Research, evidence and collaboration.

The formulas used for baseline generation and biofeedback are based on research conducted by the scientists involved in the project and consolidated across years of work on EEG data, cognitive traits and performance-related neurophysiological patterns. In the foundational research, psychometric tools such as STAI-S and STAI-T were also used alongside EEG correlates, allowing neurophysiological patterns to be interpreted in relation to validated cognitive and state/trait measures.

For this reason, MindCHAMP treats EEG as a complementary physiological indicator, not as a direct reading of emotions, intentions or clinical status. The platform does not perform emotional inference, does not classify athletes according to emotional states and does not provide psychological or medical diagnoses. Its purpose is to support cognitive training through feedback on focus, brain-band trends, cognitive load and self-regulation during guided tasks.

Individual baselines are central to the methodology. Two athletes may show different absolute EEG values while both progressing effectively within their own cognitive training pathway. MindCHAMP therefore prioritises change over time, comparing each athlete with their own profile rather than treating absolute values as universal judgements.

The coach platform also supports group-level interpretation through standardised comparisons such as Z-scores. These are intended as guidance for training planning, not as ranking or diagnostic tools. At team level, the research framework also considers patterns linked to coordination and brain synchronisation, understood as functional alignment between players that may support team performance.

Research-informed training areas

MindCHAMP integrates protocols inspired by research on Action Observation and Motor Imagery, which suggest that observing and imagining technical actions can engage neural networks partially overlapping with those involved in motor execution. When combined with physical practice, these approaches may support motor learning, technical representation and mental preparation.

The platform also draws on research areas such as Quiet Eye, visual scanning, temporal occlusion, anticipation training, mindfulness-based regulation and recovery practices. These methods are used to structure guided cognitive exercises for focus, preparation, pressure management and recovery.