BioThread — Proprietary Metrics Brainstorm¶

Captured 2026-03-18. Each metric follows the "cross-reference what others don't" pattern.

Metric #1: GAP Score (General Adaptation Profile) (Active — see CNS_FATIGUE_GAP_SPEC.md)¶

Cross-references cardiovascular recovery against neuromuscular markers to detect when the heart is recovered but the nervous system isn't. Flagship metric.

Metric #2: Readiness Asymmetry Index¶

Compare left vs. right side ground contact time and force distribution. A 5% GCT asymmetry developing over 2 weeks = early warning for compensatory movement patterns that precede injury. Catches passively what coaches only catch during visual movement screens.

Metric #3: Adaptation Velocity¶

Rate of change in performance metrics (pace at given HR, power output) vs. rate of change in recovery metrics. When adaptation decelerates while fatigue accelerates = overreaching threshold detected BEFORE breakdown.

Metric #4: Sleep-Performance Coupling Score¶

Correlate deep sleep with performance using an individual time lag model. Deep sleep Monday → performance impact Wednesday (not Tuesday). Map each athlete's specific sleep-to-performance delay curve. Some respond in 24h, some in 72h. Changes how you program recovery days.

Metric #5: Sympathetic Load Accumulator¶

LF/HF ratio tracked as a cumulative rolling sum, not a daily snapshot. One day of elevated sympathetic tone = stress. Five consecutive days = overtraining syndrome building. "Credit card balance" for the nervous system — the daily charge matters less than the running balance.

Metric #6: Training Monotony Detector¶

Flags when heart rate zones, movement patterns, and session durations become too similar day-over-day. Adaptation stalls when the body predicts the stimulus. This metric tells coaches when a program needs disruption, not just recovery.

Metric #7: Injury Probability Score (The Big One)¶

Combine CNS Gap + Readiness Asymmetry + Sympathetic Load + Adaptation Velocity into a single probabilistic model. "This athlete has a 73% elevated injury risk in the next 7 days." The metric that sells itself to every athletic director with a budget.

Platform Play¶

Each metric is: - A feature in APA (add-on per metric or bundled in tiers) - A licensable algorithm for other platforms - A publishable case study for credibility - A data moat (calibration coefficients from athlete dataset)

Next Steps¶

Determine which metrics the Garmin Fenix 8 sensor suite can already support
Prioritize 2-3 for prototype alongside GAP Score (General Adaptation Profile)
Research existing academic literature for each