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  • Sport Consumption, Fan Engagement, Sport Statistics – Post-specific Passing Characteristics in Football
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    Digitalization and the explosive development of technology have led to significant changes in football. Due to the increasing amount of data available through various sensors and other data collections, we can observe the rise of data-centric, analytical and statistically oriented thinking in football, which is also of interest to fans. Digitalisation is also closely linked to sports consumption, which is why we have seen significant changes in this area in recent years. The pandemic has further amplified the speed of digital transformation in the sports industry. One of the most important contents for sports organizations and their fans is the in-depth sports statistics and analysis that enhances the consumer experience. In our study, we examined the most common performance indicator in football, passing. Our goal was to examine the position-specific pass characteristics in detail, therefore we also examined different pass properties in our research. As a model for our analysis, I chose the premier league, which has the highest UEFA coefficient. The three rounds (rounds 30-32) of the championship season 2019/2020 have been recorded and analyzed in terms of passes. there was a significant difference between the average number of passes per game between defensive and offensive players (t=7,988, p<0.05). There is also a gradual decrease in the number of passes attempted per match and the accuracy of the pass in the examination of the middle positions when examining the positions in the depth of the pitch. For both pass accuracy and average pass count, the decreasing ranking corresponds to the position of positions on the pitch (order: 1, central defender 2, defensive midfielder 3, inside midfielder 4, attacking midfielder 5, striker). In the value indicator of the position for passes, offensive positions performed more effectively than defensive positions. The extreme positions also stand out among the attacking positions, where in the case of the position value per pass number, 23.3% of the total test was completed and 14% of the amount of the established position value indicators was provided by these posts. Overall, our study points to post-specific pass characteristics and, knowing this, we can state that the comparison of players' passing performance is relevant if the players are in the same or related positions.

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