns driven by such games is becoming increasingly common. The sites of stores and card guides where the cards of the game Magic: the Gathering are obtained do not have a strategic recommendation among them and represent a demand among players and store owners. Thus, the proposal of this work deals with the development of a recommendation system, capable of classifying the cards considering the frequency of their successful appearances in tournaments, sorting them in a hash table, used to account for the ideal pairing between them. The strategic recommendation proposed to support trading card game commerce was developed using the Python programming language, facilitating an active and targeted search for exactly what the player needs, with a qualitative cost-benefit and good performance.