Learn how to read and interpret the key metrics in Soma Analytics. Each section explains the mean data and minute-on-minute (MoM) data so you can understand performance trends and training impact.
Reaction Time (RT)
Mean Data:
Shows the athlete’s overall response speed. A lower mean reaction time means faster responses, but it can hide inconsistency or random spikes.
MoM Data:
Tracks how reaction time changes each minute.
Increase: Fatigue or focus shift toward accuracy.
Decrease: Adapting or task too easy.
Fluctuation: Inconsistent focus or overload.
Stable: Adapted to the task.
Speed (1000/RT)
Mean Data:
Represents the inverse of reaction time, offering a measure of response quickness. Because it’s a reciprocal transformation, it amplifies small improvements in fast responses but is more sensitive to outliers and lapses.
MoM Data:
Shows how response speed fluctuates minute by minute.
Increase: Faster neural processing and improved alertness
Decrease: Fatigue, reduced focus, or a strategic shift toward accuracy
Fluctuation: Inconsistent performance or overload
Stable: Balanced response speed and control
Variation (CV)
Mean Data:
Measures consistency across all trials. Lower variation = more reliable performance.
MoM Data:
Reveals when stability breaks down.
Increase: Fatigue or over-challenge.
Decrease: Adaptation and control.
Fluctuation: Inconsistent focus.
Stable: Well-balanced workload.
RCS (Rate Correct Score)
Mean Data:
Shows how many correct responses per second. Balances speed and accuracy into one efficiency score.
MoM Data:
Shows how efficiency changes through the task.
Increase: Strong adaptation and focus.
Decrease: Fatigue or accuracy bias.
Fluctuation: Inconsistent effort.
Stable: Adapted and efficient.
Accuracy
Mean Data:
Shows how many responses were correct overall. Higher accuracy means greater precision and fewer errors.
MoM Data:
Reveals changes in precision across the session.
Increase: Improved focus and control.
Decrease: Fatigue or overload.
Fluctuation: Inconsistent engagement.
Stable: Adapted performance.
rMSSD
Mean Data:
Represents short-term heart rate variability and parasympathetic recovery. Higher rMSSD reflects good recovery and strong autonomic control.
MoM Data:
Shows how recovery capacity changes in real time.
Increase: Good recovery response and resilience.
Decrease: Signs of accumulated fatigue or stress.
Fluctuation: Inconsistent recovery or external stress factors.
Stable: Balanced recovery and well-managed load.
SDNN
Mean Data:
Represents overall heart rate variability and system adaptability. Higher SDNN reflects good cardiovascular balance and stress tolerance.
MoM Data:
Tracks real-time nervous system balance.
Increase: Good adaptability
Decrease: Fatigue or elevated stress
Fluctuation: Unstable response or poor recovery
Stable: Consistent regulation and balance
Quick Summary
Metric | Mean Tells You | MoM Tells You | What to Look For |
Reaction Time | Average response speed | Fatigue or adaptation | Consistent = control |
Speed | Processing speed (inverse of RT) | Performance trends | Higher = faster processing |
Variation | Consistency | Stability under load | Lower = adaptation |
RCS | Efficiency (speed + accuracy) | Fatigue or control | Higher = efficiency |
Accuracy | Precision | Focus consistency | High and stable = control |
rMSSD / SDNN | Recovery and stress | Stress balance | Stable = recovery |
Reminder
To track HRV (rMSSD, SDNN) and BPM, connect a Polar H10 strap to Soma NPT.