AI Sprint Performance Analytics
This AI solution uses advanced mathematical modeling, multimodal LLM reasoning, and deep learning to analyze and optimize sprint performance and identify emerging talent. By integrating biomechanical data, race metrics, and athlete profiles, it delivers actionable insights for training design, race strategy, and scouting decisions, helping teams and organizations maximize competitive results and athlete value.
The Problem
“Unify splits, biomechanics, and training load into sprint strategy + talent signals”
Organizations face these key challenges:
Coaches spend hours in spreadsheets/video yet still disagree on what drove a performance
Athletes plateau because training changes are based on intuition instead of quantified drivers
Scouting decisions rely on raw times without context (wind, reaction, mechanics, development curve)
Injury/overtraining risk rises when load, recovery, and sprint mechanics aren’t tracked together