Raw data

Dataset

We’re going to work with a Dataset that describes a football match consisting of the following:

• The following two coordinates:

  • The frame at which the ball is at. There are 250 possible frames in this recording.

  • The cartesian coordinates (x,y) of the ball’s position.

• A DataVariable that describes the trajectory of the ball. It is described by the two coordinates of the Dataset.

• The following two attributes:

  • The match ID, which is 12.

  • The resolution (25 Hz) of the recording in frames per second.

Events

We’re going to create events directly in a DataFrame consisting of the following attributes:

• The event type, which can be: penalty, pass or goal.

• The frame where the event starts.

• The frame where the event ends.

• The ID of the responsible player.

Code

The described dataset can be built as follows:

import numpy as np
import pandas as pd
import xarray as xr
import xarray_events

ds = xr.Dataset(
    data_vars={
        'ball_trajectory': (
            ['frame', 'cartesian_coords'],
            np.exp(np.linspace((-6, -8), (3, 2), 2450))
        )
    },
    coords={
        'frame': np.arange(1, 2451),
        'cartesian_coords': ['x', 'y'],
        'player_id': [2, 3, 7, 19, 20, 21, 22, 28, 34, 79]
    },
    attrs={'match_id': 12, 'resolution_fps': 25}
)

events = pd.DataFrame(
    {
        'event_type':
            ['pass', 'goal', 'pass', 'pass', 'pass',
             'penalty', 'goal', 'pass', 'pass', 'penalty'],
        'start_frame': [1, 425, 600, 945, 1100, 1280, 1890, 2020, 2300, 2390],
        'end_frame': [424, 599, 944, 1099, 1279, 1889, 2019, 2299, 2389, 2450],
        'player_id': [79, 79, 19, 2, 3, 2, 3, 79, 2, 79]
    }
)

The new Dataset looks like this:

ds

<xarray.Dataset>
Dimensions:           (cartesian_coords: 2, frame: 2450, player_id: 10)
Coordinates:
  * frame             (frame) int64 1 2 3 4 5 6 ... 2446 2447 2448 2449 2450
  * cartesian_coords  (cartesian_coords) <U1 'x' 'y'
  * player_id         (player_id) int64 2 3 7 19 20 21 22 28 34 79
Data variables:
    ball_trajectory   (frame, cartesian_coords) float64 0.002479 ... 7.389
Attributes:
    match_id:        12
    resolution_fps:  25

And the new DataFrame looks like this:

events

	event_type	start_frame	end_frame	player_id
0	pass	1	424	79
1	goal	425	599	79
2	pass	600	944	19
3	pass	945	1099	2
4	pass	1100	1279	3
5	penalty	1280	1889	2
6	goal	1890	2019	3
7	pass	2020	2299	79
8	pass	2300	2389	2
9	penalty	2390	2450	79

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