Data Analytics in Soccer

Data Analytics in Soccer


Data analytics (DA) is the process of examination of raw data and evaluating the data to come up with conclusions about various issues on a specific topic. Data analytics is used in various fields such as business, agriculture, education, tourism, healthcare, medicine, sports media, and te

Data analytics (DA) is the process of examination of raw data and evaluating the data to come up with conclusions about various issues on a specific topic. Data analytics is used in various fields such as business, agriculture, education, tourism, healthcare, medicine, sports media, and technology. Data analytics enables users to come up with better decisions and solutions to the problems that a field, such as business or sports, faces. It involves the mining of all forms of raw data, further sorting out the gathered data into necessary and unnecessary one and transforming it from just useless facts into valuable information. Data analytics is revolutionary in many fields. Thus, in soccer, it can help find necessary information, enabling managers, coaches, and players to make decisions and draw conclusions from all soccer-related data collected. Therefore, this paper discusses the importance of data analytics in soccer, and it can be used in many ways.

Uncovering can apply data analytics in soccer and analyze data on player runs and sprints. The science of data analytics could get videos on playing styles of teams or coaches and try to figure out the ways to counter a team’s playing style so that the opponents’ team could be defeated. Information on playing style can be used to determine a formation a team could use and find out which formation is the most effective and efficient one for a team. Thus, data analytics offers information on drawing conclusions for application of team mentality in a game. Furthermore, data analytics can be used to determine the type of individual playing style, and this information could influence an individual's playing style. For example, a player can be told not to make sprints when the game is not yet at its peak or make more sprints when the game is on the hour mark since it is determined that at this moment, most defenders have lapse in concentration. Therefore, data analytics draws conclusions from the raw facts gathered from players by the coaches.

The gathered data can be used by managers and coaches to determine the coaching techniques the team uses on the field. Data analytics gives the strengths and weaknesses the players have on the field. For example, a slow player is trained not to leave much space for an opponent to run into. Tall players can be given the best position on the field to win headers. For example, a tall player could isolate a short player to be able to make a shot. Data on the strength of a shot and curvature of the ball coupled with data on distance from goals can be used to determine set piece techniques that could help a team score a goal. The data could also be used to determine when to shoot a ball, pass a ball, and tackle an opponent or even make a save if the player is a goalkeeper. Consequently, data analytics helps in the improvement in coaching techniques.

Data analytics is used in the development of the soccer world. Evaluating data in soccer has its focus on the basics of soccer, for example, passing. The analysis of passing moves could determine the best ways to make passes and how to defend ‘dangerous’ passes. Good passing moves lead to goals. More to say, data analytics in soccer has led to the development of simulation practice sessions where technology has been used to create hypothetical situations that could happen when a player is on the field. This simulation assists the players in training on real game scenarios and determining ways to counter attacks and find the ways to create and score goals themselves. Consequently, many soccer teams collect data in the form of videos and other media content.

High-quality footage is used to determine mistakes a player or team makes during a game. This footage can be used to correct such mistakes at the click of a button. In the Barclays English Premier League, data analytics has revolutionized the world of soccer. This evolution is seen through extensive data mining techniques such as a set of eight to ten digital cameras on the pitch that track various soccer data elements such as offensive ball touches, fouls, possession, goal scoring chances created, and goal scoring chances converted. Thus, data analytics helps uncover necessary information from the many hours game footage and it is used to analyze players and playing styles.

Analysts look at the data to determine team’s weaknesses in a game. For example, low conversion rate means that the team does not have an efficient or effective striker. When many goals are conceded from set pieces, it means that the team does not defend well in set pieces. Managers and coaches use this data to gain insight on the occurrences during the game both off and on the ball. When soccer players participate in training sessions, they wear GPS trackers, acceleration sensors, and heart monitors. These devices collect data for the optimization of players’ preparation for a game. Devices from the advancement of technology have led to stunning developments of the gadgets used for data analysis, data collection, data evaluated and enabled analysis to draw solutions from the data collection site and processes the data into useful information.

Data analytics has enabled the development of soccer by applying information on the performance of a team or individual players on tactics to improve the efficiency and effectiveness of a playing style. Thus, information gathered by data analysts helps improve the preparedness of the player and the team and players as individuals. Therefore, data analytics is beneficial in the game. The advantages of data analytics are that soccer teams can gain a competitive advantage over their opponents. Prozone, a soccer analysis firm in the United Kingdom, works in the areas of game intelligence, athlete monitoring, and tactical profiling to assess the performance of players, give a quantification of players’ abilities and skills such as finishing, passing accuracy, pace, and playing style. Consequently, data analytics has been seen to improve the effectiveness and efficiency of the team as a whole and as a player as an individual.

The information can be used to reduce injury risk of players. The data analysis of injuries could determine when a player gets well from their respective injuries and define the best way to rehabilitate them in the most conducive way possible. The data that can be accessed for data analytics in soccer are passing accuracy data, some passes, and the number of shots taken by a player and a team. Another form of such data is the possessions held by the team. Data analytics help to prevent injury of players playing soccer in any position of the field. Thus, the science of data analytics is important in the evolution of the game..

In conclusion, data analytics (DA) is an important science in the development of various fields today. In the field of soccer, it is useful in determining various solutions to problems that might arise in the game. Data analytics is used to improve playing style of the team in general and players’ game in particular. Data analytics has had a major effect on soccer by improving the competitive advantage of teams. Using data gathered by analytics can help find necessary information, thus enabling managers, coaches, and players to make decisions and draw conclusions. Furthermore, data analytics in soccer also prevent injuries that could affect players. Therefore, one can definitely say that data analytics is effective and efficient in the world of soccer.


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