An efficient rating system for players based on their position statistics

The sports industry has seen a lucrative rise in stature and has now become an important contributor to the global economy. Huge amounts of finances and money are being invested in the sports industry and with that the amount of data generated by sports has multiplied exponentially. With the rise of data science, and the increase in sports data, sports analytics has become an interesting research direction. In this paper, we developed a mathematical model for rating each player, based on their position statistics and performance. These performance ratings are also beneficial to coaches and managers who look to improve player performances and justify player selections. Extensive experiments on a public hockey dataset of 2014 world cup Hockey shows the effectiveness of the proposed approach. We also applied the proposed model to 2018 world cup hockey dataset to rate each player. In addition, a visualization framework is developed to visualize each player's performance.