Signal vs Noise
Signal is the real, repeatable pattern in your swing data; noise is the random variation that looks like a pattern but isn't. Distinguishing the two is what separates useful analysis from false precision.
Every measurement contains some noise — from wind variation, fatigue, timing differences, and video quality fluctuations. Signal is the component of variation that persists across multiple swings and correlates with real performance differences. SwingVantage's confidence scoring and sample-size labeling are both aimed at the signal-vs-noise problem: they help you know whether a finding is real before you commit to changing something that was working. A small delta in a noisy dataset is not a confirmed improvement.
Example
A 1 mph increase in ball speed after a session is within the noise range of phone-video estimation and is labeled "change within measurement uncertainty" — not confirmed progress.
Why it matters
Chasing noise is the fastest way to ruin a swing. SwingVantage labels uncertainty so you only act on real signal.
Related terms
- Sample SizeSample size is how many swings or shots a metric is based on — small samples produce more noise and lower confidence; larger samples produce more reliable estimates.
- Outlier in Swing DataAn outlier is a data point that falls far outside the normal range for that metric and session — it may represent a genuine extreme swing or a measurement artifact, and it requires honest handling before being used in averages.
- Confidence ScoreA confidence score is a 0–100 calibration of how much to trust a finding, scaled by sample size, shot-to-shot consistency, and how complete your inputs were.
- Retest DeltaA retest delta is the change between a pre-drill baseline and the post-drill retest measurement for the same specific metric targeted by that session's fix — the short-cycle confirmation of whether a single training session moved the needle.
Put this into your swing
SwingVantage can spot this in your own swing — free to start.