The biggest GAP in Sports Analytics...YOU can fill it

The biggest gap in sports data analytics is the ability to integrate:

1. Context (historical data/box stats) with….

2. Qualitative (biomechanics)….and….

3. Real-time information (current conditions and events).

……into decision-ready analytics or insights that you can act on before anyone else.

The key is to be able to do qualitative analysis (QA). QA reveals player biomechanics changes that help to explain why a player or team is gaining momentum or losing its edge — ahead of the scoreboard.

QA is a vital aspect of predictive analysis that most people overlook because it requires a combination of domain knowledge (what you know about sports skills and performance) and integrates that with data and current play conditions.

Bottom line: it's easier to write equations and plug in box stats than analyze real-time human movement.

But the person who can do QA has the edge to predict player performance AND outcomes in real-time. Real-time analysis is the gap. Real-time sports analytics is the present and future, and it's a lot easier than you've been led to believe. Anyone with gym and/or sports experience can learn how to do it for the real world.

To learn more about biomechanics qualitative analysis and step-by-step method to do it, click here. 

Author Biography

Amy Ashmore, Ph.D. holds a doctorate in Kinesiology from the University of Texas at Austin. She is located in Las Vegas, NV.