Comparison of Country-Based High And Low Market Valued Transfer Networks

Football is a “money game” and this feature of football is evident in the transfer markets. Network science, which has a wide range of applications from the brain to social networks, can also be applied to football transfer markets. In this manuscript, one million Euro has been taken as a threshold and the transfer market and 2019-2020 Winter transfer season of football was divided into two markets such as a low and high valued markets. After obtaining these two networks, their metrics and measures were calculated and compared. In addition, the article focused on “excess degree”, “assortativity” concepts of network science and investigated the differences between low and high-valued transfer markets in terms of these concepts. It was found that high market valued transfer network has a low assortativity coefficient (0.562), and low-valued transfer network has a high assortativity coefficient (0.836). This finding can be interpreted as the big transfer values, big money creates big differences in country’s transfer connections. The skewness of ingoing-outgoing degree differences distribution is much higher in the one with higher transfer values (0,962), than the one with lower transfer values (0,180). This situation can be attributed to larger deficits in the high-value market. Regarding total number of connections, self-loops and betweenness. In both networks, Brazil is seen as the country that attracts the most attention in winter season of 2019-2020.

Anahtar Kelimeler: Network science, football transfer market, excess degree, assortativity

Football is a “money game” and this feature of football is evident in the transfer markets. Network science, which has a wide range of applications from the brain to social networks, can also be applied to football transfer markets. In this manuscript, one million Euro has been taken as a threshold and the transfer market and 2019-2020 Winter transfer season of football was divided into two markets such as a low and high valued markets. After obtaining these two networks, their metrics and measures were calculated and compared. In addition, the article focused on “excess degree”, “assortativity” concepts of network science and investigated the differences between low and high-valued transfer markets in terms of these concepts. It was found that high market valued transfer network has a low assortativity coefficient (0.562), and low-valued transfer network has a high assortativity coefficient (0.836). This finding can be interpreted as the big transfer values, big money creates big differences in country’s transfer connections. The skewness of ingoing-outgoing degree differences distribution is much higher in the one with higher transfer values (0,962), than the one with lower transfer values (0,180). This situation can be attributed to larger deficits in the high-value market. Regarding total number of connections, self-loops and betweenness. In both networks, Brazil is seen as the country that attracts the most attention in winter season of 2019-2020.

Keywords: Network science, football transfer market, excess degree, assortativity