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Intermediate

Interpreted Value

Also known as: AI interpretation, AI-inferred value

Definition

An interpreted value is a judgment or label that emerged from AI reasoning applied to raw data. This means such as 'likely timing issue' or 'probable hip stall'. Instead of from a direct measurement or a deterministic rule.

Beyond measured facts and heuristic estimates, some findings in SwingVantage come from AI pattern-matching on combinations of signals that the rules engine alone cannot fully resolve. These are interpreted values. This means they are more contextual and nuanced than a deterministic rule output. But also inherently less precise and more subject to AI error. They are labeled 'AI Interpreted' or 'AI-Inferred' and are always accompanied by the evidence that led to them. As a result, you can decide how much weight to give them.

Beginner tip

AI-interpreted findings require more skepticism than deterministic findings. Before changing something based on an interpreted value, verify the underlying evidence. This means look at the cited frames in the timeline and confirm that the cue the AI described is actually visible.

Advanced note

Treat AI interpretations as hypotheses to test, not verdicts to act on immediately. Drill the suggested fix and run a retest to see if the interpretation was directionally correct. This means a positive retest delta validates the interpretation. An inconclusive delta means the interpretation was speculative.

Example

'AI Interpreted: possible mental tempo disruption — the downswing initiated 40ms faster than your average, suggesting a rushing tendency under pressure (Confidence: 55/100).'

How it shows up on video

AI-interpreted findings in Motion Lab appear with a purple [AI] badge and include the specific observable cues that triggered the interpretation. This means for example, "downswing tempo 18% faster than your average. This means interpreted as rushing under pressure." Always verify the cited cue is visible in the timeline before acting on the interpretation.

Common mistakes

  • Treating an AI-interpreted finding as equally authoritative as a deterministic finding — interpretations are inferences from patterns; deterministic findings are direct rule-engine outputs from measured positions.
  • Acting immediately on an AI interpretation without running a drill block to test whether it is correct. This means interpretations are hypotheses. Treat them as such until a retest confirms the direction.
  • Ignoring the evidence panel that accompanies each interpretation. This means the AI always shows what triggered the interpretation. Reviewing this evidence is how you decide whether to accept or question the finding.
  • Not flagging interpretations that seem uneven with your feel or prior coaching. This means inconsistencies are important diagnostic signals that the AI may have interpreted a normal variation as a fault.

In SwingVantage Motion Lab

In Motion Lab, clicking an AI-interpreted finding expands the evidence panel showing the specific landmark data and timing patterns that drove the interpretation. This transparency differs from estimated values — interpretations explain their reasoning explicitly, which you can evaluate and agree or disagree with.

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