Analytics is the buzzword in sports now. Although most of us couldn’t give the definition, it sounds like the fast-rail pass to where we need to get to. This notion of analytics has made the field of sports performance and/or strength & conditioning worse off. However, the dilemma isn’t from analytics in its true form, but rather the misuse of reporting.
Reporting isn’t enough
Reporting answers the question of what is happening? Reporting is usually driven by an organization’s Key Performance Indicators (KPIs). These reports began decades ago, handing printouts of KPIs including 1RMs, max speed, vertical jump height, etc. Then GPS was introduced and dozens of other “KPIs” began to get reported on a daily basis. Modern reporting might tell you:
Squat Maxes are up 15% since last semester
We average 940 high speed yards per practice with our Linebackers
Our days lost due to injury is down by 17% from last year
Assuming an organization’s KPIs are valid metrics to be looking at in the first place, reporting is important! An organization must know what is going on first. However, the more important question is, why is this happening? Did our injury rates go down because of the strength and conditioning program? Or was it because of the pre-hab the athletic trainers have implemented? Or maybe it was because of the high tech turf we installed in the practice facility.
Analytics answers question of why is it happening? It is is the discovery and communication of meaningful patterns in data. This does not mean presenting beautiful graphs comparing two training variables, or one’s athlete’s training history over time, represented by a line graph (reporting!). These isolated cases are more artistic, but far from useful insights to help us understand why things happen. It is important to know why so you can 1) repeat the outcome if desired 2) take steps to change the outcome if it is not desired. Analytics might tell you:
Days lost due to injury went down by 17% due to 5 less injuries suffered during the year. 15 athletes were at risk for injury upon report date in August while only 7 were at risk in May due to improvements in the sPARTA Signature. The most effective plans for improving the SPARTA Signature in this team were Plan 3, Plan 9, and Plan 12.
To draw useful insights requires large volumes of data, particularly when measuring the unpredictability of the human body’s response to training, and the compliance challenges present in all health care. As a result, statisticians and/or statistical equations can help identify the key patterns. Here at Sparta, we use two independent University Statistics departments to help verify the validity of our database and draw out useful correlations.
Many international organizations we work with have recognized the advantage of outsourcing these skills and expertise. They have third party software companies and academic institutions provide the software development and data science. This allows the organization’s internal staff accomplish the real goal; informed decision making based on relevant information for improved outcomes.