Benchmarks

Performance comparison between fast-forward (Rust core) and kloppy (pure Python) across all supported providers.

Load Time

Total wall-clock time to load tracking data into a wide-layout Polars DataFrame.

Peak Memory

Maximum memory usage during the load process.

HawkEye

HawkEye benchmarks use parallel=True, which loads multiple files in parallel. Setting parallel=False decreases peak memory but increases load time.

Load Time per Frame

Load time normalized by the number of frames, showing per-frame overhead independent of file size.

Methodology

• Layout: wide (one row per frame, all players as columns)
• Providers: sorted by input file size (ascending, left to right)
• Configurations:
  • fast-forward (Rust) - eager parallel: Rust-based parsing with parallel I/O where applicable
  • kloppy - provider coordinates & to_df polars: kloppy loading in provider-native coordinates, converted to Polars
  • kloppy - default coordinates & to_df polars: kloppy loading with default coordinate transformation, converted to Polars
• FPS: shown per provider on the x-axis (affects frame count for same-duration matches)