How Artificial Intelligence & Deep Learning Change the Game

AI & Deep Learning allow organizations to maximize player performance while minimizing player risk through better insights from performance and wellness data.

Atif Kureishy
Atif Kureishy
11 septembre 2019 5 min de lecture
Elegant neural networks | Artificial intelligence and deep learning

We treat athletes as if they are real-life superheroes that overcome physical challenges to achieve greatness in their respective sports. Today’s athletes are physically faster, stronger and more agile than the generation before, but something is wrong.

Some recent news include -

  1. The NBA expands mental health program for players.
  2. The NFL is facing a concussion epidemic and has started several programs and rule changes to better protect the players from brain injury

We have not made the same progress in improving athletes’ mental skills and health as we have physical skills and health.

Player Performance

The focus of any individual or team sport is to maximize player performance. In our sports culture, we are obsessed with team and player statistics using traditional measures in each sport. Player performance directly translates to increased probability of winning in individual sports. Team sports have added complexity based on interactions of multiple players in a team.

Player performance measures are usually categorized into two areas- 

  1. Physical Skills – Primary characteristics of power, agility, flexibility, endurance, and speed. Examples include 40-yard sprint times, pitching velocity, and vertical jump height. 
  2. Mental Skills – Primary characteristics of concentration, emotion management, mental imagery, interpersonal communication. Examples include trail making tests and cognitive reaction times.

Each sport measures the impact of a blend of physical and mental skills in ways that are specific to that sport, per category and position. Examples are:

  • Basketball – Field Goals Made, Field Goals Attempted, Free Throw Percentage
  • Football – Passing Yards, Point After Touchdown, Completion Percentage
  • Hockey – Points, Goals, Save Percentage
  • Soccer – Shots on Goal, Assists, Yellow Cards

Understanding the ways in which a player processes information is very helpful in terms of coaching, motivating and designing the types of practices that will be most effective in developing the athlete as an individual and as part of the team. What truly becomes interesting is the intersection of this subjective data with the objective data related to the way the athlete's brain actually functions, which includes measurements related to mental skills.

We have an opportunity to bring a whole new breadth to the path of maximized performance. Additionally, when applied in a team dynamic or game situation, the opportunities for making sense of these interactions and how to best use it on a timely basis is a key means for success at all levels of the game.

Player Wellness

To increase the longevity and effectiveness of players over the course of their careers, wellness programs are being established to better guide athletes on the physical and mental challenges that they will face. In the past, these wellness programs were solely focused on physical health and were not personalized per athlete or team nor focused on the mental health aspects of the sport. By establishing a preventative wellness program tailored for each athlete, Sports Enterprises can not only maintain athlete’s well-being but also increase their performance.

Physical health

The physical toll of sports is relatively well understood and has driven rapid progress in the field of sports medicine that benefit us everyday. We learned about treating both acute and chronic injuries, however much less is understood about the mental health aspects of sports medicine –

  • Acute - A common injury that occurs in high-impact sports is an acute tear of the ACL. Before, an ACL tear was the end of a career but now it means 6-10 months of rehab before getting back in the field of play. Better techniques for ACL reconstruction, improved physical therapy regimens, holistic protocols for sports rehab all contribute to shortening the duration of returning to play. 
  • Chronic - Alternatively, chronic injuries like bursitis becomes increasingly difficult to treat as overuse causes recurring inflammation of the knee. This chronic condition can cause secondary effects such as imbalance caused by shifting load onto the supporting knee, thus amplifying the effects to the athlete and increasing the risk of significant long-term injury like osteoarthritis.

Mental health 

Any top-tier professional athlete will tell you that the game is much more of a mental challenge then physical. Mental preparation is what separates good athletes from elite athletes. There is a darker side that we haven’t traditionally spoken about but now is increasingly in the news. Every day we hear about the mental health crisis that are affecting professional athletes that includes mental disorders such as depressionanxiety, and bi-polar illness.

