Sports Medicine Data

What Is Sports Medicine Data?

The field of sports medicine combines sport, kinesiology, physical therapy, and other health and fitness topics to improve athlete performance and overall health. However, rather than focusing solely on improving competence in a particular sport, sports medicine data takes on a holistic view of the athlete: everything from sleep schedule to nutrition to mood is tracked in order to improve performance and reduce the risk and recovery time of injuries.

Additionally, an athlete in this context does not refer solely to an elite-level athlete; recreational athletes are the main sources and users of sports medicine data.

Where Does Sports Medicine Data Come From?

Most authoritative sources come from medical and scientific journals or other publications. However, the greatest amount of raw data comes from athletes and coaches themselves, who record—increasingly, with wearable devices—data on their own performance.

What Types of Columns/Attributes Should I Expect When Working with This Data?

Sports medicine data includes sport-specific measurements, often divided by sex and age. Some studies, however, divide the sports into categories like “endurance sports” or “power-based sports.”

Another common field of sports medicine is injury prevention and recovery. Physical trainers and doctors know quite a bit about injury prevention and recovery, but oftentimes licensed physical therapists must provide the road map for athlete recovery and rehabilitation. Their therapeutic data, however, still falls under the larger field of sports medicine.

Finally, there is data on individual athletes—sometimes specifically studied in scientific journals and sometimes maintained by individual recreational athletes. Important attributes include sleep quality, mood, hormone levels, weight, and athletic milestones, but the number of attributes that can be studied and the decree of specificity varies wildly.

What Is Sports Medicine Data Used For?

Naturally, the purpose of sports medicine is to improve athletic performance. Athletes—whether by themselves or with trainers or doctors—do this by, first, establishing a benchmark, then setting up performance goals and plans to reach them.

Sometimes, however, this data is used as an addition to another health-related goal, such as weight management or illness rehabilitation. In all cases, however, proper risk management must be followed.

How Should I Test the Quality of This Data?

A general-use data set can rely on research studies published in medical journals. In this case, the main challenge of ensuring data quality may simply be data cleansing. However, for a data set with a specific athlete’s performance or rehabilitation in mind, that individual’s self-reported data may be the only thing that can be relied upon. Adoption of wearable technology may help mitigate the chances of incomplete or inaccurate data in this case. However, as noted, the level of specificity can vary wildly; some athletes may be content with mostly accurate data as long as they make some progress in their goals.

Interesting Case Studies and Blogs to Look Into

Springer: Sports Medicine
BMJ Journals: The athlete monitoring cycle: a practical guide to interpreting and applying training monitoring data

Tangible Examples of Impact

For the last 15 years, the editors of ACSM’s Health & Fitness Journal® (FIT) have circulated an electronic survey to thousands of professionals around the world to determine health and fitness trends for the following year.
…
New to the top 20 trends identified for 2021 include a new no. 1, online training (which was no. 26 in 2020), virtual training (no. 6), and mobile exercise apps (no. 12). Falling to no. 5 is high-intensity interval training (HIIT) and falling to no. 17 is group training.

ACSM’s Health & Fitness Journal: Worldwide Survey of Fitness Trends for 2021