GGST Frame Viewer

This tool provides a data-driven frame viewer for Guilty Gear Strive, enabling players, coaches, and analysts to query and compare frame data across characters and move variants. It normalizes startup (s), active (a), and recovery (r) values, along with on-hit and on-block modifiers, to deliver a consistent basis for practice planning and matchup study. The primary value is reducing time spent searching disparate sources and delivering a transparent, auditable data model for decision making.
Conceptually, the viewer loads a move record (character, move name, optional variant) and exposes computed fields such as total frames, hit_advantage, and block_advantage. Required inputs are character and move; optional inputs include variant and game version. The tool supports batch views, filtering by character or move category, and can export data in CSV or JSON for external analysis. Advanced users can query via API and cache results for repeated lookups.
Who benefits: players sharpening punish setups, coaches planning lab sessions, commentators validating claims, and content creators compiling reference material. Unique differentiators include a normalized data model across variants, immediate computed advantages, and offline or API-enabled workflows. Core features cover input validation, data normalization, multiple move comparisons, and data export, while use cases span practice drills, patch comparison, and reference drafting.
Example scenario: a coach compares two moves across two characters to decide which one to emphasize in a lab session, leveraging computed hit and block advantages to guide drill design.