The area of mental health in sports have been opaque and stigmatized due to lack of understanding. EEG, which is electrical activity of the brain collected via non-invasive means, provides a multi-channel, high-frequency, low-latency, time-series data set for an athlete. While brain research is ever-evolving, comparative baselines of EEG measurements have provided utility in diagnosing brain injury and recovery although acute vis-à-vis chronic brain injuries are still not well-understood. This area of EEG analysis is greatly unchartered but offers the next frontier in improving mental health of players due to its ease of deployment.

The Brain – Combining physical and mental understanding

In an effort to maximize performance while reducing player risk, we look to have a deeper understanding of the brain. The brain influences both the physical and mental skills and health of each player but remains largely unexplored in the Sports Enterprise. Artificial Intelligence offers a unique approach to understanding our own brains but is still a broad term that is a bit misunderstood, full of both promise and hype, fact and fiction. The simplest definition of Artificial Intelligence refers to software systems that behave with intelligence without being explicitly programmed. These systems learn to identify and classify input patterns, make and act on probabilistic predictions and operate without explicit rules or supervision.

Deep learning (DL) is where we are seeing the biggest breakthroughs in the field. Deep learning detects patterns by using artificial neural networks. These artificial neural networks are modeled after the most elegant neural network, our brain, and contain multiple layers to enable automatic feature extraction from the data – something that was impossible with machine learning – with each successive layer, using the output from the previous layer as input. Because of its architecture, deep learning excels at dealing with high degrees of complexity, forms and volumes of data. It can understand, learn, predict and adapt, autonomously improving itself over time.

For most of the last 100 years, brain exploration has been dominated by research which have derived broadly accepted measures such as P300 amplitude. Only recently, accessibility of high-quality EEG data combined with GPU-accelerated computation and advanced deep learning approaches has allowed us to move beyond hand-crafted EEG features. Within the Sports Enterprise, understanding of the players’ brain needs to be combined with the objectives of the organization to provide the right context and control. In the context of professional sports, these objectives loosely translate to improving player performance & wellness, leading to enhanced fan experience, increased revenues, and a winning culture.

How Artificial Intelligence & Deep Learning changes the game

Artificial Intelligence & Deep Learning can identify latent patterns, known as biomarkers, in EEG that change over time, and are associated with player performance and wellness. These biomarkers can be used to measure and achieve the personalized objectives of each player and team. By combining high quality data from different modalities (e.g. EEG, sleep, heart rate variability, performance statistics) and forming a player performance & wellness profile, we can identify these biomarkers and better understand causal relationships between the physical and mental aspects of sports. Pervasive Data Intelligence enables the automation of biomarker discovery through representation learning, i.e. finding higher order feature spaces that relate to specific phenomenon.

By applying Pervasive Data Intelligence, a Sports Team Doctor now has a path to utilize these biomarkers per player performance & wellness profile. Artificial Intelligence & Deep Learning allow organizations to maximize player performance while minimizing player risk through better insights from 100% of performance and wellness data, at the scale that only automation can deliver.

Artificial Intelligence & Deep Learning allow organizations to maximize player performance while minimizing player risk through better insights from 100% of performance and wellness data, at the scale that only automation can deliver.

À propos de Atif Kureishy

Atif is the Global VP, Emerging Practices, Artificial Intelligence & Deep Learning at Teradata.

Based in San Diego, Atif specializes in enabling clients across all major industry verticals, through strategic partnerships, to deliver complex analytical solutions built on machine and deep learning. His teams are trusted advisors to the world’s most innovative companies to develop next-generation capabilities for strategic data-driven outcomes in the areas of artificial intelligence, deep learning & data science.

Atif has more than 18 years in strategic and technology consulting, working with senior executive clients. During this time, he has both written extensively and advised organizations on numerous topics, ranging from improving the digital customer experience to multi-national data analytics programs for smarter cities, cyber network defense for critical infrastructure protection, financial crime analytics for tracking illicit funds flow, and the use of smart data to enable analytic-driven value generation for energy & natural resource operational efficiencies.

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