UFATrack

class Space_data(data_provider='UFATrack', tracking_data_path=tracking_data_path, out_path=None, testing_mode=False).preprocessing() → pd.DataFrame

Load the UFATrack from csv files(s) and convert it into a DataFrame.

Parameters:

• tracking_data_path (str) – Path to the csv file/folder containing tracking data.

• out_path (str, optional) – Path to the output folder where processed data will be saved.

• testing_mode (bool, optional) – If True, run in testing mode with limited data.

Returns:

(event_data_dict, home_tracking_dict, away_tracking_dict) — dictionaries mapping match IDs to respective DataFrames.

Return type:

tuple of dict

Example

from preprocessing import Space_data

tracking_path = './UFATrack/Tracking Data'
out_path = './'

Space_data(data_provider='UFATrack',
        tracking_data_path=tracking_path,
        out_path=out_path
        ).preprocessing()

Details

This function performs the following steps:

1. Retrieves all tracking files from the input directories using get_files().

2. Converts raw tracking data into an intermediate DataFrames using create_intermediate_file.

3. Converts intermediate DataFrames into fixed-format home and away tracking DataFrames and event DataFrames using convert_to_metrica_format.

4. Convert the multi-index tracking columns into a single-row header using format_tracking_headers.

5. Organizes results into dictionaries keyed by match ID:

   • event_data_dict for event DataFrames

   • home_tracking_dict for home team tracking DataFrames

   • away_tracking_dict for away team tracking DataFrames

The returned DataFrames include the following columns:

• Event DataFrame (`event_data_dict[match_id]`):

  • Team: Team associated with the event (‘Home’ or ‘Away’)

  • Type: Type of the event

  • Subtype: Subtype of the event (e.g., ‘success’ or ‘fail’)

  • Period: Period of the match (1 or 2)

  • Start Frame: Frame index at event start

  • Start Time [s]: Time in seconds at event start

  • End Frame: Frame index at event end

  • End Time [s]: Time in seconds at event end

  • From: Player performing the action

  • To: Player receiving the action (if applicable)

  • Start X: Starting x-coordinate of the event

  • Start Y: Starting y-coordinate of the event

  • End X: Ending x-coordinate of the event

  • End Y: Ending y-coordinate of the event

• Home Tracking DataFrame (`home_tracking_dict[match_id]`):

  • Period: Period of the match (1 or 2)

  • Time [s]: Time in seconds

  • Home_1_x … Home_7_x: X-coordinates of home players 1–7

  • Home_1_y … Home_7_y: Y-coordinates of home players 1–7

  • disc_x: Disc X-coordinate

  • disc_y: Disc Y-coordinate

• Away Tracking DataFrame (`away_tracking_dict[match_id]`):

  • Period: Period of the match (1 or 2)

  • Time [s]: Time in seconds

  • Away_1_x … Away_7_x: X-coordinates of away players 1–7

  • Away_1_y … Away_7_y: Y-coordinates of away players 1–7

  • disc_x: Disc X-coordinate

  • disc_y: Disc Y-coordinate