Welcome to another discussion on sports analytics! Today, I will discuss a topic that we’ve touched up on before… machine learning analysis. Machine Learning Analysis can be applied in sports analytics to improve team sporting performance and winning opportunities.
Machine-learning analysis for sports analytics involves the use of a data-programmed machine to make analysis. The machines used in this analysis are programmed to detect similar playing patterns in individual players in the game of sports.
WHY MACHINE LEARNING ANALYTICS?
Machine learning can analyze complex information such as the speed of team players on the field, distance covered by players, and their level of fatigue both on the field and after a play.
This is in order to help team coaches determine the best course of action for their teams, such as which player to replace during a match and what to expect from competitors during the match. The machine learning analysis is important for the following areas:
- A major advantage of using machine learning is its flexibility in managing large volumes of data as well as multiple data sources. The use of a machine learning made data collection easier and more effective.
- Machine learning is a quicker method of analytics. Using this method of analytics, coaches and sports analysts may not need to spend many hours on watching recorded game films, because meaningful insights can be derived by simply viewing the machine learning analysis. This also gives coaches the benefit of spending more time solving team problems as many solutions are already detected by the machine.
- Machine analysis is a critical and detailed method for analyzing data of continuous sport activity, such as soccer where the data is either 0 (nil) or 1(goal).
HOW MACHINE LEARNING HAS REVOLUTIONIZED THE WORLD OF SPORTS
Machine learning analytics is fast becoming popular in the world of sports. Several sports have recorded huge success through the use of machine learning.
For example, the use of machine learning analysis has been employed by the famous Manchester City Football Club. According to research, this has greatly improved their team performance. Manchester City Football Club is also known to employ this technique in recruiting new players as well as in determining what play will suit a field position.
Machine learning analysis is utilized by Chicago-based firm STATS (Sports Team Analysis and Tracking Systems) in assembling information on various player movement. In previous years, STATS has employed the use of cameras in Europe soccer stadiums and NBA arenas. These cameras, which are integral of SportsVU system, are programmed with the ability to track the movement of the individual players and the ball at 25 frames per second. STATS cameras have also been programmed to analyze other individual player strengths and weakness, such as running speed, ball possession and distance/endurance. In other words, the benefits of using machine learning analysis can be greatly improved with the application of artificial intelligence.
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