Using the power of Data Science and Engineering to monitor, predict, mitigate, and prevent injuries
About Us
Digital Athlete® is an organization dedicated to improving the long-term health and safety of athletes. Our mission is to monitor, predict, mitigate, and prevent injuries experienced by athletes.
Jeff Crandall
Founder
Sam Huddleston
Principal Data Scientist
Thomas Adam
Senior Data Engineer
Britt Evans
Senior Data Engineer
Rob Mulla
Senior Data Scientist
Ben Huddleston
Senior Software Developer (UI/UX)
Lee Gabler
Senior Engineer
Meet our team
Our team is made up of biomechanists, engineers, and data nerds. We love digging into big problems and figuring out how to make raw data tell a story.
The Digital Athlete® Application
Digital twin software is an advanced form of simulation software, using sensors to create accurate, real-time simulations of athlete performance, health and safety. Creating a digital twin for each athlete creates a better understanding of risks posed over their careers and the underlying biomechanics of injury in their sports.
Consistently updated
Through daily ingestion of the latest sensor and performance data, monitoring health information and daily load of players, the Digital Athlete® application is always up to date. Combining predictive data models with expertise of athletic trainers and strength and conditioning coaches, the Digital Athlete® application provides a comprehensive view of the health of each player, with the ability to easily determine which players are at highest risk for injury.
View what drives risk
The Player Detail View of the allows users to monitor daily trends for player risk levels as well as which features of the model are driving increased and decreased risk levels.
Quickly assess positions and players within them have the highest risk of injury
Through our positional risk view, trainers and coaches can easily identify positions that are at highest risk of injury. This allows for targeted interventions to be applied to the players that need it most. The system allows for quick determination if players are going outside the bounds of league risk norms as well as team risk norms. Users can watch for trends of players who need interventions and determine if those interventions are working to lower risk.
Digital Twin Software
We have developed a comprehensive, searchable, longitudinal digital record of significant events (training, game events, injuries, etc.) experienced by athletes. The Digital Athlete® application allows football teams to view predictive models of injury risk, and to monitor the health of their athletes. Our machine learning models, combined with past history of players, performance, sensor, and equipment data allow us to predict the likelihood of injury for each player. Some of the sensor and data systems used by Digital Athlete® are outlined below:
Performance Tracking Systems
Performance tracking systems provide location, performance and load for individual athletes both in games and practice.
Equipment Databases
Equipment information used by individual athletes and the performance of that equipment in different field environments.
Injury Surveillance Databases
Detailed injury statistics and data is incorporated into analysis around injury prevention and mitigation.
Video Data
Through video data integrated with injury statistics, performance systems, and AI, we gain a greater understanding of what drives injury and how to prevent it in the future.
Field & Surface Conditions
Turf makeup combined with equipment data helps drive safety and understanding of cleat design and performance
Head Impact Detection
Understanding kinematics surrounding head injuries determine drivers behind concussion and how head impacts effect athletes as well as determine safety measures to improve helmet design.