07/03/2024
Some things we’ve been working on the past few years with to share some surface-level insights into the objectives we’re trying to accomplish and questions we’re trying to answer
We’re very fortunate to be working with to handle almost all of our data collation/cleaning, analysis, and dissemination processes. By in large, we’re looking to use the information to:
- Better inform and individualize the training process, and drive athlete intent towards and understanding of that process
- Understand sport demands during various phases of the year and ensure preparatory efforts are moving us towards being ready for them
- Identify and proactively flag rate limiters/risk factors that could limit athletes from maximizing their preparation to perform their best when it matters most
- Optimize information sharing across the program to maximize synchronicity and influence decision-making processes more objectively
Some details on the included visuals:
1. Comprehensive Player Profiles- surface view of where an athlete is currently at across most of our key data streams. What the athlete sees in their phone is the same that their coach sees on their tablet, so there are no surprises, information gaps, or discrepancies.
2. Automated Training Buckets- monthly performance testing results categorize each athlete into training priorities for the next 4 week cycle. Generally, 1st priority is asymmetry reduction, 2nd priority is power/strength levels relative to positional norms, 3rd priority is retention of symmetry/output.
3. Publicized Performance Ratings- athlete testing results are contextualized to a “Madden” (BK) Rating that is a weighted combination of their all-time best output on that test, and their most recent outputs on that test. Highlight guys who generate high outputs, but also incentivize them to continually train/test at a high level. Ratings are relative to all-time data at the team level, overall rating is derived from all-time data compared to position group.
*Continued in comments*