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The Uplift Movement Library is the complete list of all activities, movements, events, and metrics in the Uplift ecosystem. Use it to determine:
  • which activities and movements Uplift supports
  • what events and metrics are included
  • how the events and metrics are calculated
  • what the biomechanical metrics mean
Uplift refers to movements via both the general activity and specific movement (such as baseball-hitting, jump-countermovement, or track_and_field-discus). Within each activity-movement page, view the required input dimensions as well as all variables (events & metrics) to describe movement performance.

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Common Terms

  • Session: A single captured movement or attempt, representing the core unit of data collection. These are tagged with a unique alphanumeric session_id. Sessions captured in a sequence (multiple reps or protocol) will have consecutive session_ids (ABC123_1, ABC123_2, …).
  • Dimension: A labeling or categorization system for Sessions, Metrics, or Events, aiding in organization and filtering. Some dimensions are required for proper processing (such as Handedness: left)
  • Activity: the general activity performed (baseball, jump, stability)
  • Movement: the specific movement performed (pitching, countermovement, y_balance_lower_quarter)
  • Event: A specific point in time within the single movement that marks a critical instant or boundary (ball release, jump landing, bottom)
  • Phase: A distinct segment of the movement within a single session, generally bounded by specific events.
  • Metric: A measured or calculated value that reflects some aspect of the athlete’s movement over the duration of the session
  • Discrete Metric: A single, distilled value extracted from the time-series or raw data within a session, used for quick comparisons or reporting.
Note: For brevity, metrics and discrete metrics are often referred to as “Metrics”

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Technical Details

Each metric and event page includes a Technical Details section that describes how the variable is defined, stored, and interpreted. The parameters are:
  • Variable Type: The role of this variable in the data model.
    • Discrete Metric — a single numeric value extracted from a session (e.g. peak velocity, angle at an event).
    • Continuous Metric — a time-series signal rather than a single scalar.
    • Flag — a boolean per-trial indicator derived from a threshold rule.
    • Dimension — a categorical label used to organize or filter data (e.g. handedness, arm slot type).
  • Data Type: The storage type of the value.
    • Float — a decimal number (e.g. 523.4 deg/s).
    • Boolean — true or false.
    • String — a text category (e.g. "pelvis-trunk-arm").
  • Units: The measurement unit(s) for the metric. Some metrics list two units:
    • raw — the unit returned by the CSV export and Data API (e.g. meters).
    • display — the unit shown in Uplift reports and AI summaries (e.g. inches). When only one unit is listed, it applies to both raw and display values.
  • Column Name: The exact column name in the StarRocks database view. Use this when querying or referencing data programmatically — a mismatch will cause a “column cannot be resolved” error.
  • Aggregation: How multiple trials within a session are collapsed into a single representative value.
    • mean — arithmetic average across trials (used for most continuous metrics).
    • rate — percentage of trials where the flag fired (used for boolean flags).
    • mode — most frequently occurring value (used for categorical/string metrics).
  • Precision: Number of decimal places shown in the UI (e.g. 0 = integer display, 2 = two decimal places).
  • Unknown Value: The sentinel value stored when a metric could not be measured for a trial (currently -1 for all boolean flags). Filter these out before computing statistics.
  • Measurement / Calculation: What the value physically represents or how it is derived from the raw pose data.
  • Timing: The event at which a discrete metric is sampled (e.g. at ball release, at foot contact).
  • Reference: The coordinate frame or zero point used to interpret the value (e.g. 0° = facing home plate).
  • Threshold: For flag metrics, the condition that must be met to set the flag to true.
  • Typical Range: The range of values seen across the broad athlete population. Values outside this range may indicate a data quality issue or an unusual movement pattern.
  • Optimal Direction: How to interpret whether a higher or lower value is desirable.
    • Higher is better — larger values indicate better performance (e.g. peak velocity).
    • Lower is better — smaller values indicate better performance (e.g. time under load).
    • Middle — moderate values are optimal — a range centred around an ideal value; extremes in either direction are suboptimal. See Optimal Range for the target window.
    • N/A — no universal good/bad direction; interpretation depends on context (e.g. arm slot angle, which varies by pitching style).
  • Optimal Range: For Middle metrics, the target window (min–max) that represents ideal performance. Defined as the 25th–75th percentile range from the normative dataset unless otherwise noted.