Like the European big leagues… Qualitative data growing in the K-League

Opportunities to meet high-quality data that could be seen in European big leagues such as the English Premier League (EPL) in the K-League are increasing. It is the result of the Professional Football Federation’s efforts to apply qualitative data to the K-League beyond quantitative data. This year, new data visits the fans.

The Professional Football Federation held a weekly briefing on the 11th and announced that it will introduce new packing (pass) index and activity (physical) starting this year. This is data newly introduced to the K-League following activity in 2020, expected goals (xG) and Adidas points in 2021, and defense index in 2022.

Packing is an index that tells you how many opponents you have beaten by passing or dribbling. If the pass passes two opposing team players, the packing index of the successful pass is ‘2’. If the number of successful passes counted so far was simple quantitative data, the packing index is qualitative data that can evaluate how nutritious the pass is. The federation plans to release the packing index every month with Bpro 11, an official additional data provider.

This index drew attention immediately after the semi-finals in which Germany defeated Brazil 7-1 at the 2014 FIFA World Cup in Brazil. At that time, there was no significant difference between the two teams in the number of shots, possession, and pass success rate, but Germany was significantly ahead in overall packing and opponent’s packing. In the European Football Federation (UEFA) Euro 2016, out of a total of 51 matches, the team with the highest packing index won 34 matches, drew 14 matches, and lost 3 matches.

Kim Young-kwon and Park Yong-woo (Ulsan Hyundai) ranked first and second in the K-League 1 Packing (Pass) Index for February and March, which the federation first revealed on this day. Kim Young-gwon’s total packing index was 369, and Park Yong-woo’s was 330. The federation analyzed that they could be interpreted as key players in the Ulsan build-up. They were followed by Lee Jong-seong (Suwon Samsung, 312), Ahn Young-gyu (Gwangju FC, 296), and Kim O-gyu (Jeju United, 294).

The federation will also use optical tracking system technology to disclose the total distance (km), top speed (km/h), number of sprints, and the top 5 sprint distances of the K-League players on a monthly basis. A sprint is when a driver reaches a speed of 22.68 km/h or higher while maintaining a speed of 14.4 km/h or higher for at least 2 seconds.

This data was also released in 2020, but at the time, it was difficult to compare and analyze accurately because the GPS equipment for each club, such as the physical coach’s preferred equipment, was different. However, from this year, all clubs applied the same measurement method, enabling accurate comparison. Fans will be able to check the top speed and total distance data of players seen in European big leagues such as the EPL with more accurate data.

As of February/March, Seo Young-jae (Daejeon Hana Citizen) dominated the first and second places in the top 5 fastest speeds. His top speed against Pohang Steelers reached 35.67 km/h, and he recorded a top speed of 34.91 km/h against Gangwon FC. The first place in the overall running distance was Go Seung-beom (Suwon Samsung, 50.53 km).안전놀이터 In both the number of sprints and the distance, Kim Do-hyeok (Incheon United) took first place with 139 and 2745m, respectively.

An official from the federation said, “Starting with collecting additional data in 2015, we established a data portal in 2018 to provide an environment where the public can easily browse at any time. Furthermore, we are providing secondary processed data using additional data such as Adidas points, expected goals, and saved index. We will develop and disclose qualitative data.”

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