Boosting Indian Athletes’ Performance with Tech, Analytics & AI

Staying ahead of the game is crucial for athletes and teams striving for success. Whether for the national game, field hockey, or the beloved sport of cricket, fans and communities in India expect only great things from athletes. 

However, injury rates have significantly increased, and barriers to the big sports teams are becoming harder to overcome. To ensure exceptional player performance, prevent injuries, and drive strategic decision-making in sports, sports organizations are turning to technology such as analytics, machine learning (ML), and artificial intelligence (AI).

Preventing injuries through Data & ML

Injuries are common in sports and can have significant consequences. In the last 10-15 years, there have been 500% more knee and ankle injuries and 400% more ACL injuries. Machine learning, a subset of AI that involves training algorithms to learn patterns from data, is a powerful tool that can help predict and prevent athlete injuries. 

By analyzing various physical, physiological, social, and psychological parameters, a machine learning algorithm can forecast the likelihood of injury, monitor any signs of fatigue or abnormal movement, and provide guidance for rehabilitation. Examples of such algorithms include decision trees, random forests, and neural networks. 

The main component of injury prevention is understanding the risk factors or parameters involved and their interplay. Several parameters can come into play: the athlete’s body condition, player workload data, biomechanical information, previous injury history, external environmental factors, and more. For contact sports, it’s also crucial to consider the key characteristics of the opposing team. 

With so many parameters, a comprehensive ML/AI model is crucial. The model must outline the sequence of events leading to injury and describe the body and joint biomechanics at the time of the incident. 

Challenges in data and implementation

Injury prevention in sports is increasingly becoming data-driven. However, accurate predictions are only possible with the correct data. 

Data is the biggest challenge in leveraging ML for sports. Firstly, there is no common data capture mechanism to gather comprehensive data over a significant time frame. Parameters need to be observed over 3 months to a couple of years, which can be a challenge. Take, for instance, an up-and-coming athlete who recently joined a sports team. Let’s say they could train in official facilities for the last quarter. This means the organization will have 3 months’ worth of data to ensure the athlete isn’t injured. However, this does not consider historical data from before the athlete joined.

Secondly, standardized datasets are needed to validate and test models on player injury. Implementing an open-source repository can help improve the use of machine learning. However, only the biggest sports teams and professional athletes may have access to comprehensive data gathering and analysis. In fact, not every athlete has access to the right tech—or even the right shoes and gear.

At Orion, enabling a standard mechanism for data and analysis is a top priority, not just at the professional level but also at the grassroots level. Through the Orion Grassroots Platform, we are transforming sports from the ground up.

The role of wearables 

Wearable devices have emerged as a promising solution, providing teams with invaluable real-time insights into player performance and health. From simple fitness trackers to advanced sensors, these devices offer a window into crucial metrics such as heart rate, oxygen levels, speed, distance covered, acceleration, and biomechanical data. Depending on the device and sport, wearables can empower coaches and medical staff to understand better the physical demands placed on athletes and make decisions about a player’s risk of injury. 

Wearables are truly a step in the right direction; however, it’s essential to recognize their limitations. While they can capture 50% to 60% of the data required for injury prediction, wearables only provide insights into ongoing and future performance. This means that historical data, which could offer crucial context, may be lacking. Most devices also require a hefty financial investment. Bridging this data gap and improving technological accessibility is essential for maximizing wearables’ utility in sports and ensuring that all athletes have access to the benefits they offer.

Crucial Considerations for Data, Analytics & AI

Just like any other data-driven initiative, leveraging analytics, ML, or AI raises concerns about data privacy, protection, and cybersecurity. 

Ensuring data security is key. After all, the data gathered and analyzed can genuinely make or break an athlete’s career. Sports clubs and organizations are also cautious about sharing injury information publicly, fearing it may compromise their competitive edge. 

The growing popularity of AI algorithms is also raising concerns about biases and unfair treatment based on race, gender, or socioeconomic status. Ensuring transparency and accountability is crucial to maintaining fair competition. India’s Ministry of Electronics and Information Technology (MeitY) is already taking steps in the right direction by stipulating that AI technology must get government permission to operate in India.

These concerns in data sharing need to be addressed in establishing standardized data frameworks across the industry. There is also the question of determining who can leverage these data and analytics tools. Ensuring an even playing field is difficult if there are significant barriers to technology adoption – not everyone can afford to get access to the required software and hardware. While there are several barriers to leveraging technology, the two main ones are economic and access constraints. This directly contradicts the values of fairness, integrity, and equality, which is the primary goal of sports.

Overcoming barriers

Digital transformation and innovation are key to unlocking Indian sports’ full potential. By embracing technology, analytics, and AI, athletes can optimize their performance, minimize injury risks, and make data-driven decisions on and off the field. Collaboration between sports organizations, technology firms, and government agencies is essential to driving this transformation forward.

Satish Kumar – Global Head of Sports and Entertainment at Orion.

Image Source: Freepik

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