What we do
At W10NIS, we engineer athlete-specific performance systems that translate physiometric data into precision-timed competitive strategy. Our work provides real-time physiological oversight rooted in female-specific autonomic science and built from the unique physiological fingerprint of each WTA athlete.
We use continuous HRV tracking, endocrine phase modeling, adaptive recovery analysis, and load diagnostics to detect physiological vulnerability before it manifests as performance decline. Each signal is processed through individualized models that account for circadian misalignment, travel compression, surface reactivity, and hormonal phase shifts.
These systems are supported by AI-enhanced analytics and machine learning models that continuously refine their accuracy. By evaluating multidimensional physiodata streams over time, we identify suppression risk, fatigue accumulation, and taper misalignment with increasing specificity.
We do not deliver generalized feedback. We deliver individualized, physiology-driven decision systems. Internal capacity is not estimated. It is modeled, interpreted, and aligned with external competitive demands.
Our approach
The W10NIS approach is grounded in applied physioperformance science and executed through AI-supported modeling architectures. We integrate longitudinal physiodata with adaptive algorithmic analysis to construct individualized load-response forecasts, readiness predictions, and endocrine-synchronized taper strategies.
Each precision decision system is fully menstrual-cycle integrated and responsive to phase-based changes in stress reactivity, vagal tone regulation, and recovery slope behavior. By synchronizing internal physiological capacity with external tour demands, we provide a strategic platform for coaches and athletes to navigate volatile scheduling conditions with clarity.
Physiological signals are decoded using machine learning classifiers trained to detect complex multivariate patterns across parasympathetic tone, circadian strain, and endocrine modulation. These models update dynamically as new data is introduced and are designed to deliver coaching-relevant forecasts, real-time diagnostics, and actionable physiological insights.
We do not build general tools. We engineer athlete-specific physiometric systems that elevate strategy through biologically timed intelligence. Every output is constructed with scientific oversight and delivered through direct collaboration with Daniel Alexander van Skye, DBA.
This is physioperformance science applied in real time. Every system is custom-built. Every recommendation is grounded in her physiology.