Teamwork, Technology Transform Auburn Soccer


March 26, 2018

Teamwork, Technology Transform Auburn Soccer

‘An invaluable resource’: teamwork, technology transform Auburn soccer March 24, 2018 AUBURN, Ala. – If you picture a strength and conditioning coach with a whistle and some barbells, it’s time to refresh that image. At Auburn, you can add sport technology, which provides coaches new ways to integrate heart rate, GPS and other performance data.

The Neuroscience of Skill Acquisition – SimpliFaster

An amazing concept in neuroscience that’s not fully understood is the brain activation that results from visually imagining a particular action or scenario. For example, an elite athlete can quickly envision each possible outcome from directing a soccer ball downfield with numerous passing opportunities. This happens in split-second imagery before even touching the ball.

Prevent Biometrics’ Intelligent Mouthguard Quantifies Head Impacts

Vincent Miele was an amateur boxer as a teenager, who later became a ringside physician as a medical resident while training to be a neurosurgeon at West Virginia University. Along with the renowned Dr. Julian Bailes, the two conducted a video analysis comparing a control group of typical professional boxing matches with a set of highly competitive classic bouts and a set that ended with a fatality.

Understanding Analytics for Advanced Sports Performance | Sparta Science

“Actionable Data” is a buzzword in the sports performance industry right now. The world of big data often brings forward more noise, distractions, and confusion to sports performance practitioners. It is easy to get caught up with new technologies and data tracking devices because we confuse digital with scientific.

Should We Predict Development and Performance?

“Did you know the average age of medalist is 26 in running events, but in the throwing events it’s much older?” That’s how the conversation started, before progressing towards how we needed to center our development and funding models on this data. The underlying message was a simple one, we can predict performance using past data.

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