Recommendation systems that understand what drills actually develop—not just 'this is a footwork drill' but 'this develops lateral agility under pressure'—so they can suggest drills that target your specific gaps. Better recommendations come from understanding the mechanism, not just the category.
Similarity matching is a technique where an AI system compares a user current skill profile, weaknesses, and learning style against a library of athletes with comparable characteristics to surface the drills and exercises that produced the best outcomes for similar individuals. It relies on vector-based comparisons to find the closest matches in multi-dimensional performance data.
For athletes and recreational players, similarity matching removes the guesswork from choosing practice routines by grounding recommendations in evidence from people who share the same starting point, making training more efficient and personalized.
Peri can explain this concept, give practical examples, help you decide whether it applies to your situation, or recommend a journey if appropriate.
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