Sports Analytics : The Impact of Analytics on Sports Strategy

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Human Pose Estimation for Sport Analytics | Use Case

The Major Challenge of Sport Analytics

One of the most significant challenges in sports analytics is the need to bridge the gap between cutting-edge sports analytics technology and sports analytics foundations. This involves developing a deep understanding of statistical modeling and data analysis, as well as staying up-to-date with the latest advancements in fantasy sports players-driven insights. As the landscape of sports analytics continues to evolve, it's crucial for analysts to stay ahead of the curve by leveraging innovative tools and methodologies to gain a competitive edge.

The Power of Data: Unlocking Success in Sports Analytics

In today's data-driven sports analytics landscape, teams are leveraging advanced sports performance analytics to gain a competitive edge. By analyzing sports datasets, teams can gain valuable insights into player performance, identify areas for improvement, and make informed decisions to optimize their roster. For instance, analyzing player movements and injuries can help identify potential injury risk factors, allowing teams to implement proactive measures to prevent sports analytics injury prevention. The right tools, such as specialized software and data visualization platforms, are essential for collecting, analyzing, and presenting complex data in a clear and actionable context. By integrating these tools into their workflow, coaches and analysts can gain a deeper understanding of their team's performance and make data-driven decisions to drive success.

Solutions for Sport Analytics

Human pose estimation is the computer vision based technology that detects and analyzes human posture. Our model will detect the shots played by the player. And our model will detect the human pose estimation for the player playing the sport like badminton. Accordingly, our model will recommend moves based on the rules defined.

Predictive Analytical Process - Recommend Moves

AI-Based Shot Detection the camera will detect the player playing in the court with their shots like Net drop, Smash, Defend, Backend, forehand of the players. According to the model-specific coordinates, if the player misplayed the shot during the match, the model will recommend the moves for the particular shots played by the player.

Recommend Moves Dashboard

In this sample dashboard, an organization gives you the list of weak body parts for the particular player. After analyzing the video through the model, the player gets the recommendation of the posture and the % of the recommendation for particular body parts for the particular players. The model helps to detect complete incorrect posture.

End Customer Value

Here, every detection will cover shot detection and recommend moves to the player. The customer will get the different poses for different shots with coordinations for each poses detected by the camera. The model will recommend the player's best coordinates for that shots.

Why XenonStack ?

With the help of XenonStack Support gives the demo on the recommended moves of the player while applying the model on the player video and gives them the recommended moves according to accurate pose coordinates, which are standard defined in the model, and the organization will get the insights related to the model. Click here for the Demo of Moves Dashboard As for reference, our team created the dashboards from there, and the result are generated from our machine learning model. Our model will provide you with an accurate solution for computer vision.