responsible ai
The Athlete Stays at the Center of Performance Intelligence
The design principles behind explainable metrics, adjustable analysis criteria, and reports built for real coaching conversations.
Performance intelligence is most useful when athletes, coaches, and specialists can understand, question, and adjust the evidence behind it. Automation can organize difficult footage, but it should not hide uncertainty or replace accountable judgment.
Explain how every metric is formed
A help view should describe the observation method, calculation, exclusions, confidence thresholds, and known limitations for each analysis section. That context turns a polished chart into something a coach can evaluate.
Keep comparison constructive
Two-fighter comparisons and radar charts can make patterns easier to see, but they should compare like-for-like rounds and disclose incomplete evidence. Strengths and weaknesses are better framed as review prompts than as permanent labels.
Analysis supports the decision; it does not replace the people responsible for it.
MachX performance intelligence principle