PFF FC

class Event_data(data_provider='pff_fc', event_path=event_path, max_workers=max_workers).load_data()

Load and process PFF FC event data from a JSON file or folder.

Parameters:

  • event_path – Path to the event JSON files/Folder.

  • max_workers (int, optional) – Maximum number of workers to use for parallel processing. Default is 1.

Returns:

DataFrame containing processed event data.

Return type:

pd.DataFrame

Example usage for single match:

import pandas as pd
from preprocessing import Event_data

event_path='path/to/event.json'

pff_fc_df=Event_data(data_provider='pff_fc',event_path=event_path).load_data()
print(pff_fc_df.head())

Example usage for multiple matches:

from preprocessing import Event_data

event_folder='path/to/event/folder'

pff_fc_df=Event_data(data_provider='pff_fc',
                   event_path=event_folder,
                   max_workers=10).load_data()
print(pff_fc_df.head())

Details:

This function reads PFF FC event data from a JSON file and converts it into a DataFrame.

  1. Retrieves all event and tracking files from the input directories.

  2. Converts PFF-style event data to Metrica format.

The returned DataFrame contains the following columns:

  • match_id: Identifier for the match where the event occurred.

  • 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